aceDigital materials ecosystem: from databases to AI agents for autonomous discovery
The concept of a digital materials ecosystem represents a new paradigm in materials research, where data, theory, and automation are integrated into a unified and iterative framework. By combining reliable databases, physical frameworks, and intelligent data analysis, materials discovery is evolving from empirical exploration toward a systematic and predictive science. The rapid growth of data and artificial intelligence (AI) has enabled the identification of complex structure-property relationships, while advan…
Integration of AI with databases, theory and automation enables systematic predictive materials discovery by identifying complex structure-property relationships and closing the loop between prediction and validation.
Progress depends on unresolved needs for trustworthy benchmarked datasets, interpretable high-precision models, and standardization between digital inputs and experimental responses.
Evidence
- Peer-reviewedChemical Science2026-01-01
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Truvace Impact Record TRV-2026-0406, v1: “Digital materials ecosystem: from databases to AI agents for autonomous discovery.” Truvace, 2026-07-20. /record/TRV-2026-0406 (accessed at citation time). sha256 27d64fd041c04b30…
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