uttered)
The “discussion” section is intended to explain to your reader what your data can be interpreted to mean. As with all science, the goal for your report is simply to provide evidence that something might be true or untrue—not to prove it unequivocally. The following questions should be addressed in your “discussion” section:
Hogg, Alan. "Tutoring Scientific Writing." Sweetland Center for Writing. University of Michigan, Ann Arbor. 3/15/2011. Lecture.
Swan, Judith A, and George D. Gopen. "The Science of Scientific Writing." American Scientist . 78. (1990): 550-558. Print.
"Scientific Reports." The Writing Center . University of North Carolina, n.d. Web. 5 May 2011. http://www.unc.edu/depts/wcweb/handouts/lab_report_complete.html
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Eureka! It is science fair time! Participating in a science fair is an exciting opportunity to flex your scientific muscles, but that’s not the only skill you will need. A good science fair project also requires writing a clear scientific report.
The purpose of a science fair project report is to carefully describe your results and the scientific process you used so that other people can understand your project and maybe even reproduce it themselves. For this reason, scientists and science students use a common format for science reports that features the components of the scientific method.
This includes selecting a topic or question you want to investigate, making a hypothesis or best guess at what will happen during the experiment, writing a list of materials and the steps you used during the experiment, describing the data you compiled and explaining your results. Of course, you will also want to use cardboard or poster board to create a display for your project. In most cases, vibrant colors, dramatic images and clear lettering will help your display stand out from the crowd.
When it comes to writing up the results of your science fair project, the first step is to summarize what you discovered during your experiment. Many scientists and science students rely on visual representations of the data to help show the reader precisely how the experiment turned out. For example, you might use a table or graph to show your results. This will make your science fair project report look professional and also make it easy to read.
Next, you should tell the reader if the results of your experiment supported your hypothesis or not. It’s important to remember that it is not necessarily better for your original hypothesis to match your results, so you should never alter your data to make them match. Sometimes results that don’t support the hypothesis are actually better science and open the door for further investigation.
You will want to summarize your experimental procedure and comment on whether or not your procedure was effective for answering your scientific question. A crucial part of any scientific investigation is turning an analyst’s eye to the experiment itself. This component of your science fair project report will demonstrate to your audience that you understand how to evaluate both your data and your experiment.
Finally, your science fair project report should address potential changes that might make your experiment more effective and identify areas for further study. One common suggested change is to increase the sample size since a larger sample is usually better for science experiments. When you list areas for future investigation, try to remember any questions or ideas that came up while you were conducting your experiment or while you were analyzing your data.
While writing up the results of your science fair project can seem challenging, it is also an opportunity to make your project stand out. A well-written report highlights all of your hard work and can make the difference between an average science fair project and a truly stellar one.
Classroom activities on the scientific method, how to write conclusions for science projects, how to choose the right science fair project for you, steps & procedures for conducting scientific research, how to write a summary on a science project, how to come up with a killer science fair project idea, how to report a sample size, elements of a science project, how to write word problems for math, note taking tips for science class, how to do a 2nd grade science project, how to succeed in a science major, 8 parts of science fair projects, how to interpret likert surveys, five characteristics of the scientific method, how to do a quantitative research questionnaire.
About the Author
Melissa Mayer is an eclectic science writer with experience in the fields of molecular biology, proteomics, genomics, microbiology, biobanking and food science. In the niche of science and medical writing, her work includes five years with Thermo Scientific (Accelerating Science blogs), SomaLogic, Mental Floss, the Society for Neuroscience and Healthline. She has also served as interim associate editor for a glossy trade magazine read by pathologists, Clinical Lab Products, and wrote a non-fiction YA book (Coping with Date Rape and Acquaintance Rape). She has two books forthcoming covering the neuroscience of mental health.
Writing a scientific paper.
Figures and Captions in Lab Reports
Additional tips for results sections.
This is the core of the paper. Don't start the results sections with methods you left out of the Materials and Methods section. You need to give an overall description of the experiments and present the data you found.
A short article by Dr. Brett Couch and Dr. Deena Wassenberg, Biology Program, University of Minnesota
From: https://writingcenter.gmu.edu/guides/imrad-results-discussion
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What this handout is about.
This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.
Why do we write research reports.
You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?
To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.
So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:
Your job as a writer, then, is to fulfill these two goals.
Good question. Here is the basic format scientists have designed for research reports:
This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.
The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.
states your hypothesis | explains how you derived that hypothesis and how it connects to previous research; gives the purpose of the experiment/study | |
details how you tested your hypothesis | clarifies why you performed your study in that particular way | |
provides raw (i.e., uninterpreted) data collected | (perhaps) expresses the data in table form, as an easy-to-read figure, or as percentages/ratios | |
considers whether the data you obtained support the hypothesis | explores the implications of your finding and judges the potential limitations of your experimental design |
Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.
Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.
The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:
Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.
How do i write a strong introduction.
For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.
The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.
For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.
As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.
Not a hypothesis:
“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”
Hypothesis:
“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”
Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.
You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?
Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.
This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.
Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.
Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:
“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”
Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.
As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.
Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.
With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.
Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:
Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:
“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”
Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.
Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.
Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.
Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.
Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.
This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:
“Table 1 lists the rates of solubility for each substance”
“Solubility increased as the temperature of the solution increased (see Figure 1).”
If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.
Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:
“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”
This point isn’t debatable—you’re just pointing out what the data show.
As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)
You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.
Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?
As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.
As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:
As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.
When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:
It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:
The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.
1058 |
432 |
7 |
Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.
Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.
If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.
Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.
Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.
At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.
Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:
The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.
Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:
Let’s look at some dos and don’ts for each of these objectives.
This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,
“The hypothesis that temperature change would not affect solubility was not supported by the data.”
Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.
Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).
You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.
Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.
If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.
This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.
We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.
If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)
This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.
Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.
We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.
American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.
Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.
Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.
Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.
Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.
Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.
Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.
Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.
Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.
Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.
You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill
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Students tend to approach writing lab reports with confusion and dread. Whether in high school science classes or undergraduate laboratories, experiments are always fun and games until the times comes to submit a lab report. What if we didn’t need to spend hours agonizing over this piece of scientific writing? Our lives would be so much easier if we were told what information to include, what to do with all their data and how to use references. Well, here’s a guide to all the core components in a well-written lab report, complete with an example.
The laboratory report is simply a way to show that you understand the link between theory and practice while communicating through clear and concise writing. As with all forms of writing, it’s not the report’s length that matters, but the quality of the information conveyed within. This article outlines the important bits that go into writing a lab report (title, abstract, introduction, method, results, discussion, conclusion, reference). At the end is an example report of reducing sugar analysis with Benedict’s reagent.
The report’s title should be short but descriptive, indicating the qualitative or quantitative nature of the practical along with the primary goal or area of focus.
Following this should be the abstract, 2-3 sentences summarizing the practical. The abstract shows the reader the main results of the practical and helps them decide quickly whether the rest of the report is relevant to their use. Remember that the whole report should be written in a passive voice .
The introduction provides context to the experiment in a couple of paragraphs and relevant diagrams. While a short preamble outlining the history of the techniques or materials used in the practical is appropriate, the bulk of the introduction should outline the experiment’s goals, creating a logical flow to the next section.
Some reports require you to write down the materials used, which can be combined with this section. The example below does not include a list of materials used. If unclear, it is best to check with your teacher or demonstrator before writing your lab report from scratch.
Step-by-step methods are usually provided in high school and undergraduate laboratory practicals, so it’s just a matter of paraphrasing them. This is usually the section that teachers and demonstrators care the least about. Any unexpected changes to the experimental setup or techniques can also be documented here.
The results section should include the raw data that has been collected in the experiment as well as calculations that are performed. It is usually appropriate to include diagrams; depending on the experiment, these can range from scatter plots to chromatograms.
The discussion is the most critical part of the lab report as it is a chance for you to show that you have a deep understanding of the practical and the theory behind it. Teachers and lecturers tend to give this section the most weightage when marking the report. It would help if you used the discussion section to address several points:
Finally, a short paragraph to conclude the laboratory report. It should summarize the findings and provide an objective review of the experiment.
If any external sources were used in writing the lab report, they should go here. Referencing is critical in scientific writing; it’s like giving a shout out (known as a citation) to the original provider of the information. It is good practice to have at least one source referenced, either from researching the context behind the experiment, best practices for the method used or similar industry standards.
Google Scholar is a good resource for quickly gathering references of a specific style . Searching for the article in the search bar and clicking on the ‘cite’ button opens a pop-up that allows you to copy and paste from several common referencing styles.
Title : Semi-Quantitative Analysis of Food Products using Benedict’s Reagent
Abstract : Food products (milk, chicken, bread, orange juice) were solubilized and tested for reducing sugars using Benedict’s reagent. Milk contained the highest level of reducing sugars at ~2%, while chicken contained almost no reducing sugars.
Introduction : Sugar detection has been of interest for over 100 years, with the first test for glucose using copper sulfate developed by German chemist Karl Trommer in 1841. It was used to test the urine of diabetics, where sugar was present in high amounts. However, it wasn’t until 1907 when the method was perfected by Stanley Benedict, using sodium citrate and sodium carbonate to stabilize the copper sulfate in solution. Benedict’s reagent is a bright blue because of the copper sulfate, turning green and then red as the concentration of reducing sugars increases.
Benedict’s reagent was used in this experiment to compare the amount of reducing sugars between four food items: milk, chicken solution, bread and orange juice. Following this, standardized glucose solutions (0.0%, 0.5%, 1.0%, 1.5%, 2.0%) were tested with Benedict’s reagent to determine the color produced at those sugar levels, allowing us to perform a semi-quantitative analysis of the food items.
Method : Benedict’s reagent was prepared by mixing 1.73 g of copper (II) sulfate pentahydrate, 17.30 g of sodium citrate pentahydrate and 10.00 g of sodium carbonate anhydrous. The mixture was dissolved with stirring and made up to 100 ml using distilled water before filtration using filter paper and a funnel to remove any impurities.
4 ml of milk, chicken solution and orange juice (commercially available) were measured in test tubes, along with 4 ml of bread solution. The bread solution was prepared using 4 g of dried bread ground with mortar and pestle before diluting with distilled water up to 4 ml. Then, 4 ml of Benedict’s reagent was added to each test tube and placed in a boiling water bath for 5 minutes, then each test tube was observed.
Next, glucose solutions were prepared by dissolving 0.5 g, 1.0 g, 1.5 g and 2.0 g of glucose in 100 ml of distilled water to produce 0.5%, 1.0%, 1.5% and 2.0% solutions, respectively. 4 ml of each solution was added to 4 ml of Benedict’s reagent in a test tube and placed in a boiling water bath for 5 minutes, then each test tube was observed.
Results : Food Solutions (4 ml) with Benedict’s Reagent (4 ml)
Food Solutions | Color Observed |
---|---|
Milk | Red |
Chicken Solution | Blue |
Bread | Green |
Orange Juice | Orange |
Glucose Solutions (4 ml) with Benedict’s Reagent (4 ml)
Glucose Solutions | Color Observed |
---|---|
0.0% (Control) | Blue |
0.5% | Green |
1.0% | Dark Green |
1.5% | Orange |
2.0% | Red |
Semi-Quantitative Analysis from Data
Food Solutions | Sugar Levels |
---|---|
Milk | 2.0% |
Chicken Solution | 0.0% |
Bread | 0.5% |
Orange Juice | 1.5% |
Discussion : From the analysis of food solutions along with the glucose solutions of known concentrations, the semi-quantitative analysis of sugar levels in different food products was performed. Milk had the highest sugar content of 2%, with orange juice at 1.5%, bread at 0.5% and chicken with 0% sugar. These values were approximated; the standard solutions were not the exact color of the food solutions, but the closest color match was chosen.
One point of contention was using the orange juice solution, which conferred color to the starting solution, rendering it green before the reaction started. This could have led to the final color (and hence, sugar quantity) being inaccurate. Also, since comparing colors using eyesight alone is inaccurate, the experiment could be improved with a colorimeter that can accurately determine the exact wavelength of light absorbed by the solution.
Another downside of Benedict’s reagent is its inability to react with non-reducing sugars. Reducing sugars encompass all sugar types that can be oxidized from aldehydes or ketones into carboxylic acids. This means that all monosaccharides (glucose, fructose, etc.) are reducing sugars, while only select polysaccharides are. Disaccharides like sucrose and trehalose cannot be oxidized, hence are non-reducing and will not react with Benedict’s reagent. Furthermore, Benedict’s reagent cannot distinguish between different types of reducing sugars.
Conclusion : Using Benedict’s reagent, different food products were analyzed semi-quantitatively for their levels of reducing sugars. Milk contained around 2% sugar, while the chicken solution had no sugar. Overall, the experiment was a success, although the accuracy of the results could have been improved with the use of quantitative equipment and methods.
Reference :
Using this guide and example, writing a lab report should be a hassle-free, perhaps even enjoyable process!
Sean is a consultant for clients in the pharmaceutical industry and is an associate lecturer at La Trobe University, where unfortunate undergrads are subject to his ramblings on chemistry and pharmacology.
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The nature of dark matter, the invisible substance thought to make up most of the mass in our universe, is one of the greatest mysteries in physics. Using new results from the world’s most sensitive dark matter detector, LUX-ZEPLIN (LZ), an international collaboration that includes Penn State researchers has narrowed down the possible properties of one of the leading candidates for the particles that compose dark matter: weakly interacting massive particles, or WIMPs.
Dark matter , so named because it does not emit, reflect or absorb light, is estimated to make up 85% of the mass in the universe. Although it has never been directly detected, it has left its fingerprints on multiple astronomical observations.
“Dark matter is a fundamental part of the universe; and we wouldn’t exist without it; dark matter’s mass contributes to the gravitational attraction that helps galaxies form and stay together,” said Carmen Carmona-Benitez, associate professor of physics and the LZ principal investigator at Penn State. “LZ is designed to detect cosmic particles passing through earth, including theorized dark matter particles called WIMPs, with great sensitivity. Based on what we detect — and more often, what we don’t detect — we can put additional limits or constraints on the potential characteristics and properties of WIMPs and get a better sense of what exactly these particles are and aren’t.”
LZ, led by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), is located in a cavern nearly one mile underground at the Sanford Underground Research Facility in South Dakota. Researchers at Penn State play a key role in the experiment, contributing to the operation of the detector and the analysis that led to the latest results. The experiment’s new results explore weaker dark matter interactions than ever searched before and further limits what WIMPs could be.
“These are new world-leading constraints by a sizable margin on dark matter and WIMPs,” said Chamkaur Ghag, spokesperson for LZ and a professor at University College London (UCL). He noted that the detector and analysis techniques are performing even better than the collaboration expected. “If WIMPs had been within the region we searched, we’d have been able to robustly say something about them. We know we have the sensitivity and tools to see whether they’re there as we search lower energies and accrue the bulk of this experiment’s lifetime.”
The collaboration found no evidence of WIMPs above a mass of nine gigaelectronvolts per the speed of light in a vacuum squared (GeV/c2). For comparison, the mass of a proton is slightly less than one GeV/c2. The experiment's sensitivity to faint interactions helps researchers reject potential WIMP dark matter models that don't fit the data, leaving significantly fewer places for WIMPs to hide. The new results were presented at two physics conferences on Aug. 26: TeV Particle Astrophysics 2024 in Chicago, Illinois, and LIDINE 2024 in São Paulo, Brazil. A scientific paper will be published in the coming weeks. The results include analysis of 280 days’ worth of data: a new set of 220 days collected between March 2023 and April 2024 combined with 60 earlier days from LZ’s first run. The collaboration plans to collect 1,000 days’ worth of data before the experiment ends in 2028.
“LZ is at least 50 times more sensitive than previous dark matter detectors,” said Luiz de Viveiros, assistant professor of physics at Penn State, whose team is responsible for modeling and monitoring background signals in the detector. “Its sensitivity comes from the many ways the detector can reduce background noise, which are signals that can hide or impersonate a dark matter interaction.”
LZ’s deep underground location shields the detector from cosmic rays coming from space, helping reduce background noise. LZ was also built from thousands of ultraclean, low-radiation parts to reduce natural radiation from everyday objects. The detector is built like an onion, with each layer either blocking outside radiation or tracking particle interactions to rule out dark matter mimics. Additionally, sophisticated new analysis techniques help rule out background interactions.
This result is also the first time that LZ has applied “salting” — a technique that adds fake WIMP signals during data collection.
“By camouflaging the real data until ‘unsalting’ at the very end, researchers can avoid unconscious bias and keep from overly interpreting or changing their analysis,” said David Woodward, former assistant research professor at Penn State, now program manager with LZ at Berkeley Lab.
LZ uses 10 tonnes, or 10,000 kilograms, of liquid xenon to provide a dense, transparent material for dark matter particles to potentially bump into. The hope, the researchers said, is for a WIMP to knock into a xenon nucleus, causing it to move, much like a hit from a cue ball in a game of pool. By collecting the light and electrons emitted during interactions, LZ captures potential WIMP signals alongside other data.
“Researchers have only scratched the surface of what LZ can do,” Carmona-Benitez said. “With the detector’s exceptional sensitivity and advanced analysis techniques, our collaboration is primed to discover dark matter if it exists within the experiment’s reach and to explore other rare physics phenomena.”
The next stage is using these data to look at other interesting and rare physics processes, like rare decays of xenon atoms, neutrino-less double beta decay, boron-8 neutrinos from the sun and other beyond-the-standard-model physics. Future data sets and new analysis techniques will allow the collaboration to look for even lower-mass dark matter.
LZ is a collaboration of roughly 250 scientists from 38 institutions in the United States, United Kingdom, Portugal, Switzerland, South Korea and Australia.
LZ is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation, and the Institute for Basic Science, Korea. Over 38 institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility.
Editor’s Note: A version of this release originally appeared at the Berkeley Lab website .
New results leave fewer places for elusive dark matter particles to hide.
Figuring out the nature of dark matter, the invisible substance that makes up most of the mass in our universe, is one of the greatest puzzles in physics. New results from the world’s most sensitive dark matter detector, LUX-ZEPLIN (LZ), have narrowed down possibilities for one of the leading dark matter candidates: weakly interacting massive particles, or WIMPs.
LZ, led by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), hunts for dark matter from a cavern nearly one mile underground at the Sanford Underground Research Facility in South Dakota. Mani Tripathi, Distinguished Professor in the UC Davis Department of Physics and Astronomy, is a member of the LZ project team.
The experiment’s new results explore weaker dark matter interactions than ever searched before and further limit what WIMPs could be.
“These are new world-leading constraints by a sizable margin on dark matter and WIMPs,” said Chamkaur Ghag, spokesperson for LZ and a professor at University College London (UCL). He noted that the detector and analysis techniques are performing even better than the collaboration expected. “If WIMPs had been within the region we searched, we’d have been able to robustly say something about them. We know we have the sensitivity and tools to see whether they’re there as we search lower energies and accrue the bulk of this experiment’s lifetime.”
The collaboration found no evidence of WIMPs above a mass of 9 gigaelectronvolts/c 2 (GeV/c 2 ). (For comparison, the mass of a proton is slightly less than 1 GeV/c 2 .) The experiment's sensitivity to faint interactions helps researchers reject potential WIMP dark matter models that don't fit the data, leaving significantly fewer places for WIMPs to hide. The new results were presented at two physics conferences on August 26: TeV Particle Astrophysics 2024 in Chicago, Illinois, and LIDINE 2024 in São Paulo, Brazil. A scientific paper will be published in the coming weeks.
The results analyze 280 days’ worth of data: a new set of 220 days (collected between March 2023 and April 2024) combined with 60 earlier days from LZ’s first run. The experiment plans to collect 1,000 days’ worth of data before it ends in 2028.
“If you think of the search for dark matter like looking for buried treasure, we’ve dug almost five times deeper than anyone else has in the past,” said Scott Kravitz, LZ’s deputy physics coordinator and a professor at the University of Texas at Austin. “That’s something you don’t do with a million shovels – you do it by inventing a new tool.”
LZ’s sensitivity comes from the myriad ways the detector can reduce backgrounds, the false signals that can impersonate or hide a dark matter interaction. Deep underground, the detector is shielded from cosmic rays coming from space. To reduce natural radiation from everyday objects, LZ was built from thousands of ultraclean, low-radiation parts. The detector is built like an onion, with each layer either blocking outside radiation or tracking particle interactions to rule out dark matter mimics. And sophisticated new analysis techniques help rule out background interactions, particularly those from the most common culprit: radon.
This result is also the first time that LZ has applied “salting”– a technique that adds fake WIMP signals during data collection. By camouflaging the real data until “unsalting” at the very end, researchers can avoid unconscious bias and keep from overly interpreting or changing their analysis.
“We’re pushing the boundary into a regime where people have not looked for dark matter before,” said Scott Haselschwardt, the LZ physics coordinator and a recent Chamberlain Fellow at Berkeley Lab who is now an assistant professor at the University of Michigan. “There’s a human tendency to want to see patterns in data, so it’s really important when you enter this new regime that no bias wanders in. If you make a discovery, you want to get it right.”
Dark matter, so named because it does not emit, reflect, or absorb light, is estimated to make up 85% of the mass in the universe but has never been directly detected, though it has left its fingerprints on multiple astronomical observations. We wouldn’t exist without this mysterious yet fundamental piece of the universe; dark matter’s mass contributes to the gravitational attraction that helps galaxies form and stay together.
LZ uses 10 tonnes of liquid xenon to provide a dense, transparent material for dark matter particles to potentially bump into. The hope is for a WIMP to knock into a xenon nucleus, causing it to move, much like a hit from a cue ball in a game of pool. By collecting the light and electrons emitted during interactions, LZ captures potential WIMP signals alongside other data.
“We’ve demonstrated how strong we are as a WIMP search machine, and we’re going to keep running and getting even better – but there’s lots of other things we can do with this detector,” said Amy Cottle, lead on the WIMP search effort and an assistant professor at UCL. “The next stage is using these data to look at other interesting and rare physics processes, like rare decays of xenon atoms, neutrinoless double beta decay, boron-8 neutrinos from the sun, and other beyond-the-Standard-Model physics. And this is in addition to probing some of the most interesting and previously inaccessible dark matter models from the last 20 years.”
LZ is a collaboration of roughly 250 scientists from 38 institutions in the United States, United Kingdom, Portugal, Switzerland, South Korea, and Australia; much of the work building, operating, and analyzing the record-setting experiment is done by early career researchers. The collaboration is already looking forward to analyzing the next data set and using new analysis tricks to look for even lower-mass dark matter. Scientists are also thinking through potential upgrades to further improve LZ, and planning for a next-generation dark matter detector called XLZD.
“Our ability to search for dark matter is improving at a rate faster than Moore’s Law,” Kravitz said. “If you look at an exponential curve, everything before now is nothing. Just wait until you see what comes next.”
LZ is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation, and the Institute for Basic Science, Korea. Over 38 institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility.
News release from Lawrence Berkeley Lab
LUX-ZEPLIN Dark Matter Detector Starts Up (2022)
Media Contacts
Lauren Biron is a science writer at the Lawrence Berkeley Laboratory.
Secondary categories.
Dr Theresa Fruth, from the School of Physics, prepares to descend a mile underground at the LZ experiment facility in South Dakota, USA.
Figuring out the nature of dark matter, the invisible substance that makes up most of the mass in our universe, is one of the greatest unsolved puzzles in modern physics. New results from the world’s most sensitive dark matter detector, LUX-ZEPLIN (LZ), have narrowed down possibilities for one of the leading dark matter candidates: weakly interacting massive particles, or WIMPs.
LZ, led by the United States Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), hunts for dark matter from a cavern nearly one mile underground at the Sanford Underground Research Facility in South Dakota. The experiment’s new results have set further limits on what WIMPs could be.
Dr Theresa Fruth from the School of Physics at the University of Sydney was instrumental in commissioning the LZ detector in South Dakota and is an active participant in the hunt for dark matter at the LZ experiment. She has worked on the project for nine years, including during her time at the University of Oxford and University College London.
“This detector is the best asset we have anywhere in the world in our hunt for WIMP dark matter over coming years. This result shows how sensitive the detector is and how useful it will be in helping us to solve this most intriguing of scientific puzzles,” she said.
LZ’s central detector in a surface lab clean room before delivery underground. Photo: Matthew Kapust/Sanford Underground Research Facility
Dark matter, so named because it does not emit, reflect, or absorb light, is estimated to make up 85 percent of the mass in the universe but has never been directly detected, though it has left its fingerprints on multiple astronomical observations.
Dr Fruth said: “We wouldn’t exist without this mysterious yet fundamental piece of the universe; dark matter’s mass contributes to the gravitational attraction that helps galaxies form.”
In the new result, the team found no evidence of WIMPs above 9 giga-electronvolts/c2 (GeV/c2), which is 1.6 x 10-26 kilograms, about ten times the mass of a proton.
“While finding ‘nothing’ doesn’t sound like much of a result, this is hugely important in narrowing down where we could find direct evidence of dark matter,” Dr Fruth said.
“Will dark matter fit snugly into the Standard Model of particle physics, or will its discovery need us to rewrite our theoretical models? We simply don’t know yet.”
The important new data has been presented today at physics conferences in Chicago, USA, and São Paulo, Brazil. A paper will be prepared for peer-review in coming weeks.
“If you think of the search for dark matter like looking for buried treasure, we’ve dug almost five times deeper than anyone else has in the past,” said Professor Scott Kravitz, LZ’s deputy physics coordinator and a professor at the University of Texas at Austin. “That’s something you don’t do with a million shovels, you do it by inventing a new tool.”
Researchers sit between two outer layers of LZ during construction. Photo: Matthew Kapust/Sanford Underground Research Facility
Professor Chamkaur Ghag, LZ spokesperson and professor University College London said: “These are new world-leading constraints by a sizable margin on dark matter and WIMPs. We know we have the sensitivity and tools to see whether they’re there as we search lower energies and accrue the bulk of this experiment’s lifetime.”
The experiment’s sensitivity to faint interactions helps researchers reject potential WIMP dark matter models that don’t fit the data, leaving fewer places for WIMPs to hide.
This result is also the first time that LZ has applied “salting”– a technique that adds fake WIMP signals during data collection. By camouflaging the real data until “unsalting” at the very end, researchers can avoid unconscious bias and keep from overly interpreting or changing their analysis.
“We’re pushing the boundary into a regime where people have not looked for dark matter before,” said Scott Haselschwardt, the LZ physics coordinator and a recent Chamberlain Fellow at Berkeley Lab who is now an assistant professor at the University of Michigan. “There’s a human tendency to want to see patterns in data, so it’s really important when you enter this new regime that no bias wanders in. If you make a discovery, you want to get it right.”
LZ uses 10 tonnes of liquid xenon at 175 Kelvin (minus 98.15 degrees) to provide a dense, transparent material for dark matter particles to potentially bump into. The hope is for a WIMP to knock into a xenon nucleus, causing it to move, much like a hit from a cue ball in a game of pool. By collecting the light emitted during such interactions by the detector’s 494 light sensors, LZ could capture WIMP signals with other rare events.
LZ is a collaboration of about 250 scientists from 38 institutions in the United States, United Kingdom, Portugal, Switzerland, South Korea, and Australia.
Dr Fruth leads the only Australian-based research group working on LZ. She is also a collaborator at the Australian dark matter detector (SABRE South) being built in an active gold mine in Stawell, Victoria.
LZ Completes TPC Assembly from Sanford Lab on Vimeo .
LZ is supported by the US Department of Energy, Office of Science, Office of High Energy Physics and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation, and the Institute for Basic Science, Korea. More than 38 institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility.
Downloading nasa's dark matter data from above the clouds, the hunt for dark matter: sydney joins arc centre of excellence, student astronomer finds galactic missing matter.
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New results from the world's most sensitive dark matter detector put the best-ever limits on particles called wimps, a leading candidate for what makes up our universe's invisible mass.
August 26, 2024
By Lauren Biron
LZ's central detector, the time projection chamber, in a surface lab clean room before delivery underground. Credit: Matthew Kapust/Sanford Underground Research Facility
Editor's note: The following news release was issued by the U.S. Department of Energy’s Lawrence Berkeley National Laboratory on behalf of the LZ collaboration, a group of scientists conducting an underground experiment designed to directly detect theorized dark matter particles known as WIMPs (weakly interacting massive particles). Scientists from DOE’s Brookhaven National Laboratory neutrino and nuclear chemistry group (NNC) developed the liquid scintillator that fills an essential component of the detector designed to veto false signals. The group produced 20 tons of gadolinium-doped liquid scintillator and delivered the materials to the LZ detector at the Sanford Underground Research Facility (SURF) in Lead, South Dakota in 2020. For more information about Brookhaven’s role in this research, contact Karen McNulty Walsh, 631-344-8350, [email protected] .
Figuring out the nature of dark matter, the invisible substance that makes up most of the mass in our universe, is one of the greatest puzzles in physics. New results from the world’s most sensitive dark matter detector, LUX-ZEPLIN (LZ), have narrowed down possibilities for one of the leading dark matter candidates: weakly interacting massive particles, or WIMPs.
LZ, led by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), hunts for dark matter from a cavern nearly one mile underground at the Sanford Underground Research Facility in South Dakota. The experiment’s new results explore weaker dark matter interactions than ever searched before and further limit what WIMPs could be.
“These are new world-leading constraints by a sizable margin on dark matter and WIMPs,” said Chamkaur Ghag, spokesperson for LZ and a professor at University College London (UCL). He noted that the detector and analysis techniques are performing even better than the collaboration expected. “If WIMPs had been within the region we searched, we’d have been able to robustly say something about them. We know we have the sensitivity and tools to see whether they’re there as we search lower energies and accrue the bulk of this experiment’s lifetime.”
An array of photomultiplier tubes that are designed to detect signals from particle interactions occurring within LZ's liquid xenon detector. Credit: Matthew Kapust/Sanford Underground Research Facility
The collaboration found no evidence of WIMPs above a mass of 9 gigaelectronvolts/c 2 (GeV/c 2 ). (For comparison, the mass of a proton is slightly less than 1 GeV/c 2 .) The experiment's sensitivity to faint interactions helps researchers reject potential WIMP dark matter models that don't fit the data, leaving significantly fewer places for WIMPs to hide. The new results were presented at two physics conferences on August 26: TeV Particle Astrophysics 2024 in Chicago, Illinois, and LIDINE 2024 in São Paulo, Brazil. A science paper will be published in the coming weeks.
The results analyze 280 days’ worth of data: a new set of 220 days (collected between March 2023 and April 2024) combined with 60 earlier days from LZ’s first run. The experiment plans to collect 1,000 days’ worth of data before it ends in 2028.
“If you think of the search for dark matter like looking for buried treasure, we’ve dug almost five times deeper than anyone else has in the past,” said Scott Kravitz, LZ’s deputy physics coordinator and a professor at the University of Texas at Austin. “That’s something you don’t do with a million shovels – you do it by inventing a new tool.”
LZ’s sensitivity comes from the myriad ways the detector can reduce backgrounds, the false signals that can impersonate or hide a dark matter interaction. Deep underground, the detector is shielded from cosmic rays coming from space. To reduce natural radiation from everyday objects, LZ was built from thousands of ultraclean, low-radiation parts. The detector is built like an onion, with each layer either blocking outside radiation or tracking particle interactions to rule out dark matter mimics. And sophisticated new analysis techniques help rule out background interactions, particularly those from the most common culprit: radon.
This result is also the first time that LZ has applied “salting”– a technique that adds fake WIMP signals during data collection. By camouflaging the real data until “unsalting” at the very end, researchers can avoid unconscious bias and keep from overly interpreting or changing their analysis.
“We’re pushing the boundary into a regime where people have not looked for dark matter before,” said Scott Haselschwardt, the LZ physics coordinator and a recent Chamberlain Fellow at Berkeley Lab who is now an assistant professor at the University of Michigan. “There’s a human tendency to want to see patterns in data, so it’s really important when you enter this new regime that no bias wanders in. If you make a discovery, you want to get it right.”
Members of the LZ team in the LZ water tank after the outer detector installation. Credit: Matthew Kapust/Sanford Underground Research Facility
Dark matter, so named because it does not emit, reflect, or absorb light, is estimated to make up 85% of the mass in the universe but has never been directly detected, though it has left its fingerprints on multiple astronomical observations. We wouldn’t exist without this mysterious yet fundamental piece of the universe; dark matter’s mass contributes to the gravitational attraction that helps galaxies form and stay together.
LZ uses 10 tonnes of liquid xenon to provide a dense, transparent material for dark matter particles to potentially bump into. The hope is for a WIMP to knock into a xenon nucleus, causing it to move, much like a hit from a cue ball in a game of pool. By collecting the light and electrons emitted during interactions, LZ captures potential WIMP signals alongside other data.
“We’ve demonstrated how strong we are as a WIMP search machine, and we’re going to keep running and getting even better – but there’s lots of other things we can do with this detector,” said Amy Cottle, lead on the WIMP search effort and an assistant professor at UCL. “The next stage is using these data to look at other interesting and rare physics processes, like rare decays of xenon atoms, neutrinoless double beta decay, boron-8 neutrinos from the sun, and other beyond-the-Standard-Model physics. And this is in addition to probing some of the most interesting and previously inaccessible dark matter models from the last 20 years.”
LZ is a collaboration of roughly 250 scientists from 38 institutions in the United States, United Kingdom, Portugal, Switzerland, South Korea, and Australia; much of the work building, operating, and analyzing the record-setting experiment is done by early career researchers. The collaboration is already looking forward to analyzing the next data set and using new analysis tricks to look for even lower-mass dark matter. Scientists are also thinking through potential upgrades to further improve LZ, and planning for a next-generation dark matter detector called XLZD.
“Our ability to search for dark matter is improving at a rate faster than Moore’s Law,” Kravitz said. “If you look at an exponential curve, everything before now is nothing. Just wait until you see what comes next.”
LZ is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation, and the Institute for Basic Science, Korea. Over 38 institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility.
Members of the LZ collaboration gather at the Sanford Underground Research Facility in June 2023, shortly after the experiment began the recent science run. Credit: Stephen Kenny/Sanford Underground Research Facility
Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to delivering solutions for humankind through research in clean energy, a healthy planet, and discovery science. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 16 Nobel Prizes. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science.
DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science .
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