Article

Chemistry and materials science R&D: get paid for your records

By TrustPast

Updated November 7, 2026

This page is for the owner or the R&D director of a chemistry or materials science company. You develop coatings, polymers, adhesives, catalysts, battery materials, specialty chemicals or advanced ceramics. Or you run contract R&D and analytical services for companies that do. You have chemists, technicians, an analytical lab, a pilot line and a safety programme, and the oldest notebooks are older than some of your staff.

Most R&D owners think of their value as the finished formulations and the patents. Those are the end of the story. What they don’t count is the middle: the notebook pages where a reaction failed and the chemist wrote down why, the analytical request that came back with a surprise, the failure analysis on a customer’s returned part, the stage-gate review where a project was killed. A buyer pays to license records like these to train AI models, and the middle is where the reasoning lives.

We wrote the plain version of this in what data buyers want from a trade business. It talks about estimates and change orders, but the point is the same in a lab: the record of how a problem was worked through is worth more than the clean answer. This page goes through it for chemistry and materials R&D, with micro1 as the buyer.

The records a chemistry R&D group keeps

These are our examples, not a buyer’s list. A working R&D group produces them as part of the job, year after year.

The lab notebook. Paper or electronic, the notebook is the primary record. Aim, procedure, observations, result, conclusion. The useful entries are the ones that say “gelled at 40 minutes, suspect moisture in the second lot of monomer, repeat with dried solvent.” A group of twenty chemists writes thousands of entries like that a year.

The formulation trial series. A coating that has to pass a salt spray test goes through dozens of versions. Each version changes one or two components. The trial log says what changed, what the panel looked like after 500 hours, and what the chemist tried next. The series is a search, written down step by step.

The analytical request. A chemist sends a sample to the analytical lab with a request: run a DSC, check the molecular weight, look for a contaminant. The request form is a work order. The result comes back with the analyst’s note, and sometimes the note says the sample isn’t what the chemist thought it was. Our page on job files and work orders explains why the request-and-result pair is one of the most useful records a company keeps.

The failure analysis. A customer sends back a part that cracked, delaminated or discoloured. The report walks through the investigation: visual inspection, cross-section, spectroscopy, the hypothesis, the confirmation, the root cause. It is a diagnosis in the strictest sense.

The scale-up file. A recipe that works in a flask doesn’t always work in a reactor. The pilot batch records show what changed between the bench and the line: mixing times, temperatures, addition rates, the exotherm that nobody expected.

The project record and the stage gates. Each R&D project has a charter, milestones and reviews. At each gate, the team decides to continue, change course or stop. The minutes say why. Our page on project history covers how the plan, the changes and the post-mortem show the way a company handled the gap between plan and result.

The equipment work orders. The instrument that drifted out of calibration, the reactor seal that failed, the fume hood that didn’t pass its face velocity test. Each has a work order with the fault, the fix and the date.

The safety programme. Management of change forms for new processes, hazard reviews before a new chemistry runs, the incident report after a near miss. Most labs that handle hazardous chemicals keep a written programme for this, and its revision history shows what the lab learned.

Together those records answer the questions a buyer cares about. How an idea became a trial series and then a product, or a dead end. How a failure was traced to a cause. How a bench recipe was made to run on a line. The how is in the notes, not in the final spec sheet.

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What counts, in the buyer’s own words

micro1 states its line on its data partnerships page: “We’re looking for established companies with 30+ full-time employees, mature business operations, and substantial historical operational data.” It names the records: “This can include internal communications, SOPs, project histories, CRM records, support tickets, and other business documentation.” An R&D group’s project histories and SOPs are named outright.

micro1’s pages don’t name chemistry or materials science as a category. Its data partnerships page says “Operational data from every industry can contribute”, and its referral page lists “All industries” under company requirements. So we apply what its pages say.

The data partnerships page describes what it looks for in these words: “We are looking for data that reflects how work is actually performed within an organization. This may include standard operating procedures (SOPs), process documentation, internal knowledge bases, workflows, templates, operational frameworks, and other business process artifacts.” An analytical request form is a template. A management of change procedure is a workflow. A failure analysis report is process documentation with every step left in.

One of micro1’s industry examples fits a materials company’s plant side: “Operations & logistics”, described as “Operational SOPs, logistics processes, fulfillment workflows, inventory management, and internal operations.” Raw material inventory, sample tracking and pilot line scheduling are all in that list.

On value, micro1 writes: “The most valuable datasets capture real operational expertise, decision-making processes, and repeatable workflows”. A stage-gate review is a decision-making process. A trial series is operational expertise, applied one variable at a time.

micro1 also says “Data should be primarily in English.” A group with a sister lab abroad, writing notebooks in another language, should count the English share first.

What is never included

Customers’ names and contacts, their payment details, your staff’s personal information and anything about an individual’s health are not what a buyer pays for. Our page on what is never included shows where those details hide in a company’s files.

micro1 doesn’t publish a list of records it excludes. As our own advice, an R&D company has three things to settle before anything moves.

The client’s work. In contract R&D, the client usually owns the results and often the samples, the methods and the reports. A joint development agreement may split ownership in ways nobody remembers. Only the contracts say which is which, and anything a client owns stays out. Our page on client-owned work and NDAs lists the clauses to look for.

Restricted chemistry. Some chemistry may be restricted; ask counsel. As our own advice, keep those files out until counsel has said where the line sits.

Records about people. OSHA’s laboratory standard, 29 CFR 1910.1450, requires a “Chemical Hygiene Plan”, which it defines as “a written program developed and implemented by the employer which sets forth procedures, equipment, personal protective equipment and work practices” that protect employees from the chemicals in that workplace. The plan itself is a procedure. The records around it can be personal. OSHA’s rule on access to records, 29 CFR 1910.1020, says “Each employee exposure record shall be preserved and maintained for at least thirty (30) years”, with listed exceptions. It also says “The medical record for each employee shall be preserved and maintained for at least the duration of employment plus thirty (30) years”, again with exceptions. Exposure and medical records are about people, and they stay out. Whether any safety record may be licensed at all is a question for counsel. Ask counsel before any of it moves.

How de-identification works

You don’t redact the notebooks yourself. micro1’s page asks “Does my company need to anonymize its data before transferring it?” and answers: “No, micro1 has processes for de-identifying and transforming sensitive information.”

micro1’s estimate page sets out what is confirmed “Before any participation”. Under “Data segregation”: “Your data is kept separate from other companies’ data, with access restricted to authorized personnel.” Under “De-identified before sharing”: “Personal and identifying information is removed or transformed before your data is shared with third parties.” Under “Defined retention periods”: “Raw data is deleted according to an agreed schedule.” And under “U.S. and allied buyers only”: “Your data is licensed exclusively to labs and enterprises based in the U.S. and allied countries.”

The contracting step, on the data partnerships page, includes “a commitment not to resell or distribute your data until personal and identifying information has been anonymized.” After data is shared, “certain datasets may undergo synthetic rewrites that preserve workflow structure while reducing direct ties to original records.” A failure analysis rewritten that way keeps its logic (the crack, the cross-section, the contaminant, the cause) and loses the customer and the part number.

micro1 says “companies have the opportunity to review representative samples before use.” For an R&D group, the person to do that review is whoever knows which project codes point back to a client. Our page on how de-identification works goes through each step.

What decides the price

micro1 publishes three tiers under the line “Compensation is based on the quality, uniqueness, and value of the data provided”. They are $100K-500K for “Qualified Enterprise Data Partnerships” (indicative, not an offer), $500K-3M for “Large-scale operational datasets or ongoing participation across multiple teams and business functions” (indicative, not an offer), and $3M+ for “Highly unique, proprietary operational data” (indicative, not an offer). The payment step says micro1 pays “in full within 30 days of acceptance”.

How a company is placed, in micro1’s words: “Factors considered include dataset size and volume, workflow complexity, data quality, domain expertise represented, and the uniqueness of the operational knowledge contained within the dataset.” The estimate page adds: “Final payout is determined based on data sources, volume, quality, access terms, and due diligence.”

As our own reading, here is how those land in an R&D group.

Domain expertise and uniqueness are the strong suits. A trial series on a niche coating chemistry, run by people who have done it for twenty years, is written knowledge few companies have. Workflow complexity is high too: the bench, the analytical lab, the pilot line, safety and the customer all hand work to each other.

Quality is completeness. A notebook entry with the observation and the reason beats one with a yield and nothing else. A failure analysis with each test result attached beats a one-page summary.

Years and systems matter. micro1 says “Companies with several years of records across multiple business systems are generally a stronger fit.” A lab that moved from paper notebooks to an electronic system, or switched its sample tracking, should count both. Each factor is on what decides the price. micro1 evaluates each partnership individually; a tier is a published range, not an offer.

Which programme fits

Our rule: companies with 30 or more people, now or at peak, go to micro1, and so does a company of any size outside the US. micro1’s own line is “30+ full-time employees”. A US group under that line has a different programme; the estimate asks how many people work at the company and names the one that fits. Our programme page for 30 or more people explains how the count works.

R&D companies close or get folded into a buyer, and the notebooks often outlive the company. micro1’s referral page lists a “Defunct Company Data Partnership”: “We are acquiring data from companies that are no longer operating.” The requirements are “30+ employees”, “10+ Countries”, “English” and “All industries”, with company compensation of “$100K-$3M+ for approved data packages” (indicative, not an offer). Who holds the notebooks now, and who can sign for the old company, are the first questions. Our page on closed companies starts there.

Call centers and BPO keep a QA programme that works like a lab’s: a written standard, a sample checked against it, a note on every miss. Biotech and life sciences labs share the notebook, the deviation report and the sponsor contract that decides who owns the study. And software companies run their own version of the trial series, the bug ticket reopened three times until the cause was found.

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Questions and answers

Does micro1 want our formulations?

micro1 doesn't name formulations. Its pages describe data that reflects how work is actually performed, such as SOPs, process documentation, project histories and workflows. As our own advice, decide which recipes are in scope before you apply, and say so.

We do contract research. Can we license that work?

Only the client contracts say who owns the results and the files. As our own advice, anything a client owns under contract stays out, and counsel reads the contracts first.

What about our safety and exposure records?

OSHA's rule at 29 CFR 1910.1020 says each employee exposure record shall be kept for at least thirty years, with listed exceptions. Those records are about people, and as our own advice they stay out; ask counsel about any safety record before it moves.

Do we have to remove names first?

No. micro1 says it has processes for de-identifying and transforming sensitive information, so a company doesn't need to anonymize its data before transferring it.

What does micro1 pay?

micro1's data partnerships page lists $100K-500K, $500K-3M and $3M+ as its three tiers (indicative, not an offer). It says compensation is based on the quality, uniqueness and value of the data provided.

Do we give up the records?

No. micro1 says companies retain ownership of their underlying data. The lab keeps working from its own notebooks.