ElastiCrys

High-throughput screening of elastic properties in molecular crystals

Molecular crystals are found in organic electronics, pharmaceuticals, and agrochemicals, yet their mechanical behaviour remains poorly mapped. Their elastic constants, directional dependence, and mechanical robustness affect manufacturing, solid-form stability, and the development of flexible optoelectronic materials.

ElastiCrys will develop a machine-learning interatomic potential for molecular crystals and calculate full elastic tensors with quantified uncertainty. A high-throughput pipeline will screen approximately 500,000 curated Cambridge Structural Database entries to create an open, searchable elasticity atlas. The project will identify unusual responses, including negative linear compressibility, and validate promising predictions through targeted experiments. The resulting database will support reproducible materials selection, benchmarking, and data-driven design.

Project details

• Project code: IP-2026-5909
• Duration: 12 October 2026 – 11 October 2029
• Principal investigator: Ivor Lončarić
• Host institution: Ruđer Bošković Institute
• Funder: Croatian Science Foundation, Research Projects programme, 2026 call
• Funding: €134,550
• Keywords: machine learning, artificial intelligence, materials design, density functional theory, molecular crystals, elastic properties
• CroRIS: Project record

Project team

• Ivor Lončarić — principal investigator
• Luka Benić
• Radovan Matula
• Bernhard Kretz