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AI agent for materials scientists

Candidate Material Screening Agent

Produce a short ranked list of candidates that meet the targets, with every value sourced.

DecisionsAutomationScience and researchProduct development
See how it worksGet access
Candidate Material Screening Agent: what goes in, what the agent does and what you get

What it does

Choosing a material for a new part can start with hundreds of candidates, compared in a spreadsheet with mixed sources and missing values. This agent takes the property targets, such as strength, density, maximum temperature and cost, and filters the candidate list. It checks where each value came from and whether the test conditions match the target. Candidates with missing values are searched for in databases and datasheets, and each new value gets a source note. It ranks what is left using the weights the scientist sets, and re-ranks as values are added. It shows which target eliminated each rejected candidate. It never makes the final choice. The scientist approves the shortlist. Edge case: a value measured at a different temperature is marked as not comparable.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Screening request submitted 2 USES A TOOL Load candidates and their known property values 3 DOES Check source and test conditions of each value 4 DOES Filter out candidates that fail any hard target 5 CHECKS THE RESULT Do any remaining candidates have missing values? If not: search databases and datasheets for the missingvalues and log the source. Back to step 3. 6 DOES Rank the remaining candidates by weighted score 7 CHECKS THE RESULT Does the ranking change when unknown values taketheir worst and best cases? If not: mark unstable candidates and seek data to settlethem. Back to step 6. 8 DOES Write the shortlist with the reason each othercandidate was removed 9 YOU APPROVE Scientist approves the shortlist 10 RESULT Ranked shortlist with source table
Read the steps as a list
  1. Screening request submitted
  2. Load candidates and their known property values
  3. Check source and test conditions of each value
  4. Filter out candidates that fail any hard target
  5. Do any remaining candidates have missing values?If not: search databases and datasheets for the missing values and log the source. Back to step 3.
  6. Rank the remaining candidates by weighted score
  7. Does the ranking change when unknown values take their worst and best cases?If not: mark unstable candidates and seek data to settle them. Back to step 6.
  8. Write the shortlist with the reason each other candidate was removed
  9. Scientist approves the shortlistThe agent waits here for your OK.
  10. Ranked shortlist with source table

How it decides

It eliminates a candidate that fails any hard target and ranks the rest by weighted score. A value with no source or mismatched conditions is treated as unknown, not as a pass.

  • Treat a value without a source as unknown
  • Mark values at different test conditions as not comparable
  • Eliminate on hard targets before ranking
  • Report ranking stability against unknown values

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Property targets and which are hard limits
  • Weights for ranking
  • Databases to search
  • Maximum shortlist size (default 5)
  • Cost limit

What keeps you in control

It always asks you first

  • The shortlist
  • Any change to the weights

Hard limits

  • Never present an unsourced value as fact
  • Keep rejected candidates in the log

It stops when

  • Done: shortlist approved with sources
  • Stop: no candidate meets all hard targets

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensFrom 140 alloys, 96 failed a 400 C service limit. The agent found 12 with missing creep data and located values for 9. It ranked 44 and found the top 3 swapped places if the 3 unknowns took their worst case. It sourced one more value, and the order held. The scientist approved a shortlist of 5.

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