Understanding Material Synthesis Conditions and Complexity at High-Pressure
This project aims to develop computational tools using machine learning to guide the synthesis of next-generation materials that retain their properties under ambient conditions.
Projectdetails
Introduction
Functional materials with outstanding technological properties can be found under extreme pressures and temperatures. This is particularly true for nitrides and hydrides, where the application of high-pressure high-temperature (HPHT) conditions has recently revealed an unexpectedly rich and complex chemistry.
Properties and Applications
These conditions have enabled the synthesis of compounds showing outstanding mechanical and electronic properties with applications in:
- Electronics
- Hard coatings
- Hydrogen storage
- Superconductivity
- Many more
Challenges
However, great challenges remain to be conquered in order to truly explore the possibilities permitted by these exotic materials. Indeed, their properties often vanish when brought back to ambient conditions, either because:
- The atomic arrangement becomes energetically unfavourable.
- The underlying physical processes become energetically unfavourable.
Moreover, the importance of finite-T effects and the structural and dynamical complexity of these HPHT phases prohibit computations from efficiently guiding experimental synthesis.
Project Goal
The goal of this project is to provide the computational tools for guiding the efficient and targeted synthesis of next-generation technological materials, including:
- The choice of synthesis conditions
- The selection of precursor materials
We will search for materials that retain their functional properties under decompression or are directly synthesizable at ambient pressure.
Methodology
To accomplish this, we will develop a workflow based on machine learning inter-atomic potentials to numerically explore experimental synthesis conditions at ab-initio accuracy. This will enable:
- An analysis of thermodynamic competition between different phases at HPHT
- Rigorous benchmarking against experiments to ensure that we truly portray nature's behaviour
Conclusion
This project will open up uncharted horizons for exploiting pressure and temperature as thermodynamic variables to explore new chemistry and synthesis pathways, ultimately guiding experiments towards industrially relevant novel technological materials.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.500.000 |
Totale projectbegroting | € 1.500.000 |
Tijdlijn
Startdatum | 1-3-2024 |
Einddatum | 28-2-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- LINKOPINGS UNIVERSITETpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
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Quantum Probes for High-Pressure SuperconductivityThis project aims to use nitrogen-vacancy centers in diamond anvil cells for optically detecting the Meissner effect and characterizing superconductivity in hydrogen-rich compounds under high pressure. | ERC Advanced... | € 2.493.372 | 2025 | Details |
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High-pressure nitride materials: towards the controllable and scalable synthesis in a diamond anvil cell
HIPMAT aims to enhance high-pressure synthesis of nitride materials using advanced techniques to enable controlled production and understanding of novel compounds for diverse applications.
Quantum Probes for High-Pressure Superconductivity
This project aims to use nitrogen-vacancy centers in diamond anvil cells for optically detecting the Meissner effect and characterizing superconductivity in hydrogen-rich compounds under high pressure.
Hidden in the Noise: Transient Details of Nanoparticle-Catalyzed Reactions Under Challenging Conditions
The project aims to enhance the design of metal nanoparticle catalysts for the Haber-Bosch reaction by investigating their dynamics under high-pressure conditions using advanced experimental techniques.
Towards materials at extremes: from intense dynamic compression to expansion
The project develops techniques to generate extreme pressure conditions in liquids for enhanced mechanical treatment of cellulose fibers, integrating high voltage engineering and plasma physics.
Predicting the Extreme
PREXTREME aims to solve the fermion sign problem in warm dense matter using AI and supercomputers, enhancing understanding of hydrogen's properties and advancing applications in material science and nuclear fusion.