DuBose Jeffrey T, Scott Soren B, Moss Benjamin
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States.
Department of Chemistry, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark.
ACS Phys Chem Au. 2024 Apr 1;4(4):292-301. doi: 10.1021/acsphyschemau.3c00078. eCollection 2024 Jul 24.
Proficiency in physical chemistry requires a broad skill set. Successful trainees often receive mentoring from senior colleagues (research advisors, postdocs, etc.). Mentoring introduces trainees to experimental design, instrumental setup, and complex data interpretation. In lab settings, trainees typically learn by customizing experimental setups, and developing new ways of analyzing data. Learning alongside experts strengthens these fundamentals, and places a focus on the clear communication of research problems. However, this level of input is not scalable, nor can it easily be shared with all researchers or students, particularly those that face socioeconomic barriers to accessing mentoring. New approaches to training will therefore progress the field of physical chemistry. Technology is disrupting and democratising scientific education and research. The emergence of free online courses and video resources enables students to learn in a style that suits them. Higher degrees of automation remove cumbersome and sometimes arbitrary technical barriers to learning new techniques, allowing one to collect high quality data quickly. Open sourcing of data and analysis tools has increased transparency, lowered barriers to access, and accelerated scientific dissemination. However, these advances also can lead to "black box" approaches to acquiring and analyzing data, where convenience replaces understanding and errors and misrepresentations become more common. The risk is a breakdown in education: . Our vision of the future of physical chemistry is built around democratized learning, where deep technical and analytical expertise from physical chemists is made freely available. Advancements in technical education through expert-generated educational resources and AI-based tools will enrich physical chemistry education. A holistic approach to education will prepare the physical chemists of 2050 to adapt to rapidly advancing technological tools, which accelerate the pace of research. Technical education will be enhanced by accessible open-source instrumentation and analysis procedures, which will provide instruments and analysis scripts specifically designed for education. High quality, comparable data from standardized open-source instruments will feed into accessible databases and analysis projects, providing others the opportunity to store and analyze both failed and successful experiments. The coupling of open-source education, hardware, and analysis will democratize physical chemistry while addressing risks associated with "black box" approaches.
精通物理化学需要广泛的技能。成功的学员通常会得到资深同事(研究导师、博士后等)的指导。指导会引导学员学习实验设计、仪器设置和复杂的数据解读。在实验室环境中,学员通常通过定制实验设置和开发新的数据分析法来学习。与专家一起学习能强化这些基础知识,并注重研究问题的清晰沟通。然而,这种投入水平无法扩展,也不容易与所有研究人员或学生分享,尤其是那些在获得指导方面面临社会经济障碍的人。因此,新的培训方法将推动物理化学领域的发展。技术正在颠覆科学教育和研究,并使其民主化。免费在线课程和视频资源的出现使学生能够以适合自己的方式学习。更高程度的自动化消除了学习新技术时繁琐且有时随意的技术障碍,使人们能够快速收集高质量数据。数据和分析工具的开源提高了透明度,降低了获取障碍,并加速了科学传播。然而,这些进步也可能导致获取和分析数据采用“黑箱”方法,即便利取代了理解,错误和错误表述变得更加常见。风险在于教育的崩溃。我们对物理化学未来的愿景围绕着民主化学习构建,物理化学家的深厚技术和分析专业知识将免费提供。通过专家生成的教育资源和基于人工智能的工具推进技术教育将丰富物理化学教育。全面的教育方法将使2050年的物理化学家能够适应迅速发展的技术工具,从而加快研究步伐。可访问的开源仪器和分析程序将加强技术教育,这些程序将提供专门为教育设计的仪器和分析脚本。来自标准化开源仪器的高质量、可比数据将输入可访问的数据库和分析项目,为其他人提供存储和分析失败及成功实验的机会。开源教育、硬件和分析的结合将使物理化学民主化,同时应对与“黑箱”方法相关的风险。