二维材料的液相剥离及其在数据驱动未来的电化学应用

Panwad Chavalekvirat, Wisit Hirunpinyopas, Krittapong Deshsorn, Kulpavee Jitapunkul and Pawin Iamprasertkun*, 
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引用次数: 0

摘要

二维材料,尤其是过渡金属二掺杂物(TMDs)的电化学特性取决于其结构和化学特性。要实现大规模、高产能生产,确保质量和电化学适用性,以应用于储能、电催化和基于电位的离子筛分膜,这一点至关重要。成功的先决条件是深入了解合成过程,这也是材料合成与电化学性能之间的关键环节。本综述广泛研究了液相剥离技术,深入探讨了在保持 TMDs 电化学特性的同时优化其纳米片产量的潜在进步和策略。主要目的是汇编通过直接液相剥离提高 TMDs 纳米片产量的技术,同时考虑到溶剂、表面活性剂、离心和超声动态等参数。除了讨论剥离产率,综述还强调了这些参数对 TMD 纳米片结构和化学特性的潜在影响,突出了它们在电化学应用中的关键作用。随着研究方法的不断发展,这篇综述探讨了如何将机器学习和数据科学结合起来,作为了解各种关系和关键特性的工具。为了推进二维材料研究,包括优化石墨烯、MXenes 和 TMDs 的合成以促进电化学应用,本汇编为数据驱动技术指明了方向。通过连接实验和机器学习方法,它有望重塑电化学知识的格局,为学术界提供变革性的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Liquid Phase Exfoliation of 2D Materials and Its Electrochemical Applications in the Data-Driven Future

The electrochemical properties of 2D materials, particularly transition metal dichalcogenides (TMDs), hinge on their structural and chemical characteristics. To be practically viable, achieving large-scale, high-yield production is crucial, ensuring both quality and electrochemical suitability for applications in energy storage, electrocatalysis, and potential-based ionic sieving membranes. A prerequisite for success is a deep understanding of the synthesis process, forming a critical link between materials synthesis and electrochemical performance. This review extensively examines the liquid-phase exfoliation technique, providing insights into potential advancements and strategies to optimize the TMDs nanosheet yield while preserving their electrochemical attributes. The primary goal is to compile techniques for enhancing TMDs nanosheet yield through direct liquid-phase exfoliation, considering parameters like solvents, surfactants, centrifugation, and sonication dynamics. Beyond addressing the exfoliation yield, the review emphasizes the potential impact of these parameters on the structural and chemical properties of TMD nanosheets, highlighting their pivotal role in electrochemical applications. Acknowledging evolving research methodologies, the review explores integrating machine learning and data science as tools for understanding relationships and key characteristics. Envisioned to advance 2D material research, including the optimization of graphene, MXenes, and TMDs synthesis for electrochemical applications, this compilation charts a course toward data-driven techniques. By bridging experimental and machine learning approaches, it promises to reshape the landscape of knowledge in electrochemistry, offering a transformative resource for the academic community.

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来源期刊
Precision Chemistry
Precision Chemistry 精密化学技术-
CiteScore
0.80
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期刊介绍: Chemical research focused on precision enables more controllable predictable and accurate outcomes which in turn drive innovation in measurement science sustainable materials information materials personalized medicines energy environmental science and countless other fields requiring chemical insights.Precision Chemistry provides a unique and highly focused publishing venue for fundamental applied and interdisciplinary research aiming to achieve precision calculation design synthesis manipulation measurement and manufacturing. It is committed to bringing together researchers from across the chemical sciences and the related scientific areas to showcase original research and critical reviews of exceptional quality significance and interest to the broad chemistry and scientific community.
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