From Hypothesis
to Atomic Structure
Unified access to scientific literature, materials databases, DFT compute, and an AI research assistant — designed for materials scientists.
Free during preview · No credit card
8.4M+ indexed papers
The Problem
From 15 Tabs to One Question
Materials research today means juggling literature databases, property repositories, and simulation tools — hours of context-switching, data trapped in incompatible formats, insights lost between tabs. material.codes connects your entire research stack into a single, AI-powered workflow.
Illustrative · loops automatically
The Platform
Four Modules. One Workflow.
Every tool a materials scientist needs — tightly integrated, so the output of one module feeds directly into the next.
Literature Intelligence
Semantic search over an indexed Semantic Scholar and OpenAlex corpus. Structured data extraction, AI summaries with citations.
"perovskite solar cell efficiency above 25% — last 2 years" Materials Datasets
One interface to materials property databases. Query by composition, structure, or property; download structures in any format.
"cubic perovskites with bandgap 1.2–1.8 eV, stable at 300K" Compute Engine
Submit DFT calculations without writing input files. Pseudopotentials, k-point grids, and convergence checks are automatic.
"optimize geometry of mp-2815 with PBE+U, U=3.5 on Fe" Quantum ESPRESSO
AI Assistant
A domain-aware research assistant orchestrating all four modules from natural language. Keeps context, cites primary sources.
"compare Li-ion cathode candidates for high-temp applications" Traceable by Design
Every Answer Traceable to Its Source
In R&D, an answer is only as trustworthy as the sources behind it. material.codes keeps the full chain visible — from raw measurement to final recommendation.
Built for teams that need to show where a decision came from — for internal review, IP defensibility, and regulatory scrutiny.
Source Links
Every property value links to its source database and measurement method.
Cited Answers
Every AI answer cites the primary sources it drew from.
Audit Trail
Exportable audit trail for compliance review.
Anchor Workflow
Battery Cathode Screening
The workflow we lead with: Li-ion cathode candidates from first-principles data, cross-referenced against literature, ranked, and validated with DFT — in one place.
"Find Li-ion cathode candidates with average voltage 3.5–4.3 V and energy above hull below 50 meV/atom"- Queries connected materials databases by voltage window and thermodynamic stability
- Cross-references discharge capacities reported in the literature
- Ranks candidates — thermodynamic stability first, then capacity and voltage fit
- Runs DFT geometry relaxation on the shortlist
Top Result
LiNi0.8Mn0.1Co0.1O2 (NMC811)
Pipeline Steps
Illustrative
Semiconductor Band Engineering
Same engine, different recipe: property filters, literature cross-reference, DFT validation — tuned for target band gaps.
"InGaN alloys with direct bandgap between 2.6 and 3.0 eV, lattice-matched to GaN"Catalyst Surface Analysis
On the roadmapSurface slabs, adsorption energies, and NEB reaction barriers will need a new class of compute — planned, not yet live.
Model Context Protocol
Plug Materials Data Into Your Own AI Stack
material.codes speaks MCP. Connect literature search, materials database queries, and DFT submission to Claude, Cursor, or any MCP-compatible client — from inside your team's own AI workflows.
{
"mcpServers": {
"material-codes": {
"url": "https://material.codes/mcp",
"headers": { "Authorization": "Bearer <your API key>" }
}
}
}API keys are self-managed in the Lab once you have access.
Plans & Access
Choose your plan
Every plan unlocks the full platform. Higher plans lift monthly limits and quality.
Researcher
For active research
Computational
DFT & agentic workflows
Principal
Lead a research program
Explorer is free and available now. Researcher, Computational, and Principal are coming soon. Academic pricing will be available for verified researchers.
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