Structure, essence and existence in chemistry

Hendry, Robin Findlay

doi:10.1111/rati.12387

Cited by 2 publications

(1 citation statement)

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“…So, it is worth asking what makes the periodic table work. A recent strand of research in philosophy of science emphasizes that across much of physics, chemistry, and materials science, the central principle of classification is the structure–property paradigm . ,,− That is, how are structural features of the microscale makeup of a substance, compound, or material systematically related to macroscopic or observable properties? The structure–property paradigm is relatively well-recognized as a conceptual framework for guiding research across many areas of chemistry, especially materials and nanochemistry.…”

Section: The Philosophical Roots Of Chemical Ontologies: Classifying ...mentioning

confidence: 99%

Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies

Duke,

McCoy,

Risko

et al. 2024

J. Am. Chem. Soc.

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Chemistry is experiencing a paradigm shift in the way it interacts with data. So-called "big data" are collected and used at unprecedented scales with the idea that algorithms can be designed to aid in chemical discovery. As data-enabled practices become ever more ubiquitous, chemists must consider the organization and curation of their data, especially as it is presented to both humans and increasingly intelligent algorithms. One of the most promising organizational schemes for big data is a construct termed an ontology. In data science, ontologies are systems that represent relations among objects and properties in a domain of discourse. As chemistry encounters larger and larger data sets, the ontologies that support chemical research will likewise increase in complexity, and the future of chemistry will be shaped by the choices made in developing big data chemical ontologies. How such ontologies will work should therefore be a subject of significant attention in the chemical community. Now is the time for chemists to ask questions about ontology design and use: How should chemical data be organized? What can be reasonably expected from an organizational structure? Is a universal ontology tenable? As some of these questions may be new to chemists, we recommend an interdisciplinary approach that draws on the long history of philosophers of science asking questions about the organization of scientific concepts, constructs, models, and theories. This Perspective presents insights from these long-standing studies and initiates new conversations between chemists and philosophers.■ CHEMISTRY'S BIG DATA ERA As with most sciences in the 21st century, chemistry is witnessing a seismic shift in data collection, storage, and use. The collection of large volumes of data (so-called "big data") for the purpose of using computer algorithms to aid in chemical discovery is becoming commonplace, and many experiments produce more raw data than any one scientist could review in a lifetime. Moreover, federal funding agencies now require extensive data management plans and that data be made open under FAIR (f̲ indable, a̲ ccessible, i̲ nteroperable, and r̲ eusable) 1 data principles. In the United States, the National Science Foundation, National Institutes of Health, and Department of Energy among others have begun requiring data management plans for proposal applications, 2−4 while similar efforts exist globally to promote robust and accessible research data management. 5,6 Along with funding agencies, researchers across the globe are pushing for accessible, usable, and reliably reproducible data in chemistry. 7−9 Many argue that this new era of data will transform modern chemistry from an Edisonian model of trial-and-error to data-driven and machine-enabled design through artificial intelligence (AI). 10,11 Chemical Data: Historical Background. Although the modern era of big data is still incipient, data hold an integral role in the history of chemistry (Figure 1). 12−14 Chemists have long prioritized documenting and sharing thei...

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Section: The Philosophical Roots Of Chemical Ontologies: Classifying ...mentioning

confidence: 99%

Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies

Duke,

McCoy,

Risko

et al. 2024

J. Am. Chem. Soc.

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Mechanisms in Chemistry

Hendry

2023

History, Philosophy and Theory of the Life Sciences

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Mechanisms are the how of chemical reactions. Substances are individuated by their structures at the molecular scale, so a chemical reaction is just the transformation of reagent structures into product structures. Explaining a chemical reaction must therefore involve different hypotheses about how this might happen: proposing, investigating and sometimes eliminating different possible pathways from reagents to products. One distinctive aspect of mechanisms in chemistry is that they are broken down into a few basic kinds of step involving the breaking and making of bonds between atoms. This is necessary for chemical kinetics, the study of how fast reactions happen, and what affects it. It draws on G.N. Lewis’ identification of the chemical bond as involving shared electrons, which from the 1920s achieved the commensuration of chemistry and physics. The breaking or making of a bond just is the transfer of electrons, so a chemical bond on one side of an equation might be balanced on the other side by the appearance of a corresponding quantity of excess charge. A bond is understood to have been exchanged for a pair of electrons. Since reaction mechanisms rely on identities, doesn’t the establishment of a reaction mechanism explain away the chemical phenomena, showing that they are no more than the movement of charges and masses? In one sense yes: these mechanisms seem to involve a conserved-quantity conception of causation. But in another sense no: the ‘lower-level’ entities can do what they do only when embedded in higher-level organisation or structure. There need be no threat of reduction.

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Structure, essence and existence in chemistry

Cited by 2 publications

References 52 publications

Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies

Promises and Perils of Big Data: Philosophical Constraints on Chemical Ontologies

Mechanisms in Chemistry

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