Collaborative Research: DMREF: Computationally Driven Discovery and Synthesis of 2D Materials through Selective Etching

合作研究：DMREF：通过选择性蚀刻计算驱动的 2D 材料发现和合成

• 批准号: 2324156
• 负责人: Konstantin Klyukin
• 金额: $ 121.92万
• 依托单位: Auburn University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324156&HistoricalAwards=false
• 关键词: Collaborative; Research; DMREF; Computationally; Driven

Non-technical Description: The discovery of novel two-dimensional (2D) materials is a very attractive research direction that can have a profound impact on a variety of applications in energy, environmental science, catalysis, and electronics. The selective electrochemical extraction of atoms from layered 3D structures promises a significant expansion of the world of 2D materials beyond the widely explored layered structures with weak interlayer interactions. To advance a new process for the synthesis of 2D materials and accelerate their discovery, a multidisciplinary team of chemists, physicists, and materials scientists will combine state-of-the-art computational, experimental, and machine-learning techniques in a closed-loop paradigm inspired by the Materials Genome Initiative. The project also includes high school outreach programs and interdisciplinary training of the next-generation workforce to cover a broad spectrum from synthesis and characterization to theory and modeling of materials.Technical Description: This DMREF project will provide the enabling fundamental knowledge required to develop a very selective electrochemical removal process for the synthesis of novel 2D materials of various compositions and structures. Initially focusing on a family of 2D transition metal carbides and nitrides (MXenes), our team will design a computational discovery methodology with experimental validation and closed-loop optimization of predictive models, focusing on the identification of promising 3D precursor phases and relevant etching conditions. The developed toolset will allow us to evaluate if the extraction of atomic layers is possible under electrochemical conditions, whether electrochemical etching will be selective and is not limited by kinetics, and whether the desired 2D structure will be stable in contact with electrolyte. Establishing relations of physics-based descriptors to experimental results and outcomes of simulations will allow us to carry out screening of large combinatorial material space. To validate the computational predictions, our team will perform high-throughput electrochemical etching of materials and low-throughput detailed materials characterization.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术描述：新型二维（2D）材料的发现是一个非常有吸引力的研究方向，可以对能源、环境科学、催化和电子领域的各种应用产生深远影响。从层状3D结构中选择性地电化学提取原子有望使2D材料的世界大大扩展，超越广泛探索的具有弱层间相互作用的层状结构。为了推进2D材料合成的新工艺并加速其发现，一个由化学家、物理学家和材料科学家组成的多学科团队将在材料基因组计划的启发下，将联合收割机最先进的计算、实验和机器学习技术结合在一个闭环范例中。该项目还包括高中外展计划和下一代劳动力的跨学科培训，涵盖从材料的合成和表征到理论和建模的广泛范围。技术描述：该DMREF项目将提供开发非常选择性的电化学去除过程所需的基础知识，用于合成各种成分和结构的新型2D材料。最初专注于2D过渡金属碳化物和氮化物（MXenes）家族，我们的团队将设计一种计算发现方法，通过实验验证和预测模型的闭环优化，重点是识别有前途的3D前体相和相关蚀刻条件。开发的工具集将使我们能够评估在电化学条件下原子层的提取是否可能，电化学蚀刻是否具有选择性并且不受动力学限制，以及所需的2D结构是否与电解质接触稳定。建立基于物理的描述符的实验结果和模拟结果的关系，将使我们能够进行大的组合材料空间的筛选。为了验证计算预测，我们的团队将进行高通量的材料电化学蚀刻和低通量的详细材料表征。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。