Chemists, physicists and materials scientists ask how matter and energy behave, then turn the answers into batteries, medicines, sensors, chips and new materials. This beginner course shows what these careers actually involve and how people get into them.

Module 1 maps the physics, chemistry and math each field builds on, explains how experiment, simulation and instruments work together, and gives you the habit every scientist relies on: checking a result with units and a quick estimate. Module 2 covers the research path honestly: what a bachelor's, master's or PhD qualifies you for, how to build evidence such as an undergraduate research poster, and where industry and national-lab openings are posted. Module 3 teaches the everyday skills of reading a paper, finding literature on Google Scholar and arXiv, and keeping a lab notebook that someone else could follow.

Every lesson has a reading, free videos from reputable educators and a quiz, and most have a hands-on activity you can do safely at home. This course teaches knowledge and career navigation. It does not replace an accredited degree, hands-on lab courses or the safety training and supervision your institution or employer provides before you work in a real lab. It builds on STEM Foundations.

How chemists, physicists and materials scientists work: the science and math core, units and estimation, the research path, and how to read and record science.

Foundations for Physical Science & Materials Careers

## Why this matters

Chemists, physicists and materials scientists often work in the same building, use the same instruments and publish in the same journals. What separates them is the question they start from. Knowing which topics each field leans on helps you choose courses, read job postings and see why the math requirements look so heavy.

## Three fields, three starting questions

- **Physics** asks how matter and energy behave at the most basic level: motion, forces, energy, waves, electricity and magnetism, heat, light, and the quantum behaviour of atoms and particles. Physicists build models that predict, then test them against measurement.
- **Chemistry** asks how atoms bond and how substances change into other substances: structure, reactions, rates, equilibrium and energy changes. Chemists make, separate, identify and measure substances.
- **Materials science** asks how the structure of a material (its atoms, crystals, grains and defects) controls its properties (strength, conductivity, colour, corrosion resistance), and how processing changes that structure. It sits between physics, chemistry and engineering.

A single product shows how the fields overlap. A lithium-ion battery needs chemists to design the electrolyte reactions, physicists to model how ions and electrons move, and materials scientists to make electrodes that survive thousands of charge cycles without cracking.

## The shared math core

All three fields are math-heavy, and the math builds in a predictable order:

| Topic | What it lets you do | Where you meet it |
|---|---|---|
| Algebra and functions | Rearrange formulas, work with exponents and logs | Every lab report |
| Calculus | Describe rates of change and totals | Motion, reaction rates, heat flow |
| Differential equations | Model systems that change over time | Radioactive decay, cooling, kinetics |
| Linear algebra | Handle many variables at once | Crystal structures, quantum mechanics, data fitting |
| Statistics | Report uncertainty and compare results | Every measurement you publish |

You do not need all of this before you start. Most bachelor's programmes spread it over the first two years, alongside the science courses that use it.

## What each field adds on top

Beyond the shared core, each field has its own spine of courses:

- **Physics:** classical mechanics, electromagnetism, thermodynamics and statistical mechanics, quantum mechanics, optics, plus a lot of lab and computing.
- **Chemistry:** general chemistry, organic chemistry, analytical chemistry, physical chemistry (where chemistry meets physics and calculus), inorganic chemistry and biochemistry, with many hours of hands-on lab work.
- **Materials science:** chemistry and physics foundations, then crystallography, thermodynamics of materials, phase diagrams, mechanical behaviour, and characterisation techniques such as microscopy and X-ray diffraction.

## Worked example: reading a job posting

Suppose a posting for an entry-level "Materials Characterisation Scientist" asks for:

1. A degree in materials science, chemistry or physics.
2. Experience with X-ray diffraction (XRD) and scanning electron microscopy (SEM).
3. Python or MATLAB for data analysis.
4. Clear written reports.

Map each line to the foundations: (1) any of the three fields can qualify, because the work is shared; (2) is instrumentation, which you meet in upper-level lab courses and research; (3) is the computing that sits on top of the math core; (4) is communication, which every field needs. The posting is not asking for one narrow degree. It is asking for the shared foundation plus specific hands-on skills.

## Common mistakes

- **Treating the fields as separate boxes.** Many careers move between them. A physics graduate can work as a materials scientist, and a chemist can work on semiconductor processing.
- **Avoiding math.** Physical chemistry and quantum mechanics are where many students struggle, and the cause is usually weak algebra or calculus, not the science.
- **Skipping computing.** Data analysis and simulation are now part of nearly every role. A little Python goes a long way.
- **Expecting to learn lab skills online.** Instruments, chemical handling and lab safety are learned in supervised teaching labs. This course teaches the knowledge around them, not the hands-on practice.

## Where to check real requirements

Professional societies publish career guides and education standards. For chemistry, the American Chemical Society describes its approved bachelor's programmes at [acs.org](https://www.acs.org/education/policies/acs-approval-program.html). For physics, see the American Physical Society at [aps.org](https://www.aps.org/). For materials, see the Materials Research Society at [mrs.org](https://www.mrs.org/). Checked on 2026-10-23.

## Quick recap

- Physics asks how matter and energy behave; chemistry asks how substances bond and change; materials science links structure to properties.
- All three share a math core: algebra, calculus, differential equations, linear algebra and statistics.
- Real jobs mix the fields; postings ask for the shared foundation plus specific instrument and computing skills.

## Try it

This lesson has no activity. Watch the videos, then take the quiz in the **Do** tab.


Map the core physics, chemistry and math topics that chemists, physicists and materials scientists build on.

Physics, chemistry, and math foundations

Materials science bridges the gap between physics, chemistry and engineering

Crash Course Physics Preview

## Why this matters

Physical scientists rarely trust a single source of evidence. A prediction from a model, a number from an instrument and a result from a simulation each have weaknesses. Discovery happens when they agree, and the most interesting moments come when they do not. Understanding how the three fit together helps you read papers, choose a research group and talk to colleagues in other specialities.

## The three tools

**Theory** gives a model: equations that say what should happen. Newton's laws, the ideal gas law and quantum mechanics are all models.

**Experiment** asks nature directly. You control conditions, change one variable at a time and measure the result, with an honest estimate of uncertainty.

**Simulation** uses a computer to work out what the model predicts in cases too complex to solve by hand. A simulation might follow millions of atoms in a molten metal, or the airflow around a wing.

**Instruments** are how experiments see. Most of the physical world is too small, too fast or too faint for human senses, so scientists measure it indirectly:

| Instrument | What it measures | Typical use |
|---|---|---|
| Spectrometer | How much light is absorbed or emitted at each wavelength | Identifying substances, measuring concentration |
| Mass spectrometer | Mass-to-charge ratio of ions | Identifying molecules and isotopes |
| X-ray diffractometer (XRD) | How X-rays scatter from a crystal | Determining crystal structure |
| Electron microscope (SEM/TEM) | Images using electrons instead of light | Seeing grains, defects and nanoparticles |
| Oscilloscope | Voltage over time | Signals in electronics and detectors |

## How they work together

The usual loop looks like this:

1. A model predicts something measurable.
2. A simulation works out the prediction in detail for a realistic case.
3. An experiment measures it, using an instrument that has been **calibrated** against known standards.
4. The results are compared, including uncertainty.
5. If they disagree beyond the uncertainty, someone checks the instrument, the simulation inputs and the model, in that order.

## Worked example: a new solar-cell material

A team wants a material that absorbs sunlight well.

- **Theory and simulation:** a computational materials scientist uses quantum-mechanical software to predict the material's band gap, the minimum energy a photon needs to be absorbed. The prediction is 1.4 electronvolts (eV).
- **Synthesis:** a chemist makes a thin film of the material.
- **Measurement:** a spectrometer measures how much light the film absorbs at each wavelength. The absorption starts near 890 nm, which corresponds to about 1.4 eV.
- **Comparison:** the measured and predicted values agree within uncertainty. That agreement makes both the model and the measurement more believable.

Now suppose the measurement had said 1.9 eV. The team would check the instrument calibration, whether the film was really the intended compound (perhaps with XRD), and whether the simulation used a method known to underestimate band gaps. Each tool checks the others.

## Calibration and uncertainty

An instrument reading is only as good as its calibration. Labs measure **reference standards** with known values, for example a certified reference material or a known emission line, and correct their readings to match. Every reported value also carries an uncertainty, such as 1.42 plus or minus 0.03 eV. Without it, you cannot tell whether two results agree.

## Simulation is not a shortcut

Simulations depend on their inputs and approximations. A good computational scientist reports which method was used, checks that the answer does not change when the grid or time step is refined (**convergence**), and compares with at least one known experimental result before trusting new predictions. National laboratories, universities and companies all run large simulations, and computational roles are a real career path in their own right.

## Common mistakes

- **Trusting a number because a machine produced it.** Uncalibrated or misused instruments produce precise-looking nonsense.
- **Trusting a simulation because it is detailed.** Detail is not accuracy; check convergence and compare with experiment.
- **Ignoring disagreement.** A mismatch is information. Some major discoveries started as results that did not fit.
- **Forgetting the sample.** Many surprising measurements turn out to be contaminated or mislabelled samples.

## Safety note

Real instruments involve hazards such as X-rays, lasers, high voltage, cryogens and chemicals. Using them requires your institution's or employer's safety training and supervision. This lesson is for understanding only.

## Quick recap

- Theory predicts, simulation works out the details, experiment measures with calibrated instruments.
- Results are compared with their uncertainties; agreement builds confidence, disagreement triggers checks.
- Simulation needs convergence checks and validation against experiment.

## Try it

This lesson has no activity. Watch the videos, then take the quiz in the **Do** tab.


Describe how experiment, simulation and scientific instruments work together to test an idea.

Experiments, simulation, and instrumentation

Spectroscopy, Explained

Computer Simulation: Exploring nature with a computer

## Why this matters

In physical science, an answer that is off by a factor of a thousand often looks just as convincing as the right one. A wavelength typed in nanometres instead of metres, or grams instead of kilograms, silently wrecks a calculation. Two habits catch most of these errors before they reach a lab notebook or a paper: **carry units through every step**, and **estimate the answer before you calculate it**.

## The SI system and its constants

Science uses the International System of Units (SI). It has seven base units: the metre (m), kilogram (kg), second (s), ampere (A), kelvin (K), mole (mol) and candela (cd). Every other unit is built from them. A newton is kg·m/s², a joule is a newton-metre, and a watt is a joule per second.

Since 2019, the base units are defined by fixing the exact values of physical constants. For example:

| Constant | Symbol | Exact value |
|---|---|---|
| Speed of light in vacuum | c | 299,792,458 m/s |
| Planck constant | h | 6.62607015 × 10⁻³⁴ J·s |
| Elementary charge | e | 1.602176634 × 10⁻¹⁹ C |
| Boltzmann constant | k | 1.380649 × 10⁻²³ J/K |
| Avogadro constant | N_A | 6.02214076 × 10²³ mol⁻¹ |

Look values up from the official sources instead of from memory: the BIPM SI pages at [bipm.org](https://www.bipm.org/en/measurement-units) and the NIST constants database at [physics.nist.gov](https://physics.nist.gov/cuu/Constants/). Checked on 2026-10-23.

## Carry units through the calculation

Treat units like algebra symbols. They multiply, divide and cancel. If the units of your final answer are wrong, the formula or a conversion is wrong.

**Worked example: the energy of a green laser photon.** A photon's energy is E = hc / λ, where λ is the wavelength. A green laser pointer emits at 532 nm.

1. Convert the wavelength to SI: 532 nm = 532 × 10⁻⁹ m = 5.32 × 10⁻⁷ m.
2. Multiply the constants: hc = (6.626 × 10⁻³⁴ J·s)(2.998 × 10⁸ m/s) = 1.986 × 10⁻²⁵ J·m. The seconds cancel.
3. Divide: E = 1.986 × 10⁻²⁵ J·m / 5.32 × 10⁻⁷ m = 3.73 × 10⁻¹⁹ J. The metres cancel, leaving joules, which is an energy. Good.
4. Convert to electronvolts, the unit used for photons and electrons: 1 eV = 1.602 × 10⁻¹⁹ J, so E = 3.73 / 1.602 = 2.33 eV.

If you had left λ in nanometres, you would get an energy a billion times too small, still with a plausible-looking number of digits.

## Estimate first

An **order-of-magnitude estimate** gets the answer to within a factor of about ten using rounded numbers. It takes seconds and tells you whether a detailed result is believable.

For photons there is a famous shortcut: hc is about 1240 eV·nm. So E (in eV) is roughly 1240 divided by the wavelength in nm. For 532 nm: 1240 / 532 ≈ 2.3 eV. That matches the detailed calculation. Since visible light runs from about 380 to 750 nm, visible photons carry roughly 1.7 to 3.3 eV, so any visible-light answer outside about 1 to 4 eV is almost certainly a mistake.

**Another estimate: how many atoms are in a 1 cm³ copper cube?** Copper's density is about 9 g/cm³ and its molar mass about 64 g/mol. So 9 g is about 9/64 ≈ 0.14 mol, and 0.14 × 6 × 10²³ ≈ 8 × 10²² atoms. Roughly 10²³ atoms, which is the right scale for a small piece of anything solid.

## Significant figures and sensible precision

Report as many digits as your inputs justify. If the wavelength is known to three figures (532 nm), report 2.33 eV, not 2.330496 eV. Exact constants do not limit your precision; measured inputs do.

## Common mistakes

- **Mixing prefixes.** nm, µm and mm differ by factors of 1000. Convert to base SI units before multiplying.
- **Dropping units halfway.** Write them on every line until the end.
- **Using a remembered constant with the wrong exponent.** Look it up, and check the estimate.
- **Trusting a calculator over an estimate.** When they disagree by more than a factor of ten, recheck the calculation.

## Quick recap

- Seven SI base units; since 2019 they are defined by exact constants such as c, h and e.
- Units multiply and cancel like algebra; wrong final units mean a wrong calculation.
- Estimate first; for photons, E in eV ≈ 1240 / λ in nm.

## Try it

Open the **Do** tab and finish a short Python function that turns a wavelength into a photon energy, then compare it with your 1240 / λ estimate.


Check a calculated result with units and a quick order-of-magnitude estimate.

Units, constants, and estimation

Scientific Notation and Dimensional Analysis

A clever way to estimate enormous numbers - Michael Mitchell

The physics, chemistry and math these careers build on, how experiment, simulation and instruments work together, and checking results with units and estimates.

Understanding the Physical World

## Why this matters

In software or data work, many people get hired on skills and a portfolio alone. Physical science is different. The job title "physicist" usually means a PhD, and research-leading chemists and materials scientists usually have a master's or doctorate. That does not mean a bachelor's is a dead end, far from it, but you should know what each level typically leads to before you plan years of study.

## What each degree level usually qualifies you for

| Degree | Typical length (US) | Typical roles |
|---|---|---|
| Bachelor's (BS) | About 4 years | Lab technician, quality control chemist, research associate, process or production chemist, materials test technician, instrument specialist, technical sales, science teaching (with a teaching licence), entry to engineering or data roles |
| Master's (MS) | 1 to 2 years beyond a BS | Scientist roles in industry, analytical method development, materials engineer, senior research associate, project lead on defined problems |
| Doctorate (PhD) | Often 5 to 6 years beyond a BS in the US | Independent researcher, principal scientist, national-lab staff scientist, faculty, R&D group leader |

These are patterns, not rules. Some BS chemists lead teams after years of experience, and some PhDs work in roles that a BS could do.

## Why research roles expect a PhD

A PhD trains you to do something nobody has done before: choose an open question, design a way to answer it, recover when it fails, and defend the result to experts. That takes years of supervised practice in one area. Employers hiring someone to set a research direction want proof that you can do this, and the dissertation is that proof.

In the US, most physical science PhD students are **funded**: tuition is usually waived and students receive a stipend for teaching or research assistant work. Funding terms vary by institution and field, so check each programme. Many US students enter a PhD directly after a bachelor's, without a separate master's.

## What the bachelor's needs to include

Whatever level you aim for, the bachelor's is the foundation and the hands-on part matters:

- **Chemistry:** many employers and graduate programmes look for a degree approved by the American Chemical Society, which sets minimum lab hours and course coverage. See [acs.org](https://www.acs.org/education/policies/acs-approval-program.html). Checked on 2026-10-23.
- **Physics:** upper-level labs, computing and, ideally, research experience. See career resources from the American Physical Society at [aps.org](https://www.aps.org/). Checked on 2026-10-23.
- **Materials:** a materials science and engineering degree, or chemistry, physics or engineering with time on characterisation instruments. See [mrs.org](https://www.mrs.org/). Checked on 2026-10-23.

Lab courses are where you learn instruments and safe chemical handling under supervision. No online course, including this one, replaces them.

## Worked example: comparing three paths

Maya enjoys chemistry lab work and wants a stable job soon after graduating. A BS in chemistry leads directly to quality control or analytical lab roles. She can add an employer-funded MS later.

Jordan wants to design new battery materials and lead projects. A BS followed by an MS can lead to industry scientist roles; a PhD opens principal scientist and national-lab paths.

Sam loves theoretical physics and wants to run a research group. That path is a PhD, then usually one or more postdoctoral positions, then faculty or staff scientist applications. Sam should know that permanent academic research jobs are competitive, and many PhD physicists build successful careers in industry, data science, finance or national labs instead.

## Questions to ask before committing

1. What job do you want ten years from now, and what degree do people in that job have? Look at real profiles and postings.
2. Is the graduate programme funded, and what is the typical time to degree?
3. Do you like research when it fails for months? Try undergraduate research before deciding.
4. Would an employer pay for a part-time master's later?

The US Bureau of Labor Statistics Occupational Outlook Handbook summarises typical education, pay and outlook for chemists and materials scientists and for physicists at [bls.gov/ooh](https://www.bls.gov/ooh/). Checked on 2026-10-23.

## Common mistakes

- **Starting a PhD without research experience.** Undergraduate research is the best test of whether you will enjoy it.
- **Assuming a BS is not enough for any science job.** Many technical roles hire bachelor's graduates.
- **Paying full price for a master's without a plan.** Check funding and what the degree actually unlocks.
- **Ignoring the lab component.** A degree without hands-on lab courses limits options for chemistry and materials work.

## Quick recap

- BS: technical and lab roles; MS: industry scientist roles; PhD: independent research leadership.
- US physical science PhDs are often funded, and many start straight after a BS.
- Hands-on, supervised lab coursework is essential, and an ACS-approved degree helps in chemistry.

## Try it

This lesson has no activity. Watch the videos, then take the quiz in the **Do** tab.


Compare what bachelor's, master's and PhD holders typically do in physical science and materials careers.

Why advanced degrees matter here

Should you do a PhD? (PhD in physics at Cambridge)

The REAL difference between a PhD and a Masters

Write the poster title as a finding or a clear question, in 15 words or fewer.

Write the research question and why it matters in two sentences a first-year student would understand.

Summarise the method in 3 to 5 bullet points, including what was measured and in which units.

Choose the single most important result and sketch the one figure that shows it, with labelled axes, units and error bars or uncertainty.

Write a one-sentence take-home message that someone could read from two metres away.

Sketch the layout: title across the top, then question, method, result figure (largest), conclusion and references, reading left to right.

Cut every text block to no more than about 50 words, and count the total. Aim for under 500 words.

Practise a 60-second spoken summary out loud, then time it.

## Why this matters

Grades show you can learn science. Research evidence shows you can **do** science: ask a question, carry out a method, handle messy results and explain them. Graduate programmes, national labs and industry R&D teams all look for it. For most undergraduates, that evidence starts with a research project and a poster, and sometimes grows into a co-authored paper.

## Forms of research evidence

From most accessible to most demanding:

1. **Course projects and lab reports** written to a high standard.
2. **Undergraduate research** in a faculty member's group during the term, often for course credit or pay.
3. **Summer research programmes**, such as US National Science Foundation REU sites ([nsf.gov](https://www.nsf.gov/funding/initiatives/reu)) and DOE national-lab internships ([science.osti.gov](https://science.osti.gov/wdts/suli)). Checked on 2026-10-23.
4. **Posters and talks** at departmental, regional or national meetings.
5. **Co-authored publications**, which usually take longer than a single summer.

## How to get into undergraduate research

- Read your department's faculty research pages and pick two or three groups whose work you can describe in a sentence.
- Email each faculty member briefly: who you are, which of their projects interests you and why, your relevant courses and skills (including any Python), and your availability. Attach a one-page CV.
- Ask your instructors and the department's undergraduate advisor; many positions are filled by word of mouth.
- Expect to start with simple tasks. Reliability earns you more responsibility.

Before you work in any research lab you will complete the institution's safety training and work under supervision. That is a requirement, not a formality.

## What a research poster is

A poster is a large single page, often about 90 × 120 cm, that summarises a project. At a poster session you stand beside it for an hour or two and talk with people who walk up. Most visitors give a poster a few seconds before deciding whether to stop, so the design job is to make the main finding obvious from a distance.

A typical structure:

| Section | What goes in it | Length |
|---|---|---|
| Title | The finding or question | One line |
| Introduction | Why the question matters | 2 to 3 sentences |
| Methods | What you did, briefly, often with a diagram | 3 to 5 bullets |
| Results | One to three figures with clear captions | Most of the space |
| Conclusion | The take-home message and next steps | 2 to 3 bullets |
| References and acknowledgements | Key sources, funding, mentors | Small text |

## Worked example: from project to poster

A student measured how the electrical resistance of a thin metal film changed with temperature in a supervised teaching lab.

- **Weak title:** "Investigation of Temperature-Dependent Electrical Properties of Thin Films."
- **Strong title:** "Resistance of 200 nm copper films rises 0.38% per kelvin, close to bulk copper."
- **Method bullets:** film deposited by the lab manager; four-point probe measurement; 20 to 100 °C in 10 °C steps; three films.
- **Main figure:** resistance against temperature with error bars and a fitted straight line, axes labelled with units.
- **Take-home message:** "At 200 nm thickness, copper films keep nearly bulk-like temperature behaviour."

The strong version tells a visitor the result before they read anything else.

## From poster to publication

A paper needs more data, a careful comparison with previous work and peer review. Undergraduates usually contribute as one of several co-authors. Ask your mentor early what would be needed for the work to become publishable, and keep careful records (Module 3 covers lab notebooks) so your contribution can be used.

## Common mistakes

- **Too much text.** If a visitor has to read paragraphs, they will walk on.
- **Figures without units or uncertainty.** Every axis needs a label and a unit.
- **No clear message.** Write the one-sentence takeaway first, then design around it.
- **Waiting until senior year.** Research takes time to arrange; start asking in your first or second year.
- **Overclaiming.** Report what your data shows, including limitations.

## Quick recap

- Research evidence ranges from strong lab reports to posters and co-authored papers.
- Find research by reading faculty pages, sending short specific emails and applying to summer programmes.
- A good poster leads with the finding, keeps text short and lets one clear figure carry the result.

## Try it

Open the **Do** tab and plan a poster from an open-access study or a safe pendulum measurement at home.


Plan an undergraduate research poster that shows a question, method and result clearly.

Evidence: research, posters, and publications

What makes a great research poster? [Good and Bad Examples]

Making a better research poster

Pick one career to focus on (chemist, physicist or materials scientist) and write two job titles that fit your current or planned degree level.

Search a general job site and one company careers page in an industry from the lesson (for example pharmaceuticals, semiconductors, batteries or coatings). Save two postings.

Open the DOE national laboratories list (energy.gov/national-laboratories), choose one lab, and save one posting or internship from its careers page.

If you are a US student, read the eligibility and deadline for DOE SULI or NIST SURF and note them.

For each saved posting, copy the required qualifications into a table with three columns: requirement, do I have it (yes/partly/no), how I could get it.

Circle the requirement that appears most often across postings. That is your next skill to build.

Set a calendar reminder for the next internship or programme deadline you found.

## Why this matters

Most physical scientists do not work in universities. They work in companies that make things and in government laboratories that run large facilities and long-term research. Knowing where these jobs are, what they are called and how they are posted saves you months of searching in the wrong places.

## Where physical scientists work

**Industry** employs the largest share of chemists and materials scientists. Common sectors include:

- Pharmaceuticals and biotechnology (analytical chemistry, formulation, quality control)
- Semiconductors and electronics (process engineering, thin films, metrology)
- Energy storage and renewables (batteries, solar cells, catalysts)
- Chemicals, plastics, coatings and adhesives (product development, process chemistry)
- Aerospace, automotive and metals (materials testing, failure analysis)
- Environmental and contract testing labs (regulated analysis of water, air and products)
- Optics, lasers, medical devices and instruments (physicists in R&D and applications)

**Government laboratories** include the US Department of Energy national laboratories (such as Argonne, Oak Ridge, Lawrence Livermore and Sandia), the National Institute of Standards and Technology (NIST), NASA centres and defence labs. They operate facilities such as synchrotrons, neutron sources and supercomputers that no single university could afford. The DOE keeps a list of its labs at [energy.gov](https://www.energy.gov/national-laboratories). Checked on 2026-10-23.

**Academia** includes faculty roles, but also staff scientists, lab managers and instrument facility managers, who are often BS or MS holders.

## Job titles to search for

Titles vary between employers, so search several:

| Level | Titles to try |
|---|---|
| BS | Research associate, laboratory technician, QC chemist, analytical chemist I, process technician, materials test technician |
| MS | Scientist I, materials engineer, process engineer, method development chemist, applications scientist |
| PhD | Senior scientist, research scientist, staff scientist, postdoctoral researcher |

## Internships and early-career programmes

Internships are the most common route from student to employee. In the US, examples include:

- **DOE Science Undergraduate Laboratory Internships (SULI)**, paid research internships at national labs: [science.osti.gov](https://science.osti.gov/wdts/suli).
- **NIST Summer Undergraduate Research Fellowship (SURF)**: [nist.gov/surf](https://www.nist.gov/surf).
- **NSF Research Experiences for Undergraduates (REU)** sites at universities: [nsf.gov](https://www.nsf.gov/funding/initiatives/reu).
- Company internship and co-op programmes, often posted in the autumn for the following summer.

Federal civilian jobs are posted at [usajobs.gov](https://www.usajobs.gov/). Eligibility (for example citizenship requirements and enrolment status), pay and deadlines change, so read each programme's current rules. Checked on 2026-10-23.

## Worked example: matching a posting

A posting for "Analytical Chemist I" at a pharmaceutical contract lab asks for:

1. BS in chemistry or a related field.
2. Experience with HPLC (high-performance liquid chromatography).
3. Working knowledge of GMP (good manufacturing practice) documentation.
4. Attention to detail and clear written records.

A third-year chemistry student might map it like this: (1) yes, in progress; (2) partly, used HPLC in an instrumental analysis lab course; (3) no, but GMP training is often provided on the job, and reading the basics shows interest; (4) yes, and the lab notebook skills in Module 3 are evidence. The gap list says: get more instrument time, perhaps through undergraduate research, and learn the vocabulary of regulated labs.

## What employers look for beyond the degree

- **Hands-on instrument experience** from lab courses, research or internships.
- **Data skills:** spreadsheets and increasingly Python for analysis.
- **Documentation:** accurate notebooks and reports, especially in regulated industries.
- **Safety culture:** every lab employer trains new staff on its own procedures, and expects you to follow them.
- **Communication and teamwork** across chemists, engineers and technicians.

## Common mistakes

- **Searching only for "physicist" or "chemist".** Many relevant jobs have engineer, scientist or associate titles.
- **Missing deadlines.** Summer programmes often close months ahead.
- **Applying without tailoring.** Match your CV to the posting's top requirements.
- **Ignoring contract and testing labs.** They hire many entry-level scientists and teach regulated practice.

## Quick recap

- Industry employs most physical scientists; national labs and NIST run large facilities and long-term research.
- Search several job titles, and use internships (SULI, SURF, REU, company co-ops) as entry points.
- Map each posting's requirements to your skills to find your next step.

## Try it

Open the **Do** tab and build a small target list of real openings with a gap table.


Find industry and national-laboratory openings for chemists, physicists and materials scientists, and match them to your skills.

Industry and national-lab roles

The SULI (Science Undergraduate Laboratory Internship) Experience

What each degree level qualifies you for, how to show research evidence, and where industry and national-lab roles are posted.

The Research Path

First pass (10 minutes): read the title, abstract, figure captions and conclusion only. Write one sentence saying what you think the paper found.

Write the paper's research question in your own words, as a question ending in a question mark.

Second pass: read the introduction and note the gap the authors say they are filling, in one sentence.

Read the methods and list what was measured or simulated, with which instrument or method, and on how many samples or cases.

Pick the most important figure. Write what is on each axis (with units) and what the figure shows.

Write the main result in one sentence, including a number and its uncertainty if the paper gives one.

List one limitation the authors mention and one question you still have.

Compare your first-pass sentence with your final summary and note what changed.

## Why this matters

Research papers are how physical scientists share results. In a research group you might be asked to read several a week; in industry you read them to choose a method or check a competitor's claim. Papers are dense and written for experts, so reading one front to back on the first try is slow and discouraging. A strategy makes it manageable.

## How a paper is organised

Most experimental and computational papers follow a structure often called **IMRaD**:

| Section | Question it answers |
|---|---|
| Title and abstract | What was found, in a paragraph? |
| Introduction | Why does this matter, and what gap does it fill? |
| Methods (or Experimental) | What exactly was done, so others could repeat it? |
| Results | What was measured or calculated? |
| Discussion and conclusion | What does it mean, and what are the limits? |
| References and supplementary information | Where does it build on others, and where are the extra details? |

Physics papers sometimes merge sections, and letters are shorter, but the same questions are always answered somewhere.

## The three-pass method

A widely used approach, described by computer scientist S. Keshav in "How to Read a Paper", reads in three passes, each deeper than the last.

**Pass 1: the survey (5 to 10 minutes).** Read the title, abstract, section headings, figures and captions, and the conclusion. Skip the equations. Afterwards you should be able to say what kind of paper it is, what question it answers and what it claims. Often this is enough to decide whether to go further.

**Pass 2: the content (about an hour).** Read the whole paper, but skip proofs and fine details. Study each figure carefully: what are the axes and units, what are the error bars, does the figure actually support the claim in the text? Mark terms you do not know and references you might need.

**Pass 3: the deep read (several hours).** Rarely needed as a beginner. Here you try to reproduce the reasoning, check assumptions and think about how you would do the work yourself. This is what reviewers and researchers who build directly on a paper do.

## Worked example: summarising a materials paper

Suppose you read a paper titled "Doping increases the ionic conductivity of a solid electrolyte for lithium batteries". A good summary looks like this:

- **Question:** Does adding a small amount of element X to the solid electrolyte increase how fast lithium ions move through it?
- **Gap:** Solid electrolytes are safer than liquids but conduct ions too slowly; previous doping attempts gave small improvements.
- **Method:** Samples with 0, 1, 2 and 5% doping were made; conductivity was measured by impedance spectroscopy from 25 to 100 °C; crystal structure was checked by X-ray diffraction; three samples per composition.
- **Key figure:** conductivity (S/cm, logarithmic axis) against temperature for each composition.
- **Main result:** 2% doping gave about ten times the conductivity of the undoped sample at room temperature, with sample-to-sample variation of about 20%.
- **Limitation:** long-term stability in a working battery was not tested.

That summary fits on an index card and is what your supervisor will usually want.

## Reading figures critically

Figures carry most of a paper's evidence. For each one, ask:

1. What is plotted, in what units, and on what scale (linear or logarithmic)?
2. How many samples or runs does each point represent?
3. Are there error bars, and what do they represent?
4. Does the text claim more than the figure shows?

## Peer review and preprints

Journal papers have been through **peer review**: experts checked them before publication. That reduces errors but does not guarantee correctness. **Preprints**, such as those on arXiv, have not necessarily been peer reviewed. They are valuable for speed, but read them with extra care. The next lesson covers finding both.

## Common mistakes

- **Reading every word in order on the first pass.** Start with the abstract, figures and conclusion.
- **Getting stuck on one equation.** Mark it and move on; come back if you need it.
- **Trusting the abstract alone.** Abstracts present the best version of the result; check the figures.
- **Not writing anything down.** A short structured summary is what makes the reading useful later.

## Quick recap

- Papers follow a predictable structure: abstract, introduction, methods, results, discussion.
- Read in passes: survey, content, then a deep read only when needed.
- Summarise as question, gap, method, key figure, result with a number, and limitation.

## Try it

Open the **Do** tab and summarise an open-access paper using the three-pass method.


Summarise a research paper's question, method and main result using a three-pass reading strategy.

Reading a paper

Tutorial: How to Read and Comprehend Scientific Research Articles

How to Read a Scientific Paper

Write your topic as one sentence, then list 3 to 5 search terms, including at least one synonym.

On Google Scholar, search one exact phrase in quotation marks and note how many results appear.

Narrow the search to the last five years with the date filter and note how the results change.

Find a review article (try adding the word review) and save its title and year.

Open the 'Cited by' list of an older, highly cited paper and pick one recent paper that cites it.

On arXiv, search the same topic, note which category the results come from (for example cond-mat or physics), and open one preprint's abstract page.

Check whether your arXiv preprint has a journal reference (published version) listed on its abstract page.

Record five papers in a simple table: authors, year, title, source (journal or arXiv), link, one-line note.

## Why this matters

Before starting any project, a scientist asks: what is already known? Repeating work that was published ten years ago wastes months. Finding the right five papers, especially a recent review, is often the fastest way into a new topic. Literature searching is a skill, and two free tools cover most needs in physical science: **Google Scholar** and **arXiv**.

## Google Scholar

[Google Scholar](https://scholar.google.com/) indexes journal articles, preprints, theses, books and conference papers across all fields. Useful features:

- **Exact phrases:** put quotation marks around a phrase, such as "solid electrolyte", to require those words together.
- **Exclude words:** a minus sign removes results, for example `graphene -oxide`.
- **Author search:** `author:"A Smith"` limits results to an author.
- **Title-only search:** start with `allintitle:` to require every term in the title.
- **Date filter:** the left-hand menu limits results to recent years.
- **Cited by:** shows newer papers that cite a result, which is how you move forward in time from a classic paper.
- **Related articles:** finds papers similar to one you like.
- **Alerts:** emails you when new papers match a search.
- **Cite:** produces a formatted reference you can copy.

Results are ranked partly by citations, so older papers float to the top. Use the date filter to find recent work.

## arXiv

[arXiv](https://arxiv.org/) is a free preprint server run by Cornell University. Physicists, mathematicians and many materials scientists post papers there, often before or at the same time as journal submission. It is organised by category; for example `cond-mat` (condensed matter, which includes materials), `physics.chem-ph` (chemical physics), `quant-ph` (quantum physics) and `astro-ph` (astrophysics).

Things to know:

- arXiv papers are moderated for basic suitability but are **not necessarily peer reviewed**.
- Each paper's abstract page shows its versions (v1, v2...) and, once published, often a **journal reference** or DOI.
- Daily listings of new submissions per category are a common way researchers keep up.

Chemistry has its own preprint server, ChemRxiv, which works in a similar way. Checked on 2026-10-23.

## Getting the full text

Many journal articles are behind paywalls. Legal routes include: your university library, which subscribes to many journals; the arXiv or author-posted version; open-access journals; and tools like [Unpaywall](https://www.unpaywall.org/), which find legal free versions. You can also email the corresponding author; most are happy to share.

## Worked example: starting a search

Topic: "How does temperature affect sodium-ion battery performance?"

1. **Terms:** "sodium-ion battery", temperature, "low temperature", performance, review.
2. **Search:** `"sodium-ion battery" "low temperature" review` on Google Scholar, filtered to the last five years. A recent review appears near the top.
3. **Read the review first.** It summarises the field and cites the key papers, so its reference list becomes your reading list.
4. **Go forward in time:** open "Cited by" on the review to find papers published after it.
5. **Check arXiv:** search `sodium-ion low temperature` and look in the `cond-mat` and `physics` results for the newest preprints.
6. **Record:** keep a table or use a free reference manager (such as Zotero) with authors, year, title, source and a one-line note.

## Judging what you find

- Prefer recent reviews for orientation and original research papers for specific results.
- Check whether a preprint has since been published, and whether results have been reproduced by other groups.
- Watch for predatory journals: unfamiliar journals that promise very fast publication for a fee. Ask a librarian or mentor if unsure.
- Citation counts show attention, not correctness.

## Common mistakes

- **Searching only one term.** Fields use different words for the same idea; try synonyms.
- **Reading only the most cited papers.** They are often old; filter by date.
- **Skipping review articles.** A good review can save weeks.
- **Losing track of sources.** Record every useful paper as you find it.
- **Treating preprints as settled.** Check for a published version and later work.

## Quick recap

- Google Scholar: quotation marks, minus, author and title operators, date filter, Cited by, alerts.
- arXiv: free preprints by category; not necessarily peer reviewed; check for a journal reference.
- Start with a recent review, move forward with Cited by, and record every source.

## Try it

Open the **Do** tab and run a small literature search with Google Scholar and arXiv.


Search Google Scholar and arXiv effectively to find the key papers on a topic.

Finding literature

Google Scholar Tutorial: How to Use Google Scholar for Academic Research

What are preprints?

In a paper notebook or a document, write today's date, a title and a one-sentence objective for the measurement.

List every item you will use, with identifying details (for example ruler brand and smallest division, paper type and pack size).

Write the procedure as numbered steps, including how many repeats you will do and exactly what you record each time.

Do the measurement yourself and record raw readings in a table as you go, with units. Do not erase or overwrite; cross out mistakes with a single line.

Note any deviation from your written procedure and anything unexpected.

Calculate the result (for example stack thickness divided by number of sheets) and write it with an uncertainty estimate.

Give only your written procedure to a friend or family member and ask them to repeat the measurement without help.

Compare their result with yours. Revise any step they found unclear, and record what you changed and why.

## Why this matters

A result that cannot be repeated is not useful to anyone. In research, a colleague or a future version of you will need to know exactly what was done. In industry, especially in regulated labs such as pharmaceutical quality control, the notebook or electronic record is a legal document that inspectors can review. Good record-keeping is one of the first things a research supervisor or lab manager will judge you on.

## Reproducibility, briefly

- **Repeatability:** the same person, method and equipment get the same result again.
- **Reproducibility:** a different person or lab, following your description, gets a consistent result.

Surveys of scientists over the past decade have found that many have tried and failed to reproduce someone else's experiment. Causes include unclear methods, unrecorded details (a different batch of a reagent, a different room temperature), selective reporting and simple errors. Clear notebooks address many of these.

## What goes in a lab notebook entry

Institutions and employers have their own rules, which you must follow. Common elements:

| Element | Example |
|---|---|
| Date and your name | 2026-10-23, J. Rivera |
| Title and objective | "Calibrate the balance; check against a 100 g reference mass" |
| Materials and equipment | Instrument model and ID, reagent name, supplier, lot number, concentration |
| Procedure | Numbered steps, or a reference to a written standard procedure plus any changes |
| Raw data | Readings with units, written directly in the notebook or saved to a named file |
| Observations | Colour changes, unusual noises, interruptions, room conditions |
| Deviations | Anything that differed from the plan, and why |
| Results and analysis | Calculations, with the file name and version of any script used |
| Conclusion and next steps | What it means and what to do next |

For paper notebooks, common rules are: use a bound notebook with numbered pages, write in ink, never tear out pages, cross out errors with a single line so they stay readable, and date and sign each page. Many labs now use **electronic lab notebooks (ELNs)**, which add timestamps, audit trails and links to data files. The principles are the same.

## Worked example: improving a procedure

Weak entry:

> Made the solution and measured it. Absorbance was 0.42.

Improved entry:

> 2026-10-23. Objective: check absorbance of a standard solution at 520 nm. Solution prepared by the lab manager from stock lot 4471 (see SOP-12, step 3), diluted 1:10 with deionised water in a 10 mL volumetric flask. Spectrometer ID SP-02, warmed up 20 min, blank: deionised water in the same cuvette. Three readings: 0.421, 0.418, 0.423. Mean 0.421, range 0.005. Room temperature 21 °C. Deviation: used cuvette B because cuvette A was scratched.

The second version lets someone else repeat the measurement and explains a result that might otherwise look odd later.

Note that this is a description of an entry only. Preparing solutions and using instruments in a real lab requires your institution's or employer's safety training, the safety data sheets for each chemical, and supervision.

## Data and code count too

Modern physical science produces data files and analysis scripts. For reproducibility:

- Keep **raw data unchanged**; save processed data as new files.
- Name files consistently, for example `2026-10-23_SP02_absorbance_run1.csv`.
- Record which script and version produced each result, and keep scripts under version control (such as Git).
- Write a short README describing where things are.

## Common mistakes

- **Writing it up later.** Memory fails within hours; record as you go.
- **Recording only the final number.** Keep raw readings and every repeat.
- **Leaving out the boring details.** Lot numbers, instrument IDs and room conditions are often what explains a strange result.
- **Hiding mistakes.** Crossed-out errors and failed runs are part of an honest record.
- **Ignoring local rules.** Your lab's notebook policy and safety procedures come first.

## Quick recap

- Reproducibility means someone else can follow your record and get a consistent result.
- A good entry has date, objective, materials with IDs, procedure, raw data, observations, deviations, analysis and conclusion.
- Keep raw data unchanged and link results to the scripts that made them.

## Try it

Open the **Do** tab, write a procedure for a safe home measurement, and test it by having someone else follow it.


Write a procedure and notebook entry clear enough that someone else can reproduce your result.

Lab notebooks and reproducibility

Keeping a Laboratory Notebook

Ten Tips For Keeping a Better Lab Notebook

Read a paper efficiently, find literature on Google Scholar and arXiv, and keep a lab notebook someone else could follow.

Foundations for Physical Science & Materials Careers

About this course

Course content

Understanding the Physical World

The Research Path

Reading Science

Where this course leads

Next course on the path

Careers that use it