Projects | Modelling and Theory of Materials

ElastiCrys

Mon, 12 Oct 2026 00:00:00 +0000

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

Hrvatski prijevod

Visokopropusno pretraživanje elastičnih svojstava molekulskih kristala

Molekulski kristali sveprisutni su u organskoj elektronici, farmaceutici i agrokemiji, no njihovo je mehaničko ponašanje i dalje slabo istraženo. Mehanička svojstva, uključujući elastične konstante i njihovu anizotropiju, važna su za proizvodnju, stabilnost i fleksibilnu optoelektroniku.

Projekt ElastiCrys razvit će međuatomski potencijal temeljen na strojnom učenju i izračunati potpune elastične tenzore uz kvantificiranu nesigurnost. Pretraživanjem približno 500.000 struktura iz Cambridge Structural Database nastat će otvorena baza elastičnih svojstava. Projekt će izdvojiti neuobičajene odzive i potvrditi predviđanja ciljanim eksperimentima te podržati podatkovno vođen dizajn materijala.

Micro4Nano

Fri, 01 Oct 2021 00:00:00 +0000

Multifunctional nanocarriers for nonlinear microscopy: new tools for biology and medicine

Multiphoton microscopy enables three-dimensional visualisation of biological tissues, helping researchers understand the relationship between their structure and function. Micro4Nano develops methods for imaging to a depth of up to 1 mm, combining hyperspectral imaging, second-harmonic generation, fluorescent labels and Raman microscopy.

The project also develops multifunctional nanocarriers for two-photon microscopy and drug delivery, with the aim of monitoring living cells and tissues in real time. Its network training programme supports early-career researchers and interdisciplinary collaboration.

Project details

Project code: 101007804
Duration: 1 October 2021 – 30 September 2026
Institutional lead: Ivor Lončarić
Institution: Ruđer Bošković Institute — partner
Funder: European Union, Horizon 2020, H2020-MSCA-RISE-2020
Total project funding: €795,800
Institutional allocation: €59,800
Project website: CORDIS project record
CroRIS: Project record

Project team

Team members at the Ruđer Bošković Institute:

Hrvatski prijevod

Multifunkcionalni nanonosači za nelinearnu mikroskopiju: novi alati za biologiju i medicinu

Projekt Micro4Nano razvija metode trodimenzionalnog oslikavanja bioloških tkiva kombiniranjem hiperspektralnog oslikavanja, signala generacije drugog harmonika, fluorescentnih oznaka i Ramanove mikroskopije. Razvijaju se i multifunkcionalni nanonosači za dvofotonsku mikroskopiju i isporuku lijekova, uz interdisciplinarnu suradnju i osposobljavanje mladih znanstvenika.

ExtMatModelML

Fri, 15 Jan 2021 00:00:00 +0000

Extending length and time scales of first principles material modelling via machine learning

Density functional theory (DFT) is an indispensable tool in materials research, but simulations of large systems and long-time dynamics can be prohibitively expensive. This project uses machine learning to construct potential energy surfaces from precomputed DFT energies and forces, making simulations with near-DFT accuracy accessible at a fraction of the cost.

The project focuses on molecular crystals, including temperature-driven effects and crystal screening, and on the dynamics of molecules on surfaces relevant to heterogeneous catalysis. It also aims to strengthen materials research in Croatia through collaboration and the education of young researchers.

Project details

Project code: UIP-2020-02-5675
Duration: 15 January 2021 – 14 January 2026
Principal investigator: Ivor Lončarić
Host institution: Ruđer Bošković Institute
Funder: Croatian Science Foundation, Installation Research Projects programme, 2020-02 call
Funding: €243,413.63
Keywords: density functional theory, molecular dynamics, machine learning, molecular crystals, catalysis
CroRIS: Project record

Project team

Research infrastructure

Equipment: High-performance computing cluster (HPC ZTF)
Service: Advanced computing

Hrvatski prijevod

Povećanje prostorne i vremenske skale modeliranja materijala iz prvih principa pomoću strojnog učenja

Projekt koristi strojno učenje ploha potencijalne energije kako bi povezao preciznost teorije funkcionala gustoće s modeliranjem većih sustava i dugotrajne dinamike. Istražuju se molekulski kristali, temperaturno inducirane pojave i dinamika molekula na površinama relevantna za heterogenu katalizu.