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What you get

A comparison matrix of candidates against the conditions you care about. Every populated cell cites a paper and the conditions the value was measured under. Every empty cell is a gap — and those are where your test budget should go.

Who it’s for

Materials, process, and reliability engineers choosing between options with incomplete internal data. Semiconductor, automotive, aerospace, and consumer-product R&D groups.

The move that makes this work

Express the requirement as conditions, not as a material name. The spec becomes the query: temperature range, cycle count, atmosphere, dimension, contaminant, load. Then hold those conditions constant across every candidate so the results are comparable. A search for a material name returns everything ever written about it. A search for the material under your conditions returns the handful of papers that answer your question.

How it works

1

Turn the spec into physical conditions

Write the operating envelope out explicitly before searching. This is the step that determines whether the output is usable.
2

One fan-out per candidate, conditions held constant

Run a query set per material or process, varying only the candidate. Anything else and you are comparing searches, not materials.
3

Set the domain, or drown

Without domain=mat,eng,phys,chem, technical vocabulary pulls in unrelated biomedical literature. This single parameter is the difference between a usable and an unusable result set.
4

Extract values with their conditions attached

Use include_full_text_chunks=true. A performance number without its test conditions is not comparable to another number, and conditions live in methods sections rather than abstracts.
5

Report the gaps as loudly as the data

Say plainly which candidate-condition combinations have no published data. That is the most actionable output of the whole exercise.

The API call

Full-text excerpts require a paid plan or an Enterprise API key and currently cover open-access papers. Engineering and materials literature skews toward closed-access conference proceedings, so expect coverage here to be patchier than in biomedicine — check before treating the matrix as complete.
Useful domain codes for this work: mat (materials), eng (engineering), phys (physics), chem (chemistry), env (environmental).

What to check before you trust it

  • Verify conditions on every extracted value. A modulus measured at room temperature says nothing about behaviour at 200°C, and the two look identical in a table.
  • Watch for standards mismatch. Values measured under different test standards are not comparable even when units match.
  • Empty cells may be a terminology problem. Before reporting a gap, re-run with the alternative names the field uses for the same material or process.
  • Published performance is best-case. Laboratory conditions and production conditions differ; treat literature values as an upper bound to validate, not a spec to adopt.

Find published process conditions for a manufacturing step

Once you have chosen the material, find the conditions to run it at.

Extract numbers and formulas from full-text papers

The extraction discipline this depends on.

Best practices

Excerpt-first extraction and the rest of the primitives.

All use cases

Browse the gallery by persona.