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«SURFACES, SCALES, AND SYNTHESIS SCIENTIFIC REASONING AT THE NANOSCALE by Julia R. Bursten B.A., Philosophy, Rice University, 2008 M.A., Philosophy, ...»

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SURFACES, SCALES, AND SYNTHESIS

SCIENTIFIC REASONING AT THE NANOSCALE

by

Julia R. Bursten

B.A., Philosophy, Rice University, 2008

M.A., Philosophy, University of Pittsburgh, 2010

Submitted to the Graduate Faculty of

the Kenneth P. Dietrich School of Arts and Sciences in partial

fulfillment

of the requirements for the degree of

Doctor of Philosophy

University of Pittsburgh

UNIVERSITY OF PITTSBURGH

KENNETH P. DIETRICH SCHOOL OF ARTS AND SCIENCES

This dissertation was presented by Julia R. Bursten It was defended on April 9, 2015 and approved by Robert Batterman, University of Pittsburgh, Philosophy Jill Millstone, University of Pittsburgh, Chemistry Sandra Mitchell, University of Pittsburgh, HPS John Norton, University of Pittsburgh, HPS Mark Wilson, University of Pittsburgh, Philosophy James Woodward, University of Pittsburgh, HPS Dissertation Director: Robert Batterman, University of Pittsburgh, Philosophy ii Copyright c by Julia R. Bursten iii ABSTRACT

SURFACES, SCALES, AND SYNTHESIS

SCIENTIFIC REASONING AT THE NANOSCALE

Julia R. Bursten, PhD University of Pittsburgh, 2015 Philosophers interested in scientific methodology have focused largely on physics, biology,

and cognitive science. They have paid considerably less attention to sciences such as chemistry and nanoscience, where not only are the subjects distinct, but the very aims differ:

chemistry and nanoscience center around synthesis. Methods associated with synthesis do not fit well with description, explanation, and prediction that so dominate aims in philosophers paradigm sciences. In order to synthesize a substance or material, scientists need different kinds of information than they need to predict, explain, or describe. Consequently, they need different kinds of models and theories. Specifically, chemists need additional models of how reactions will proceed. In practice, this means chemists must model surface structure and behavior, because reactions occur on the surfaces of materials.

Physics, and by extension much of philosophy of science, ignores the structure and behavior of surfaces, modeling surfaces only as boundary conditions with virtually no influence on material behavior. Such boundary conditions are not seen as part of the physical laws that govern material behavior, so little consideration has been given to their roles in improving scientists understanding of materials and aiding synthesis. But especially for theories that are used in synthesis, such neglect can lead to catastrophic modeling failures. In fact, as one moves down toward the nanoscale, the very concept of a material surface changes, with the consequence that nanomaterials behave differently than macroscopic materials made up of the same ele- ments. They conduct electricity differently, they appear differently colored, iv and they can play different roles in chemical reactions. This dissertation develops new philosophical tools to deal with these changes and give an account of theory and model use in the synthetic sciences. Particularly, it addresses the question of how models of materials at the nanoscale fit together with models of those very same materials at scales many orders of magnitude larger. To answer this and related questions, strict attention needs to be paid to the ways boundaries, surfaces, concepts, models, and even laws change as scales change.

Keywords: philosophy of science, philosophy of physics, philosophy of chemistry, explanation, nanoscience, synthesis, models, theories, kinds.

–  –  –

Nanoscience research and development has the potential to reshape human understanding of physical systems and the technologies they produce. Research into nanoscale systems is currently one of the fastest-growing areas of scientific interest, and nano is finding niches across all the mathematical and natural sciences—in solid-state physics (e.g. Atwater 2007), synthetic chemistry (e.g. Klabunde and Richards 2001), biological technologies (e.g. Nussinov and Alem´n 2006), diagnostic (e.g. West and Halas 2003) and therapeutic (e.g. An and a Hyeon 2009) medicine, and more.

Small is getting huge, and the rapid growth of the field has focused almost exclusively on experiments and application. Most research projects in nanoscience are centered around the development of particular material systems, methods for production of those systems, and applications of those systems toward technologies that could change the way energy and information is stored and deployed. Consequently, nanoscience researchers have not so far devoted much time to creating a systematic understanding of the conceptual and theoretical foundations of nanoscale systems.

What this means is that key questions about the relation between scientific concepts deployed at macroscopic and molecular scales and the nanoscale analogues of those concepts have yet to be answered. Models and theories at the nanoscale are currently scattershot;

they have been developed semi-empirically for use in prediction of the behaviors of individual systems, and many models make assumptions about the target systems that conflict with either assumptions made by other models or with known facts about the nature of the target system itself. For instance, many theoretical descriptions of nanosynthesis, cobbled together from conflicting models, describe the synthesized material as sometimes continuous, sometimes discrete; sometimes symmetrical and defect-free, sometimes non-symmetric and ix defect-ridden.





Traditional philosophical accounts of modeling and of theory structure suggest this blooming, buzzing confusion of inconsistent models and conflicting assumptions indicates poor theory design. Nonetheless, models and theories of nanoscale systems are often quite successful at providing nanoscience researchers with the information they seek about a target system.

This dissertation aims to justify this success and to suggest strategies for future success, both in the case of nanoscience and in other synthetic sciences.

I begin from the premise that the central activity of nanoscience research, and of chemical research more generally, is synthesis, the development of substances and materials from other substances and materials. Synthesis provides a different aim for scientific theory and practice—namely, making—than standard philosophical accounts have thus far acknowledged. Most standard philosophical accounts teach that the aim of scientific theories, insofar as they have an aim, is either description of natural systems, or prediction of future behaviors of natural systems, or explanation of observed correlations or causal connections between those behaviors, or some combination thereof. Synthesis of a material or substance is neither describing nor predicting nor explaining: it is making, and making is a different kind of scientific activity. There is no a priori reason to expect that the structure of scientific theories aimed at describing or predicting or explaining should be the same as the structure of scientific theories aimed at making.

Nor is there any a priori reason to expect that theories aimed at making should all display a single structure. So rather than generalizing from a survey of such theories—borrowing from, e.g., mechanical engineering, biomedicine, informatics, and applied economics, among others—I study nanoscience in detail. Uncovering the character of theories in nanoscience thereby serves as a groundwork for future work on the structure and use of theories in other synthetic sciences. Nanoscience makes a particularly apt base case because it also contains a number of pressing, endemic philosophical puzzles, whose resolution could affect the development of the field itself. Among those, most prominent are methods for gaining control over surface structure and behavior through synthesis techniques, but other considerations also arise.

From this focused study of nanoscience, I draw a number of philosophical morals about x the structure of scientific reasoning in synthetic science in general and in nanoscience in particular. I demonstrate that central debates in philosophy of science, including the nature(s) of explanation and understanding, the structure(s) of theories and the referents of scientific terms, have all grown up on the premise that the central activity of science is to describe the natural world. With the rejection of that premise comes a host of new opportunities for philosophical reflection on scientific reasoning.

Philosophers interested in scientific methodology have focused largely on physics, biology, and cognitive science. They have paid considerably less attention to sciences such as chemistry and nanoscience, where not only are the subjects distinct, but the very aims differ: chemistry and nanoscience center around synthesis. Reasoning strategies associated with synthesis do not fit well with description, explanation, and prediction that so dominate aims in philosophers’ paradigm sciences; in order to synthesize a substance or material, scientists need different kinds of information than they need to predict, explain, or describe.

Consequently, they need different kinds of models and theories. Specifically, chemists need additional models of how reactions will proceed.

In practice, this means chemists must model surface structure and behavior, because reactions occur on the surfaces of materials. Much of physics, and by extension much of philosophy of science, ignores the structure and behavior of surfaces, modeling surfaces only as boundaries on a system with virtually no influence on material behavior. Such boundaries are not seen as part of the physical laws that govern material behavior, so little consideration has been given to their roles in improving scientists’ understanding of materials and aiding synthesis. But especially for theories that are used in synthesis, such neglect can lead to catastrophic modeling failures.

In fact, as one moves down toward the nanoscale, the very concept of a material surface changes, with the consequence that nanomaterials behave differently than macroscopic materials made up of the same elements. They conduct electricity differently, they appear differently colored, and they can play different roles in chemical reactions. These differences are the result of their sheer smallness: when materials shrink down to the nanoscale, atoms in a material stand in different relations to one another than in macroscopic materials. A larger proportion of atoms lie on the surface of nanomaterials than macroscopic materials, xi and this difference is responsible for most of these scale-dependent changes in material behaviors. This dissertation develops new philosophical tools to deal with these changes and construct an account of theory and model use in the synthetic sciences. Particularly, it addresses the question of how models of materials at the nanoscale fit together with models of those very same materials at scales many orders of magnitude larger.

The size of the material, and the proportion of atoms on the surface of a material, are nothing like the laws and mechanisms that philosophers usually cite as explanantia. This difference in size is instead a difference in the role of a boundary condition, that is, an independently-specified parameter that constrains the behavior of a system. Boundary conditions are a type of modeling parameter usually associated with mathematical models containing differential equations. Traditional accounts of theories and models in philosophy of science have mostly ignored the role of boundary conditions in generating explanations, predictions, and descriptions of systems of scientific interest. Traditional accounts have also ignored the function of theories and models in synthetic scientific activities, such as the design and production of new substances and materials. This dissertation explains why these oversights are problematic for accounts of theories, models, explanations, and concepts in nanoscience and in the physical sciences more generally, and it constructs an alternative account of theories and models that rectifies these oversights.

Models of nanomaterials have developed by combining and adapting theories about macroscopic material behavior and theories about atomic and molecular behavior in response to empirical observation. For instance, some models of nanomaterials have evolved from continuum models of macroscopic materials. Continuum models ignore molecular structure, which makes them effective or phenomenological rather than “foundational,” and they model surfaces as infinitesimal boundary conditions. These effective models produce accurate predictions and useful explanations of the behavior of macroscopic materials while ignoring both the atomic constitution of matter and the structure and behavior of material surfaces.

Treating surfaces as boundary conditions is an effective strategy for macroscopic materials modeling because surfaces make up a small proportion of the material as a whole. However, when materials shrink down to the nanoscale, this is no longer the case, and continuum models of materials must be modified and supplemented with structural information about xii inter-atomic relations in the material. This challenge to traditional materials modeling strategies demonstrates that surface and other central concepts in materials modeling are scale-dependent; that is, their role in describing and constraining the behavior of materials changes as a function of scale.



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