Collaborative Research: New Phase Diagrams for Predictive Solvothermal Synthesis in Non-Aqueous Solvents

合作研究：非水溶剂中预测溶剂热合成的新相图

• 批准号: 2240282
• 负责人: Daniel Shoemaker
• 金额: $ 37.58万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2027-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2240282&HistoricalAwards=false
• 关键词: Collaborative; Research; New; Phase; Diagrams

Non-Technical Summary Solvothermal synthesis involves precipitating a solid out of a supersaturated solution and is a common materials synthesis route for functional materials. Many classes of important materials cannot be easily precipitated using water as the solvent; including intermetallics, sulfides, and nitrides; which are more readily synthesized in non-aqueous organic solvents. The number of available organic solvents is large, but there is currently no rigorous understanding of which combination of solvent and starting material is best to synthesize a given target material. With this project, supported by the Solid State and Materials Chemistry Program in NSF’s Division of Materials Research, Professor Wenhao Sun at the University of Michigan and Professor Daniel Shoemaker at the University of Illinois Urbana-Champaign build new predictive theoretical models to better understand which compounds precipitate out of supersaturated non-aqueous solutions. This scientific understanding allows chemists to skip the tedious trial-and-error efforts of solution synthesis optimization and enables the rational design of synthesis recipes for the manufacture and processing of new, more complex, or higher-quality materials that drive technological innovation. The research is carried out by undergraduate and graduate students, who are trained in computational materials science and experimental thermochemistry during this project.Technical SummaryMany classes of materials are synthesized in organic solvents, such as ethanol, ethylene-glycol, ammonia, acetonitrile, hydrazine, DMSO, DMF, THF, etc. Currently, there are no thermodynamic frameworks to guide solvothermal synthesis in non-aqueous media, meaning chemists largely rely on heuristics for precursor solubility and laborious trial-and-error efforts for solution synthesis optimization. This project undertakes a combined computational and experimental research program to develop the first thermodynamic phase diagrams to guide solvothermal synthesis in non-aqueous organic solvents. The project involves measuring and developing predictive models for the chemical potentials of solvated species in non-aqueous solvents, and then combining these ion chemical potentials with high-dimensional thermodynamic frameworks to predict the solubility and chemical equilibria of complex materials under various non-aqueous solvents and conditions. These new solvothermal phase diagrams offer a rigorous foundation to rationally design recipes for the targeted solution-based synthesis of advanced solid-state materials. Broad availability for the tools developed in this project is aided by interfacing with freely-available and widely-used thermochemical databases. Hands-on learning is supported by precisely aligning model precipitation reactions with undergraduate thermodynamics lessons in chemistry and materials science.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.

非技术综述溶剂热合成涉及从过饱和溶液中沉淀出固体，是功能材料的一种常见材料合成路线。许多重要的材料，包括金属间化合物、硫化物和氮化物，在非水有机溶剂中更容易合成，用水作为溶剂不易沉淀。可用的有机溶剂的数量很多，但目前还没有严格的理解，即哪种溶剂和起始材料的组合最适合合成给定的目标材料。在NSF材料研究部固态和材料化学计划的支持下，密歇根大学的孙文浩教授和伊利诺伊大学香槟分校的Daniel Shoemaker教授建立了新的预测理论模型，以更好地了解哪些化合物从过饱和的非水溶液中沉淀出来。这种科学的理解使化学家们可以跳过乏味的溶液合成优化的反复试验，并能够合理地设计合成配方，以制造和加工推动技术创新的新的、更复杂的或更高质量的材料。这项研究是由本科生和研究生进行的，他们在这个项目中接受了计算材料科学和实验热化学的培训。技术概述许多类别的材料都是在有机溶剂中合成的，如乙醇、乙二醇、氨、乙腈、肼、DMSO、DMF、THF等。目前，没有热力学框架来指导非水介质中的溶剂热合成，这意味着化学家在很大程度上依赖启发式方法来研究前体的溶解度，并进行艰苦的反复尝试来优化溶液合成。该项目开展了一项计算和实验相结合的研究计划，以开发第一个热力学相图来指导非水有机溶剂中的溶剂热合成。该项目包括测量和开发溶剂化物种在非水溶剂中的化学势的预测模型，然后将这些离子化学势与高维热力学框架相结合，以预测复杂材料在各种非水溶剂和条件下的溶解度和化学平衡。这些新的溶剂热相图为合理设计基于定向溶液的先进固态材料合成配方提供了严格的基础。该项目开发的工具的广泛可获得性得益于与免费提供和广泛使用的热化学数据库的接口。实践学习是通过精确地将模型沉淀反应与化学和材料科学的本科生热力学课程相一致来支持的。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。