arXiv subjects

Eric Toberer

Publications and source records attributed to Eric Toberer.

7 recordsLinked to original sources

arXiv2025

Human-in-the-Loop and AI: Crowdsourcing Metadata Vocabulary for Materials Science

Metadata vocabularies are essential for advancing FAIR and FARR data principles, but their development constrained by limited human resources and inconsistent standardization practices. This paper introduces MatSci-YAMZ, a platform that integrates artificial intelligence (AI) and human-in-the-loop (HILT), including crowdsourcing, to support metadata vocabulary development. The paper reports on a proof-of-concept use case evaluating the AI-HILT model in materials science, a highly interdisciplinary domain Six (6) participants affiliated with the NSF Institute for Data-Driven Dynamical Design (ID4) engaged with the MatSci-YAMZ plaform over several weeks, contributing term definitions and providing examples to prompt the AI-definitions refinement. Nineteen (19) AI-generated definitions were successfully created, with iterative feedback loops demonstrating the feasibility of AI-HILT refinement. Findings confirm the feasibility AI-HILT model highlighting 1) a successful proof of concept, 2) alignment with FAIR and open-science principles, 3) a research protocol to guide future studies, and 4) the potential for scalability across domains. Overall, MatSci-YAMZ's underlying model has the capacity to enhance semantic transparency and reduce time required for consensus building and metadata vocabulary development.

cs.AI↗

arXiv2025

Towards MatCore: A Unified Metadata Standard for Materials Science

The materials science community seeks to support the FAIR principles for computational simulation research. The MatCore Project was recently launched to address this need, with the goal of developing an overall metadata framework and accompanying guidelines. This paper reports on the MatCore goals and overall progress. Historical background context is provided, including a review of the principles underlying successful core metadata standards. The paper also presents selected MatCore examples and discusses future plans.

cond-mat.mtrl-sci↗

arXiv2024

Probabilistic Prediction of Material Stability: Integrating Convex Hulls into Active Learning

Active learning is a valuable tool for efficiently exploring complex spaces, finding a variety of uses in materials science. However, the determination of convex hulls for phase diagrams does not neatly fit into traditional active learning approaches due to their global nature. Specifically, the thermodynamic stability of a material is not simply a function of its own energy, but rather requires energetic information from all other competing compositions and phases. Here we present Convex hull-aware Active Learning (CAL), a novel Bayesian algorithm that chooses experiments to minimize the uncertainty in the convex hull. CAL prioritizes compositions that are close to or on the hull, leaving significant uncertainty in other compositions that are quickly determined to be irrelevant to the convex hull. The convex hull can thus be predicted with significantly fewer observations than approaches that focus solely on energy. Intrinsic to this Bayesian approach is uncertainty quantification in both the convex hull and all subsequent predictions (e.g., stability and chemical potential). By providing increased search efficiency and uncertainty quantification, CAL can be readily incorporated into the emerging paradigm of uncertainty-based workflows for thermodynamic prediction.

cond-mat.mtrl-sci↗

arXiv2023

Mechanistically-guided materials chemistry: synthesis of new ternary nitrides, CaZrN$_2$ and CaHfN$_2$

Recent computational studies have predicted many new ternary nitrides, revealing synthetic opportunities in this underexplored phase space. However, synthesizing new ternary nitrides is difficult, in part because intermediate and product phases often have high cohesive energies that inhibit diffusion. Here, we report the synthesis of two new phases, calcium zirconium nitride (CaZrN$_2$) and calcium hafnium nitride (CaHfN$_2$), by solid state metathesis reactions between Ca$_3$N$_2$ and $M$Cl$_4$ ($M$ = Zr, Hf). Although the reaction nominally proceeds to the target phases in a 1:1 ratio of the precursors via Ca$_3$N$_2$ + $M$Cl$_4$ $\rightarrow$ Ca$M$N$_2$ + 2 CaCl$_2$, reactions prepared this way result in Ca-poor materials (Ca$_xM_{2-x}$N$_2$, $x<1$). A small excess of Ca$_3$N$_2$ (ca. 20 mol\%) is needed to yield stoichiometric Ca$M$N$_2$, as confirmed by high-resolution synchrotron powder X-ray diffraction. In situ synchrotron X-ray diffraction studies reveal that nominally stoichiometric reactions produce Zr$^{3+}$ intermediates early in the reaction pathway, and the excess Ca$_3$N$_2$ is needed to reoxidize Zr$^{3+}$ intermediates back to the Zr$^{4+}$ oxidation state of CaZrN$_2$. Analysis of computationally-derived chemical potential diagrams rationalizes this synthetic approach and its contrast from the synthesis of MgZrN$_2$. These findings additionally highlight the utility of in situ diffraction studies and computational thermochemistry to provide mechanistic guidance for synthesis.

cond-mat.mtrl-sci↗

arXiv2023

Occupational Disorder as the Origin of Flattening of the Acoustic Phonon Branches in the Clathrate Ba$_{8}$Ga$_{16}$Ge$_{30}$

In the search for high-performance thermoelectrics, materials such as clathrates have drawn attention due to having both glass-like low phonon thermal conductivity and crystal-like high electrical conductivity. Ba$_{8}$Ga$_{16}$Ge$_{30}$ (BGG) has a loosely bound guest Ba atom trapped inside rigid Ga/Ge cage structures. Avoided crossings between acoustic phonons and the flat guest atom branches have been proposed to be the source of the low lattice thermal conductivity of BGG. Ga/Ge site disorder with Ga and Ge exchanging places in different unit cells has also been reported. We used time-of-flight neutron scattering to measure the complete phonon spectrum in a large single crystal of BGG and compared these results with predictions of density functional theory to elucidate the effect of the disorder on heat-carrying phonons. Experimental results agreed much better with the calculation assuming the disorder than with the calculation assuming the ordered configuration. Although atomic masses of Ga and Ge are nearly identical, we found that disorder strongly reduces phonon group velocities, which significantly reduces thermal conductivity. Our work points at a new path towards optimizing thermoelectrics.

cond-mat.mtrl-sci↗

arXiv2022

The Mixing Thermodynamics and Local Structure of High-entropy Alloys from Randomly Sampled Ordered Configurations

A general method is presented for modeling high entropy alloys as ensembles of randomly sampled, ordered configurations on a given lattice. Statistical mechanics is applied post hoc to derive the ensemble properties as a function of composition and temperature, including the free energy of mixing and local structure. Random sampling is employed to address the high computational costs needed to model alloys with a large number of components. Doing so also provides rigorous convergence criteria, including the quantification of noise due to random sampling, and an estimation of the number of additional samples required to lower this noise to the needed/desired levels. This method is well-suited for a variety of cases: i) high entropy alloys, where standard lattice models are costly; ii) "medium" entropy alloys, where both the entropy and enthalpy play significant roles; and iii) alloys with residual short-range order. Binary to 5-component alloys of the group-IV chalcogenides are used as case examples, for which the predicted miscibility shows excellent agreement with experiment.

cond-mat.mtrl-sci↗

arXiv2018

Ionic vs. van der Waals Layered Materials: Identification and Comparison of Elastic Anisotropy

In this work, we expand the set of known layered compounds to include ionic layered materials, which are well known for superconducting, thermoelectric, and battery applications. Focusing on known ternary compounds from the ICSD, we screen for ionic layered structures by expanding upon our previously developed algorithm for identification of van der Waals (vdW) layered structures, thus identifying over 1,500 ionic layered compounds. Since vdW layered structures can be chemically mutated to form ionic layered structures, we have developed a methodology to structurally link binary vdW to ternary ionic layered materials. We perform an in-depth analysis of similarities and differences between these two classes of layered systems and assess the interplay between layer geometry and bond strength with a study of the elastic anisotropy. We observe a rich variety of anisotropic behavior in which the layering direction alone is not a simple predictor of elastic anisotropy. Our results enable discovery of new layered materials through intercalation or de- intercalation of vdW or ionic layered systems, respectively, as well as lay the groundwork for studies of anisotropic transport phenomena such as sound propagation or lattice thermal conductivity.

cond-mat.mtrl-sci↗