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
2M+ indexed papers · 150K+ material records · 12 property databases · 4 compute codes
The Problem
From 15 Tabs to One Question
Modern materials research demands jumping between literature databases, property repositories, simulation tools, and analysis software — each with its own interface, format, and workflow.
Hours of context-switching. Data trapped in incompatible formats. Manual copy-paste from paper tables to spreadsheets. Critical insights lost between tools.
material.codes connects your entire research stack into a single, AI-powered workflow.
Illustrative · loops automatically
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.
Research Scenarios
Built for Real Research Questions
From high-throughput screening to targeted property engineering — see how material.codes handles complex research workflows.
Battery Material Screening
Identify promising Li-ion cathode candidates from first-principles data with application-specific voltage and capacity constraints.
"Find layered oxide cathodes with average voltage > 3.8V, capacity > 180 mAh/g, and thermal stability above 200°C"- Queries Materials Project + AFLOW for matching compositions
- Cross-references electrochemical data from literature
- Ranks candidates by synthesizability scores
- Exports structures for DFT geometry relaxation
Top Result
LiNi0.8Mn0.1Co0.1O2 (NMC811)
Pipeline Steps
Semiconductor Band Engineering
Design alloy compositions to hit target band gaps for photovoltaic and LED applications using high-throughput DFT screening.
"InGaN alloys with direct bandgap between 2.6 and 3.0 eV for blue LED emission, lattice-matched to GaN substrate"- Retrieves composition-property relationships from AFLOW
- Applies Vegard's law interpolation with bowing corrections
- Generates band structure plots from existing calculations
- Flags lattice mismatch strain for selected compositions
Optimal Composition
In0.18Ga0.82N
Screening Results
Catalyst Surface Analysis
Identify active sites, compute adsorption energies, and screen surface terminations for heterogeneous catalysis applications.
"CO2 reduction on Cu surfaces — compare (100), (110), (111) facets for formate vs CO selectivity"- Constructs surface slabs from bulk structure
- Computes surface energies and identifies stable terminations
- Submits NEB calculations for reaction barriers
- Correlates results with selectivity trends from literature
Recommended Facet
Cu(100) — formate pathway
Adsorption Energies (eV)
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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