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Nicholas W. Lundgren

Publications and source records attributed to Nicholas W. Lundgren.

3 recordsLinked to original sources

kALDo 2.0: Scalable Thermal Transport from First Principles and Machine Learning Potentials

We introduce kALDo2.0, an open-source Python package for computing vibrational, elastic, and thermal transport properties of solids from first principles and machine-learned interatomic potentials. Building on the anharmonic lattice dynamics (ALD) framework, kALDo2.0 provides efficient CPU and GPU-accelerated implementations of the Boltzmann transport equation (BTE) for crystals and the quasi-harmonic Green-Kubo (QHGK) method. QHGK extends thermal transport predictions beyond crystals to disordered materials, including glasses, alloys, and complex nanostructures. kALDo2.0 introduces native integration with modern machine-learned potentials (MLPs), enabling thermal transport workflows that combine the accuracy of first-principles methods with the scalability of classical force fields. It also features comprehensive support for temperature-dependent effective potentials workflows, flexible storage backends for large-scale calculations, and advanced quantification of anharmonicity. The software seamlessly interfaces with electronic structure codes (Quantum ESPRESSO, VASP), molecular dynamics packages (LAMMPS), and MLPs (ACE, NEP, MACE, MatterSim, Orb), enabling thermal transport studies from 0 K to finite temperatures. kALDo2.0 implements multiple BTE solution strategies and essential physical corrections, including isotopic scattering and non-analytical terms for polar materials. A modular Python architecture with lazy evaluation and multiple storage formats (ASCII, NumPy, HDF5) enables simulations of systems containing up to tens of thousands of atoms. This paper describes the theoretical framework, implementation details, software architecture, and validation examples demonstrating kALDo2.0's capabilities for studying complex materials, including halide perovskites with strong anharmonicity and polar oxides requiring long-range electrostatic corrections.

cond-mat.mtrl-sci

Mode Localization and Suppressed Heat Transport in Amorphous Alloys

Glasses usually represent the lower limit for the thermal conductivity of solids, but a fundamental understanding of lattice heat transport in amorphous materials can provide design rules to beat such a limit. Here we investigate the role of mass disorder in glasses by studying amorphous silicon-germanium alloy (a-Si$_{1-x}$Ge$_x$) over the full range of atomic concentration from $x=0$ to $x=1$, using molecular dynamics and the quasi-harmonic Green-Kubo lattice dynamics formalism. We find that the thermal conductivity of a-Si$_{1-x}$Ge$_x$ as a function of $x$ exhibits a smoother U-shape than in crystalline mass-disordered alloys. The main contribution to the initial drop of thermal conductivity at low Ge concentration stems from the localization of otherwise extended modes that make up the lowest 8\% of the population by frequency. Contributions from intermediate frequency modes are decreased more gradually with increasing Ge to reach a broad minimum thermal conductivity between concentrations of Ge from $x=0.25$ to $0.75$.

cond-mat.mtrl-sci

Efficient Anharmonic Lattice Dynamics Calculations of Thermal Transport in Crystalline and Disordered Solids

Understanding heat transport in semiconductors and insulators is of fundamental importance because of its technological impact in electronics and renewable energy harvesting and conversion. Anharmonic Lattice Dynamics provides a powerful framework for the description of heat transport at the nanoscale. One of the advantages of this method is that it naturally includes quantum effects due to atoms vibrations, which are needed to compute the thermal properties of semiconductors widely used in nanotechnology, like silicon and carbon, even at room temperature. While the heat transport picture substantially differs between amorphous and crystalline semiconductors from a microscopic standpoint, a unified approach to simulate both crystals and glasses has been devised. Here we introduce a unified workflow, which implements both the Boltzmann Transport equation (BTE) and the Quasi Harmonic Green-Kubo (QHGK) methods. We discuss how the theory can be optimized to exploit modern parallel architectures, and how it is implemented in $κALDo$: a versatile and scalable open-source software to compute phonon transport in solids. This approach is applied to crystalline and partially disordered silicon-based systems, including bulk silicon and clathrates, and on silicon-germanium alloy clathrates with largely reduced thermal conductivity.

cond-mat.mtrl-sci