CAREER: Large-scale quantum-continuum simulation of layered metal oxide semiconductor photoelectrodes under finite-temperature electrochemical conditions

材料研究部门和化学部门为该职业奖提供资金，该奖项支持与教育和推广活动紧密结合的计算研究，旨在扩大现有光催化材料的调色板。太阳能是人类可用的最丰富的能源，但由于阳光的可变性，这种能源不能按需利用。这个职业奖支持人工光合作用特定领域的研究和教育，人工光合作用模拟自然光合作用，植物利用阳光驱动的过程，将叶子吸收的二氧化碳和根部泵入的水转化为有机营养物质，以支持它们的生存和生长。通过人工光合作用，可以生产出碳中性燃料。通过开发精确的计算机模型来预测人工光合作用背后的化学转化，PI和他的研究小组旨在回答围绕一种有前途的材料的燃料生产能力的关键问题，这种材料已被证明比以前使用的材料吸收更大一部分太阳光谱。这项研究的结果将是扩大在阳光下有效工作的材料的调色板，并开发新的软件，以了解特定材料成分的微小变化如何影响其最终的燃料生产性能。新软件将通过开源发行版向社区传播。该职业奖还支持一项全面的教育和推广计划，以增加妇女和代表性不足的群体在科学和工程领域的参与，重点是使她们接触计算机编程和模拟的世界，开发有效的教材，培养具有计算能力的新一代年轻科学家和工程师。加速材料建模领域多样化和训练有素的劳动力的出现，以努力减少新能源材料工业发展所涉及的时间和成本。技术概述材料研究部和化学部为该职业奖提供资金，该奖项支持与教育和推广活动紧密结合的计算研究，旨在扩大现有光催化材料的调色板。太阳能是人类可用的最丰富的能源，但由于阳光的可变性，这种能源不能按需利用。人工光合作用提供了一种可持续的方法，通过直接光催化将太阳能储存为化学燃料来克服这种可变性；然而，目前使用的大多数稳定的光催化剂依赖于金属氧化物半导体，其带隙与太阳光谱不匹配，这极大地限制了它们的整体性能。通过在现实环境条件下开发半导体和电解质界面上电化学反应的精确分子和亚分子模型，PI和他的研究团队旨在理解、预测和控制光化学反应器运行的表面机制，从而最大化其燃料生产性能。这个CAREER项目特别专注于研究层状金属氧化物光催化剂，它可以在阳光下发挥最佳作用。为了预测有前途的层状半导体的性质，PI将利用并进一步开发新发布的量子连续统模型，在有限温度下进行半导体溶液界面的大规模模拟，考虑离子的吸附和显式水层在外加电压下的响应。新的软件将在开源的Quantum-Espresso发行中创建，为计算界提供一个广泛适用和高度可转移的建模框架，用于未来研究带电光电极的光催化机制。该职业奖还支持一项全面的教育和推广计划，以增加妇女和代表性不足的群体在科学和工程领域的参与，重点是使她们接触计算机编程和模拟的世界，开发有效的教材，培养具有计算能力的新一代年轻科学家和工程师。加速材料建模领域多样化和训练有素的劳动力的出现，以努力减少新能源材料工业发展所涉及的时间和成本。

NON-TECHNICAL SUMMARYThe Division of Materials Research and the Division of Chemistry provide funding for this CAREER award, which supports computational research tightly integrated with educational and outreach activities aimed at broadening the palette of currently available photocatalytic materials.Solar energy is the most abundant energy source available to humankind, but this energy cannot be harnessed on demand due to the variability of sunlight. This CAREER award supports research and education in the specific area of artificial photosynthesis, which emulates natural photosynthesis, the sunlight-driven process used by plants to transform the carbon dioxide absorbed by their leaves and the water pumped by their roots into organic nutrients for supporting their survival and growth. Using artificial photosynthesis, carbon-neutral fuels can be produced.By developing accurate computer models to predict the chemical transformations that underlie artificial photosynthesis, the PI and his research team aim at answering critical questions that surround the fuel-production ability of a promising family of materials that have been shown to absorb a much larger portion of the solar spectrum than previously used materials. The outcome of this research will be to expand the palette of materials that can efficiently operate under sunlight, and develop new software for understanding how small variations in the composition of a given material can affect its ultimate fuel-production performance. The new software will be disseminated to the community through an open-source distribution.This CAREER award also supports a comprehensive educational and outreach plan to increase the participation of women and underrepresented groups in science and engineering with an emphasis on exposing them to the universe of computer programming and simulation, on developing effective teaching materials to train a computationally literate generation of young scientists and engineers, and on accelerating the emergence of a diverse and well-trained workforce in the area of materials modeling in an effort to reduce the time and cost involved in the industrial development of new energy materials.TECHNICAL SUMMARYThe Division of Materials Research and the Division of Chemistry provide funding for this CAREER award, which supports computational research tightly integrated with educational and outreach activities aimed at broadening the palette of currently available photocatalytic materials. Solar energy is the most abundant energy source available to humankind, but this energy cannot be harnessed on demand due to the variability of sunlight. Artificial photosynthesis provides a sustainable way to overcome that variability through the direct photocatalytic storage of solar power into chemical fuels; however, most of the stable photocatalysts in use today rely on metal oxide semiconductors whose bandgap does not match the solar spectrum, which greatly limits their overall performance.By developing accurate molecular and submolecular models of electrochemical reactions at the interface between a semiconductor and an electrolyte under realistic environmental conditions, the PI and his research team aim to understand, predict, and control the surface mechanisms that underlie the operation of photochemical reactors towards maximizing their fuel-production performance. This CAREER project is specifically focused on studying layered metal oxide photocatalysts that can operate optimally under sunlight. In order to predict the properties of promising layered semiconductors, the PI will exploit and further develop a newly released quantum-continuum model to perform large-scale simulations of semiconductor-solution interfaces at finite temperature, taking into account the adsorption of ions and the response of explicit water layers under applied voltage. New software will be created in the open-source Quantum-Espresso distribution to provide the computational community with a widely applicable and highly transferable modeling framework for future studies of photocatalytic mechanisms at electrified photoelectrodes. This CAREER award also supports a comprehensive educational and outreach plan to increase the participation of women and underrepresented groups in science and engineering with an emphasis on exposing them to the universe of computer programming and simulation, on developing effective teaching materials to train a computationally literate generation of young scientists and engineers, and on accelerating the emergence of a diverse and well-trained workforce in the area of materials modeling in an effort to reduce the time and cost involved in the industrial development of new energy materials.