Development and validation of a computational approach to predicting the synthesis of inorganic materials

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 159-191).The concept of computational materials design envisions the identification of chemistries and structures with desirable properties through first-principles calculations, and the downselection of these candidates to those experimentally accessible using available synthesis methods. While first-principles property screening has become routine, the present lack of a robust method for the identification of synthetically accessible materials is an obstacle to true materials design. In this thesis, I develop a general approach for evaluating synthesizeability, and where possible, identifying synthesis routes towards the realization of target materials. This approach is based on a quasi- thermodynamic analysis of synthesis methods, relying on the assumption that phase selection is guided by transient thermodynamic stability under the conditions relevant to phase formation. By selecting the thermodynamic handles relevant to a growth procedure and evaluating the evolution of thermodynamic boundary conditions throughout the reaction, I identify potential metastable end-products as the set of ground state phases stabilized at various stages of the synthesis. To validate this approach, I derive the quasi-thermodynamic influence of adsorption-controlled finite- size stability and bulk off-stoichiometry on phase selection in the aqueous synthesis of polymorphic FeS2 and MnO2 systems, rationalizing the results of a range of synthesis experiments. To enable this analysis, I develop and benchmark the methodology necessary for the reliable first-principles evaluation of structure-sensitive bulk and interfacial stability in aqueous media. Finally, I describe a manganese oxide oxygen evolution catalyst, whose high activity is controlled by metastable, tetrahedrally- coordinated Mn3+ ions as an example of materials functionality enabled by structural metastability. The framework for the first-principles analysis of synthesis proposed and validated in this thesis lays the groundwork for the development of computational synthesis prediction and holds the potential to greatly accelerate the design and realization of new functional materials.by Daniil A. Kitchaev.Ph. D

Phase behavior and superprotonic conductivity in the Cs_(1-x)Rb_xH_2PO_4 and Cs_(1-x)K_xH_2PO_4 systems

The solid acid compound CsH_2PO_4 (CDP) adopts a cubic structure of high conductivity above 228 °C, rendering it attractive as a fuel cell electrolyte for intermediate temperature operation. This superprotonic phase is stable from the phase transition temperature, T_s, to the dehydration temperature, T_d, where the latter depends on water vapor pressure (e.g. T_d = 290 °C at p_(H_2O) = 0.8 atm). In this work we examine the possibility of modifying these temperatures and thereby, amongst other characteristics, fuel cell operating conditions by introduction of Rb and K as substituents for Cs in CDP. The phase behavior of the Cs_(1−x)Rb_xH_2PO_4 and Cs_(1−x)K_xH_2PO_4 pseudo-binary systems are determined by in situ X-ray diffraction (XRD) and thermal analysis. It is found that RbH_2PO_4 (RDP) and CDP are entirely miscible both below and above the transition to the cubic phase. With increasing Rb concentration, T_s increases and T_d decreases. In contrast, K has limited solubility in CDP, with a 27 at.% solubility limit in the cubic phase, and both T_s and T_d decrease with K content. The eutectoid temperature in the Cs_(1−x)K_xH_2PO_4 system is 208 ± 2 °C and the K solubility decreases sharply below this temperature. In both systems, conductivity decreases monotonically with increasing substituent concentration. Furthermore, even after normalization for cation size, the impact of K is greater than that of Rb, suggesting local disruptions to the proton migration pathway, beyond global changes in unit cell volume. Although this investigation shows unmodified CDP to remain the optimal fuel cell electrolyte material, the study provides a possible framework for elucidating proton transport mechanisms in superprotonic conductors

Finding and proving the exact ground state of a generalized Ising model by convex optimization and MAX-SAT

This paper was supported primarily by the US Department of Energy (DOE) under Contract No. DE-FG02-96ER45571. In addition, some of the test cases for ground states were supported by the Office of Naval Research under contract N00014-14-1-0444.Lattice models, also known as generalized Ising models or cluster expansions, are widely used in many areas of science and are routinely applied to the study of alloy thermodynamics, solid-solid phase transitions, magnetic and thermal properties of solids, fluid mechanics, and others. However, the problem of finding and proving the global ground state of a lattice model, which is essential for all of the aforementioned applications, has remained unresolved for relatively complex practical systems, with only a limited number of results for highly simplified systems known. In this paper, we present a practical and general algorithm that provides a provable periodically constrained ground state of a complex lattice model up to a given unit cell size and in many cases is able to prove global optimality over all other choices of unit cell. We transform the infinite-discrete-optimization problem into a pair of combinatorial optimization (MAX-SAT) and nonsmooth convex optimization (MAX-MIN) problems, which provide upper and lower bounds on the ground state energy, respectively. By systematically converging these bounds to each other, we may find and prove the exact ground state of realistic Hamiltonians whose exact solutions are difficult, if not impossible, to obtain via traditional methods. Considering that currently such practical Hamiltonians are solved using simulated annealing and genetic algorithms that are often unable to find the true global energy minimum and inherently cannot prove the optimality of their result, our paper opens the door to resolving longstanding uncertainties in lattice models of physical phenomena. An implementation of the algorithm is available at https://github.com/dkitch/maxsat-isingPublisher PDFPeer reviewe

Hidden structural and chemical order controls lithium transport in cation-disordered oxides for rechargeable batteries

This work was supported by the Robert Bosch Corporation, Umicore Specialty Oxides and Chemicals, and the Assistant Secretary for Energy Efficiency and Renewable Energy, Vehicle Technologies Office of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 under the Advanced Battery Materials Research (BMR) Program. The research conducted at the NOMAD Beamline at ORNL’s Spallation Neutron Source was sponsored by the Scientific User Facilities Division, Office of Basic Sciences, U.S. Department of Energy. Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The computational analysis was performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory, as well computational resources provided by Extreme Science and Engineering Discovery Environment (XSEDE), which was supported by the National Science Foundation grant number ACI-1053575.Structure plays a vital role in determining materials properties. In lithium ion cathode materials, the crystal structure defines the dimensionality and connectivity of interstitial sites, thus determining lithium ion diffusion kinetics. In most conventional cathode materials that are well-ordered, the average structure as seen in diffraction dictates the lithium ion diffusion pathways. Here, we show that this is not the case in a class of recently discovered high-capacity lithium-excess rocksalts. An average structure picture is no longer satisfactory to understand the performance of such disordered materials. Cation short-range order, hidden in diffraction, is not only ubiquitous in these long-range disordered materials, but fully controls the local and macroscopic environments for lithium ion transport. Our discovery identifies a crucial property that has previously been overlooked and provides guidelines for designing and engineering cation-disordered cathode materials.Publisher PDFPeer reviewe