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Enhanced Atmospheric Water Harvesting in Metal-Organic Frameworks = = 增强基于金属有机框架的大气水收集.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Enhanced Atmospheric Water Harvesting in Metal-Organic Frameworks =/
其他題名:	增强基于金属有机框架的大气水收集.
作者:	Zheng, Zhiling.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	163 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-09, Section: B.
Contained By:	Dissertations Abstracts International85-09B.
標題:	Chemistry. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30813998
ISBN:	9798381743487

Enhanced Atmospheric Water Harvesting in Metal-Organic Frameworks = = 增强基于金属有机框架的大气水收集.
Zheng, Zhiling.

Enhanced Atmospheric Water Harvesting in Metal-Organic Frameworks =增强基于金属有机框架的大气水收集. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 163 p.

Source: Dissertations Abstracts International, Volume: 85-09, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2023.

The dawn of the 21st century has ushered in a water crisis, intensified by the dual challenges of climate change and burgeoning population growth. Freshwater reservoirs are being strained, and while there are existing water generation technologies, they often come with limitations, either being energy-consuming or geographically confined. In response, atmospheric water harvesting (AWH) has emerged as a potential remedy, providing access to an inexhaustible source of water. Central to this solution is the development of efficient materials capable of capturing water, especially in arid regions where the need is most urgent. Metal-organic frameworks (MOFs), with their unique construction from metal-containing secondary building units (SBUs) linked by organic molecules, present a robust, crystalline, and enduringly porous framework, placing them at the forefront of potential solutions. MOFs' structural and chemical versatility, combined with their ultra-high porosity, makes them ideal candidates for large gas and vapor uptakes, thereby making them invaluable for AWH.This dissertation focuses on a range of methodologies aimed at enhancing the design, synthesis, and pragmatic applications of MOFs in atmospheric water harvesting. The focus is twofold: discovery strategies and optimization techniques. Key highlights include the pivotal role of reticular design in augmenting MOF water harvesting properties and the synergy between artificial intelligence (AI) and reticular chemistry to accelerate the close-up discovery of water-harvesting MOFs. Furthermore, this work elucidates high-yield, eco-friendly, and scalable synthesis protocols for MOFs, along with device-centric optimizations to harness MOFs' potential in real-world water harvesting scenarios. Chapter I provides a general introduction to metal-organic frameworks and their potential in water harvesting. MOFs, as emerging candidates, possess numerous advantages, making them ideal sorbents for water harvesting. These include retaining water capacity across multiple uptake-release cycles, exhibiting impressive water sorption capacities under operational conditions, requiring lower regeneration temperatures, and demonstrating dynamic water sorption properties. Apart from their high crystallinity and permanent porosity, the tunability of MOFs facilitates the design of bespoke materials tailored for specific needs. This chapter emphasizes the role of reticular design in establishing MOFs as a distinctive class of sorbents for atmospheric water harvesting. It also delves into the structure-function relationships of MOFs pertinent to water sorption and discusses the principles for designing novel MOFs for this application. Chapter II delves into synthesis strategies tailored for the large-scale and eco-friendly production of MOFs suitable for water harvesting. While traditional MOF synthesis primarily targets small-scale laboratory setups, the broader application of MOF technology for water harvesting necessitates overcoming challenges in scalability and productivity. This chapter bridges the gap between laboratory findings and industrial applications. It introduces a green, robust, and high-yield synthesis protocol for MOFs, prioritizing cost-effectiveness and environmental sustainability. Several aluminum-based MOFs were synthesized at the kilogram scale and detailed characterization confirmed the retaining of their crystallinity and water uptake capacities. The chapter also sheds light on key parameters essential for optimizing the green synthesis of MOFs, emphasizing their future scalability in water harvesting applications.Chapter III shifts the focus from the sorbent material to device optimization. A notable advancement in passive water harvesting is introduced through the design of a device leveraging MOF-303. Characterized by its efficiency and modularity, this device demonstrated its prowess in real-world conditions, particularly in extreme environments in the Death Valley National Park. The chapter underscores the device's potential in combating water scarcity and outlines several key parameters crucial for enhancing its atmospheric water harvesting efficiency. Chapters IV and V elucidate new strategies to enhance MOF water sorption properties. Specifically, Chapter IV delves into a multivariate approach, transitioning a single-linker MOF to a diverse mixed-linker MOF family. The resulting MOFs benefit from wider tunability in both operational humidity ranges and the regeneration temperature. Additionally, the employed synthesis method is both scalable and environmentally conscious. Chapter V presents a "linker arm" extension strategy, which enhances the water-harvesting capabilities of MOF-303 by elongating the linker "arm", resulting in a significant 50% boost in water uptake. These two examples of strategic innovation underscore the versatility and potential of MOFs in water-harvesting applications.Chapter VI delves into the transformative potential of AI-guided MOF synthesis, suggesting a departure from traditional research paradigms towards innovative methodologies for discovering new MOFs tailored for water harvesting. The chapter champions the use of AI agents to alleviate labor-intensive lab tasks, thereby allowing researchers to focus on more intricate aspects and achieve enhanced efficiency. The integration of machine learning algorithms aims to curtail human biases in optimizing MOF synthesis conditions. Specifically, a suite of seven ChatGPT-based agents is introduced, demonstrating their capability to streamline numerous lab activities. This confluence of AI and MOF synthesis marked a significant milestone in refining water-harvesting MOFs, with the overarching AI framework streamlining the synthesis process, mitigating human biases, and maximizing efficiency.Chapter VII is the concluding chapter of my thesis. In it, I share my reflections and insights on the future development of MOFs for atmospheric water harvesting. As we delve deeper into this field and refine our design principles and optimization strategies, I believe that MOFs will undoubtedly play a pivotal role in ensuring water security, sustainability, and prosperity for all.

ISBN: 9798381743487Subjects--Topical Terms:

516420
Chemistry.
Subjects--Index Terms:

Adsorption isotherms

Enhanced Atmospheric Water Harvesting in Metal-Organic Frameworks = = 增强基于金属有机框架的大气水收集.
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500 $a Source: Dissertations Abstracts International, Volume: 85-09, Section: B.
500 $a Advisor: Yaghi, Omar M.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2023.
520 $a The dawn of the 21st century has ushered in a water crisis, intensified by the dual challenges of climate change and burgeoning population growth. Freshwater reservoirs are being strained, and while there are existing water generation technologies, they often come with limitations, either being energy-consuming or geographically confined. In response, atmospheric water harvesting (AWH) has emerged as a potential remedy, providing access to an inexhaustible source of water. Central to this solution is the development of efficient materials capable of capturing water, especially in arid regions where the need is most urgent. Metal-organic frameworks (MOFs), with their unique construction from metal-containing secondary building units (SBUs) linked by organic molecules, present a robust, crystalline, and enduringly porous framework, placing them at the forefront of potential solutions. MOFs' structural and chemical versatility, combined with their ultra-high porosity, makes them ideal candidates for large gas and vapor uptakes, thereby making them invaluable for AWH.This dissertation focuses on a range of methodologies aimed at enhancing the design, synthesis, and pragmatic applications of MOFs in atmospheric water harvesting. The focus is twofold: discovery strategies and optimization techniques. Key highlights include the pivotal role of reticular design in augmenting MOF water harvesting properties and the synergy between artificial intelligence (AI) and reticular chemistry to accelerate the close-up discovery of water-harvesting MOFs. Furthermore, this work elucidates high-yield, eco-friendly, and scalable synthesis protocols for MOFs, along with device-centric optimizations to harness MOFs' potential in real-world water harvesting scenarios. Chapter I provides a general introduction to metal-organic frameworks and their potential in water harvesting. MOFs, as emerging candidates, possess numerous advantages, making them ideal sorbents for water harvesting. These include retaining water capacity across multiple uptake-release cycles, exhibiting impressive water sorption capacities under operational conditions, requiring lower regeneration temperatures, and demonstrating dynamic water sorption properties. Apart from their high crystallinity and permanent porosity, the tunability of MOFs facilitates the design of bespoke materials tailored for specific needs. This chapter emphasizes the role of reticular design in establishing MOFs as a distinctive class of sorbents for atmospheric water harvesting. It also delves into the structure-function relationships of MOFs pertinent to water sorption and discusses the principles for designing novel MOFs for this application. Chapter II delves into synthesis strategies tailored for the large-scale and eco-friendly production of MOFs suitable for water harvesting. While traditional MOF synthesis primarily targets small-scale laboratory setups, the broader application of MOF technology for water harvesting necessitates overcoming challenges in scalability and productivity. This chapter bridges the gap between laboratory findings and industrial applications. It introduces a green, robust, and high-yield synthesis protocol for MOFs, prioritizing cost-effectiveness and environmental sustainability. Several aluminum-based MOFs were synthesized at the kilogram scale and detailed characterization confirmed the retaining of their crystallinity and water uptake capacities. The chapter also sheds light on key parameters essential for optimizing the green synthesis of MOFs, emphasizing their future scalability in water harvesting applications.Chapter III shifts the focus from the sorbent material to device optimization. A notable advancement in passive water harvesting is introduced through the design of a device leveraging MOF-303. Characterized by its efficiency and modularity, this device demonstrated its prowess in real-world conditions, particularly in extreme environments in the Death Valley National Park. The chapter underscores the device's potential in combating water scarcity and outlines several key parameters crucial for enhancing its atmospheric water harvesting efficiency. Chapters IV and V elucidate new strategies to enhance MOF water sorption properties. Specifically, Chapter IV delves into a multivariate approach, transitioning a single-linker MOF to a diverse mixed-linker MOF family. The resulting MOFs benefit from wider tunability in both operational humidity ranges and the regeneration temperature. Additionally, the employed synthesis method is both scalable and environmentally conscious. Chapter V presents a "linker arm" extension strategy, which enhances the water-harvesting capabilities of MOF-303 by elongating the linker "arm", resulting in a significant 50% boost in water uptake. These two examples of strategic innovation underscore the versatility and potential of MOFs in water-harvesting applications.Chapter VI delves into the transformative potential of AI-guided MOF synthesis, suggesting a departure from traditional research paradigms towards innovative methodologies for discovering new MOFs tailored for water harvesting. The chapter champions the use of AI agents to alleviate labor-intensive lab tasks, thereby allowing researchers to focus on more intricate aspects and achieve enhanced efficiency. The integration of machine learning algorithms aims to curtail human biases in optimizing MOF synthesis conditions. Specifically, a suite of seven ChatGPT-based agents is introduced, demonstrating their capability to streamline numerous lab activities. This confluence of AI and MOF synthesis marked a significant milestone in refining water-harvesting MOFs, with the overarching AI framework streamlining the synthesis process, mitigating human biases, and maximizing efficiency.Chapter VII is the concluding chapter of my thesis. In it, I share my reflections and insights on the future development of MOFs for atmospheric water harvesting. As we delve deeper into this field and refine our design principles and optimization strategies, I believe that MOFs will undoubtedly play a pivotal role in ensuring water security, sustainability, and prosperity for all.
520 $a 伴随着21世纪黎明的曙光，水危机也悄然而至。气候变化和人口增长的双重挑战更是加剧了这一危机。淡水资源储备正承受着压力，现有的水生成技术虽然存在，但通常有很大限制：要么耗能，要么地理上受限。为了应对这一考验，大气水收集（AWH）已经成为一种潜在的解决方案，为获取无尽的水源提供了途径。这个解决方案的核心是开发能够捕获水分的高效材料，特别是在最急需的干旱地区。由金属含量的次级构建单元（SBU）与有机分子连接而成的金属有机框架（MOFs）以其独特的结构、坚固、晶体且持久多孔的框架，使其成为潜在解决方案的前沿。MOFs的结构和化学多样性，结合其超高的多孔性，使其成为大量气体和蒸汽吸收的理想候选物，因此对AWH至关重要。本论文专注于一系列旨在增强MOFs在大气水收集中的设计、合成和实际应用的方法论。重点是两方面：发现策略和优化技术。重要亮点包括网格设计在增强MOF水收集属性中的关键作用，以及人工智能（AI）与网格化学的协同作用，加速了水收集MOFs的近距离发现。此外，本文阐明了MOFs的高产量、环保、可扩展的合成路径，以及以设备为中心的优化，以在现实世界的水收集场景中发挥MOFs的潜力。第一章提供了金属有机框架及其在水收集中潜力的一般介绍。作为新兴候选者，MOFs拥有众多优势，使其成为水收集的理想吸附剂。这些优势包括在多次吸收-释放循环中保持水容量，展示出在操作条件下令人印象深刻的水吸收能力，需要较低的再生温度，并展示出动态的水吸收属性。除了高度的结晶性和永久多孔性外，MOFs的可调节性还有助于为特定需求设计定制材料。这一章强调了网格设计在将MOFs确立为大气水收集的独特吸附剂类别中的作用。它还深入探讨了MOFs与水吸收相关的结构-功能关系，并讨论了为这一应用设计新型MOFs的原则。第二章深入探讨了为大规模和环保生产适用于水收集的MOFs量身定制的合成策略。虽然传统的MOF合成主要针对小规模实验室设置，但MOF技术在水收集方面的广泛应用需要克服可扩展性和生产力方面的挑战。本章弥合了实验室发现与工业应用之间的差距。它引入了一种绿色、稳健、高产量的MOFs合成协议，优先考虑成本效益和环境可持续性。在公斤级别合成了几种基于铝的MOFs，并通过详细的特性分析确认了它们保留的结晶性和水吸收能力。该章还阐明了优化MOFs绿色合成的关键参数，强调它们在水收集应用中未来的可扩展性。第三章将重点从吸附材料转移到设备优化。通过设计利用MOF-303的装置，介绍了在被动水收集方面的显著进展。这种装置以其效率和模块化而闻名，在真实世界条件下，尤其是在美国死亡谷国家公园的极端环境中，展示了其效能。该章强调了该设备在应对水资源短缺方面的潜力，并概述了几个提高其大气水收集效率的关键参数。第四章和第五章阐释了提高MOF水吸收特性的新策略。具体来说，第四章深入探讨了多变量方法，将单连接器MOF转变为多样的混合连接器MOF家族。由此产生的MOFs在操作湿度范围和再生温度方面获得了更广泛的调节能力。此外，所采用的合成方法既可扩展又环保。第五章提出了一种"连接臂"延长策略，通过延长MOF-303的连接臂，显著提高了其水收集能力，水吸收量增加了50%。这两个战略创新的例子突显了MOFs在水收集应用中的多功能性和潜力。第六章深入探讨了AI引导下的MOF合成的变革潜力，建议从传统研究范式转向为水收集量身定制新MOFs的创新方法论。本章提倡使用AI代理来减轻实验室繁重的工作，从而使研究人员能够专注于更复杂的方面，并提高效率。整合机器学习算法旨在减少人类在优化MOF合成条件时的偏见。具体来说，介绍了一套由七个ChatGPT-based代理组成的套件，展示了它们简化众多实验室活动的能力。AI与MOF合成的结合标志着在完善水收集MOFs方面的重要里程碑，这种全面的AI框架简化了合成过程，减少了人类偏见，并最大化了效率。第七章是本论文的结论章。在这一章中，探讨了MOFs在大气水收集未来发展的反思和见解。随着我们更深入地探索这一领域，完善我们的设计原则和优化策略，MOFs无疑将在确保所有人的水安全、可持续性和繁荣中发挥关键作用。.
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