CAMELLIA · Computational Mapping of Electrocatalytic Interfaces In-Operando Conditions
„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“
- Период
- 2022-05-15 → 2024-05-14
- Финансиране от ЕС
- 214 934 €
- Участници
- 1
- Схема
- HORIZON-TMA-MSCA-PF-EF
Линиите свързват координатора с партньорите.
Накратко на български
Катализаторите в химичните реакции се анализират чрез квантова механика и изкуствен интелект, за да се разбере поведението им на микроскопично ниво. Това помага за създаването на по-ефективни и устойчиви процеси за производство на енергия и лекарства.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Computational Mapping of Electrocatalytic Interfaces In-Operando Conditions
In the realm of chemical and energy production, catalysis plays a pivotal role in driving innovation and sustainability. Enhanced catalytic technologies are crucial for optimizing resources, reducing environmental impacts, and making essential commodities, such as pharmaceuticals, more accessible and cost-effective. A profound understanding of catalysts at the microscopic level is essential for this technological evolution. Utilizing tools like quantum mechanics and machine learning, we aim to uncover nuanced details of catalytic processes in both homogeneous and heterogeneous environments. These insights will foster technological advancements by enabling the optimization of catalytic processes. Project CAMELLIA has embarked on this challenging journey with specific objectives: Refining Computational Models: We intend to improve existing computational models to more accurately represent the dynamics of catalysts in various chemical reactions. By incorporating sophisticated techniques like accelerated Molecular Dynamics, machine learning, and artificial intelligence, we aim to deepen our understanding of catalyst behaviors at microscopic levels. Developing a Comprehensive Catalysis Database: Our goal is to assemble a robust database that will serve as a global knowledge reservoir, encompassing extensive information on catalytic properties and behaviors. This initiative will promote collaborative research and innovation by providing a rich resource of information in the field of catalysis. Achieving these objectives will significantly advance the field of catalysis, facilitating the development of more efficient and sustainable production processes, thereby enriching industries such as healthcare and energy.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
The aim of project CAMELLIA (ComputAtional Mapping of ELectrocataLytic InterfAces) is to derive fundamental insights, predict and design electrocatalytic properties (activity, selectivity, stability) of nanoparticles with realistic sizes, under operando conditions. To achieve this goal, a computational approach, based on electronic structure methods – Density Functional Theory calculations – in conjunction with newly developed Artificial Neural Network-trained interatomic potentials, is used. Coverage- , solvent-, and potential-cognizant static and molecular dynamics simulations are employed to develop a methodology for the construction of an open-source computational database, collecting properties of electrocatalytically active interfaces, under relevant experimental conditions. These insights will be used to i. elucidate the in-situ nature of electrocatalyst active sites, in the context of technologically-relevant chemical reactions; ii. bridge the gap between experimental and computational methods in addressing key processes hindering the development of active and stable electrocatalytic materials for successful deployment of fuel cells technology; iii. go beyond state-of-the-art computational models based on well-defined extended surfaces, towards realistic simulations of synthesized nanoparticles, in a complex electrochemical environment.
Оригинален текст от CORDIS (на английски).
Участници
- DANMARKS TEKNISKE UNIVERSITET · Kongens LyngbyКоординаторДания
Връзки
- Виж в CORDIS
- DOI: 10.3030/101063836
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5036cc016&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5036db9e6&appId=PPGMS
Данни: CORDIS, © Европейски съюз
