CAREER: Blueprint for Unlocking New Energy Conversion Functionality in Chalcogenide Frameworks through Precisely Designed Composition, Electronic Structure and Surface Coordination

职业：通过精确设计的成分、电子结构和表面配位解锁硫族化物框架中新能源转换功能的蓝图

• 批准号: 2044403
• 负责人: Jesus Velazquez
• 金额: $ 52.09万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2044403&HistoricalAwards=false
• 关键词: CAREER; Blueprint; Unlocking; New; Energy

Non-Technical Summary: An entirely new palette of materials is required to enable a sustainable terawatt-scale energy infrastructure. The development of functional materials with properties that facilitate renewable energy conversion and storage represents a promising approach that takes direct aim at this problem, one of the defining challenges of our time. This project, which is supported jointly by the Solid State and Materials Chemistry program in the Division of Materials Research and the Catalysis program in the Division of Chemical, Bioengineering, Environmental and Transport Systems, has far-reaching impact on both national and global sustainability, the accelerated discovery of economically viable energy conversion materials. The classes of materials being explored in this effort have properties such as electrical conductance, efficacy of solar-energy absorption, and electrochemical reactivity towards carbon dioxide reduction that are programmable as a function of their structure and elemental make-up. PI Velazquez’s study is comprised of an iterative combination of experimental research and computational modeling. The focus of this project is to combine state-of-the-art materials synthesis with experimental evaluation of electronic and structural properties in tailor-made solid-sate materials such that their properties of relevance to energy conversion can be accurately mapped to their composition and structure. This effort is augmented by a predictive computational modeling approach where favorable material properties are predicted for entirely new elemental compositions, thereby yielding new candidate materials in a closed-loop manner. In parallel with the experimental effort, undergraduate and graduate students are trained to solve problems at the interface between solid-state materials chemistry and chemical engineering; the training program specifically supports underrepresented minority and first-generation students. A major thrust of the educational plan involves curriculum supplementation through remote integration of modern solid-state chemistry and engineering research into high schools, thereby providing aspiring scientists with the tools required to successfully engage in STEM research. Technical Summary: This research systematically elucidates fundamental understanding of versatile classes of multi-dimensional metal chalcogenides, revealing material property descriptors through ex situ, in-situ, and operando measurements of atomistic and electronic structure in order to inform predictive models for electrochemical and photoelectrochemical reactivity. The PI hypothesizes that fine control over local metal-chalcogen coordination, intercalant charge density, and binary/ternary stoichiometry engenders desirable material properties that underpin energy conversion and storage functionality, including binding-site carbophilicity/oxophilicity, framework ionicity/covalency, and band gap/positions. To evaluate this hypothesis, the composition and local geometry of small-molecule adsorption sites in solid-state chalcogenide frameworks are systematically modified across the span of a substantial design space in order to experimentally and computationally elucidate trends in functionality that correlate with chemical and physical properties. Experimental results borne out of these modifications inform predictive machine learning-density functional theory models, which in turn generate candidate framework compositions that will engender optimal properties. This approach effectively closes a feedback loop between experiment and theory; as such, the anticipated products of this study are new metal chalcogenide materials and heterostructures from the 1D M2Mo6X6 (M = K, Rb, Cs; X = S, Se, Te), 2D MX2 (M = Ti, Mo, W; X = S, Se, Te), and 0D/3D MyMo6X8 (M = alkali, alkaline, transition, and/or post transition metal; y = 0–4; X = O, S, Se, Te) composition spaces that predictably yield oxygenated fuels, mediate bulk and interfacial charge-transport, and enable tunable photon absorption. More importantly, this research is expected to yield a materials design toolset that illustrates the importance of successfully iterative interplay between theory, synthesis, structure elucidation, and electronic structure studies when it comes to generating desirable solid-state properties. The intellectual merit of this work stems from its integrative approach to material design, where a foundational understanding regarding the effects of composition and structure on emergent physical properties, chemical reactivity, and energy conversion-related functionality is unraveled.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.

非技术摘要：需要全新的材料调色板来实现可持续的Terawatt尺度能源基础设施。具有促进可再生能源转换和存储的属性的功能材料的开发代表了一种有希望的方法，它直接针对这个问题，这是我们时代的定义挑战之一。该项目得到了材料研究部和化学，生物工程，环境和运输系统部材料研究和催化计划的共同支持，对国家和全球可持续性都具有深远的影响，这是对经济上可行的能源转换材料的良好发现。在这项工作中探索的材料类别具有诸如电导，太阳能吸收的有效性以及对还原碳还原碳的电化学反应性，这些反应性是其结构和元素化妆的函数。 Pi Velazquez的研究完成了实验研究和计算建模的迭代组合。该项目的重点是将最先进的材料合成与对量身定制的固态材料中的电子和结构特性进行实验评估，以便将其与能量转化的特性准确地映射到其组成和结构上。通过预测的计算建模方法来增强这种工作，其中预测了全新的元素组成的有利材料特性，从而以闭环方式产生新的候选材料。与实验努力同时，对本科生和研究生进行了培训，以解决固态材料化学和化学工程之间的界面上的问题。该培训计划专门支持代表性不足的少数群体和第一代学生。教育计划的一个主要作用是通过将现代固态化学和工程研究远程整合到高中，从而为有抱负的科学家提供成功从事STEM研究所需的工具，从而补充了课程。技术摘要：这项研究系统地阐明了对多维金属金属核化的多功能类别的基本理解，通过现场，原地和原子和电子结构的Operanto测量来揭示材料特性描述符，以便为预测性模型提供电学模型和光电极的预测模型。 PI假设是，对局部金属 - chalcogen配位，间剂电荷密度以及二进制/三元阶层计量学工程师的精细控制所需的材料具有理想的材料，这些特性是能量转换和存储功能的基础，包括结合位点的碳纤维/氧粒性，框架的离子/共价性/共价性和频带差异和频带差异。为了评估这一假设，在固态葡萄球菌剂框架中，小分子吸附位点的组成和局部几何形状在整个大量设计空间的跨度上进行了系统的修饰，以便在实验和计算上阐明与化学和物理特性相关的功能趋势。这些修改为实验结果带来了预测性的机器学习密度功能理论模型，从而产生候选框架组成，从而产生最佳特性。方法有效地关闭了实验和理论之间的反馈回路。 as such, the anticipated products of this study are new metal chalcogenide materials and heterostructures from the 1D M2Mo6X6 (M = K, Rb, Cs; X = S, Se, Te), 2D MX2 (M = Ti, Mo, W; X = S, Se, Te), and 0D/3D MyMo6X8 (M = alkali, alkaline, transition, and/or post transition metal; y = 0–4; x = o，s，se，te）的组成空间，可以预测产生氧化燃料，培养基和界面电荷传输，并启用可调的光子滥用。更重要的是，这项研究有望产生材料设计工具集，该工具集说明了在产生理想的固态特性时，理论，合成，结构阐明和电子结构研究之间成功迭代相互作用的重要性。该工作植物从其综合方法到材料设计的智力优点，在这些方法中，对组成和结构对新兴物理特性的影响，化学反应性以及与能量转换相关的功能的基础理解被阐明了。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子优点和广泛的影响来评估NSF的法定任务，并被认为是宝贵的支持。

项目成果

Machine Learning Guided Synthesis of Multinary Chevrel Phase Chalcogenides

机器学习引导多元 Chevrel 相硫属化物的合成

• DOI: 10.1021/jacs.1c02971
• 发表时间: 2021
• 期刊: Journal of the American Chemical Society
• 影响因子: 15
• 作者: Singstock, Nicholas R.;Ortiz-Rodríguez, Jessica C.;Perryman, Joseph T.;Sutton, Christopher;Velázquez, Jesús M.;Musgrave, Charles B.
• 通讯作者: Musgrave, Charles B.

Ln 10 S 14 O (Ln = La, Pr, Nd, Sm) Oxysulfides: A Series of Direct n-Type Semiconductors

Ln 10 S 14 O (Ln = La, Pr, Nd, Sm) 硫氧化物：一系列直接 n 型半导体

• DOI: 10.1021/acs.chemmater.2c01244
• 发表时间: 2022
• 期刊: Chemistry of Materials
• 影响因子: 8.6
• 作者: Wuille Bille, Brian A.;Kundmann, Anna C.;Osterloh, Frank E.;Velázquez, Jesús M.
• 通讯作者: Velázquez, Jesús M.

Promoting Inclusive and Culturally responsive Teaching using Co-classes for General Chemistry

利用普通化学共同课程促进包容性和文化响应式教学

• DOI: 10.1021/acs.jchemed.1c00339
• 发表时间: 2021
• 期刊: Journal of chemical education
• 影响因子: 3
• 作者: Ortiz-Rodríguez, J. C.;Brinkman, H.;Nglankong, L.;Enderle, B.*;Velázquez, J. M.*
• 通讯作者: Velázquez, J. M.*

Synthesis and thermodynamics of uranium-incorporated α-Fe2O3 nanoparticles

• DOI: 10.1016/j.jnucmat.2021.153172
• 发表时间: 2021-07-14
• 期刊: JOURNAL OF NUCLEAR MATERIALS
• 影响因子: 3.1
• 作者: Lam, Andy;Hyler, Forrest;Navrotsky, Alexandra
• 通讯作者: Navrotsky, Alexandra