14 papers · ranked by Valyu relevance
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Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
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Artificial intelligence, represented by large language models (LLMs), has demonstrated tremendous capabilities in natural language recognition and extraction. To further evaluate the performance of various LLMs in extracting information from academic papers, this study explores the application of LLMs in reticular…
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While virtual libraries of synthetically accessible compounds have exploded in size to many billions, our capacity to extract valuable drug leads from these vast databases remains limited by computational resources. To overcome this, we developed SLICE SMARTS and Logic In ChEmistry), a powerful new tool designed for…
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In the real world, many reversal phenomena occur—for example, cases in which a statement once regarded as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phenomena as a logical system. It inverts the truth and falsity of propositions through contextual…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…
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In philosophy and science, a first principle is a basic proposition or assumption that cannot be deduced from any other proposition or assumption. Ancient Greek philosophy Aristotle defined the first principle as “the first basis from which a thing is known.” First principles thinking (or reasoning from first…
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The scarcity and expense of fatigue data limits optimal design of components and constrains companies to a few well qualified materials when safety-critical applications are concerned. This research investigates different strategies to improve extraction of structured information from unstructured scientific…
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We introduce a novel workflow integrating reasoning-capable language models with specialized chemical analysis tools to enhance molecular structure determination using nuclear magnetic resonance spectroscopy. Generally, structure elucidation involves generating candidate molecular structures, comparing their predicted…
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Nuclear Magnetic Resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful evaluation of multiple features of spectral data. This study explores the capabilities of large language models (LLMs) for…
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The Socratic method, grounded in iterative questioning and critical dialogue, offers a compelling framework for leveraging large language models (LLMs) to advance scientific reasoning and discovery in chemistry and materials science. In this paper, we explore how Socratic principles can be integrated into prompt…
Guanqi Qiu
Chemists have long utilized theories and models to rationalize empirical data and predict outcomes in new chemical systems. Unexpected reactivities often present themselves as exceptions or paradoxes, highlighting gaps in our current understanding and the limitations of (then) existing models. Rather than something to…
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The exponentially growing body of scientific literature has made manual synthesis and hypothesis generation increasingly impractical, introducing an essential bottleneck in the scientific discovery pipeline. While large language models (LLMs) have unprecedented capability to process and summarize textual knowledge…
Charles T. Cox Jr., Mitch Rivers, Thomas Locascio, Benjamin Yacht + 3 more
This communication extends on findings previously reported in which students were asked to construct Reaction Coordinate Diagrams (RCDs) de novo. Instead of asking students to construct RCDs, this study explores students’ understanding of kinetics and thermodynamics when provided with mechanisms for the Aldol and…
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This paper introduces Post-Inspection Analysis (PIA), a concept for understanding and reverse engineering balanced equations of similar reactions. Here we explore the idea that balanced equations contain useable information observed by grouping and analysing similar equations, allowing us to uncover observations that…