Showing 1–11 of 11 results for author: Habib, A

An Agentic Orchestration of Atomistic Simulations

Authors: Rahul Somasundaram, Adela Habib, Khanh Dang, Sachin Shivakumar, Ryley G. Hill, Golo Wimmer, Avanish Mishra, Aleksandra Pachalieva, Arthur Lui, Hari Viswanathan, Michael Grosskopf, Saryu Fensin, Russell Bent, Nathan DeBardeleben, Earl Lawrence

Abstract: Atomistic simulations are central to materials design, but their execution involves complex, multi-step workflows that require significant human expertise. Here, we present an agent-based system embedded within the URSA (Universal Research and Scientific Agent) framework that automates the design, execution, and validation of atomistic simulations, demonstrated using the Large-scale Atomic/Molecul… ▽ More Atomistic simulations are central to materials design, but their execution involves complex, multi-step workflows that require significant human expertise. Here, we present an agent-based system embedded within the URSA (Universal Research and Scientific Agent) framework that automates the design, execution, and validation of atomistic simulations, demonstrated using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) tool. Our system autonomously selects interatomic potentials, constructs and runs simulations, and performs iterative error recovery within a closed-loop workflow. We evaluate the scientific reliability of the agent by benchmarking its outputs against LAVA, a high-throughput toolkit for LAMMPS and the Vienna Ab initio Simulation Package (VASP) calculations. Our framework reduces manual intervention and trial-and-error, thereby improving the rigor, reproducibility, and scalability of atomistic modeling. △ Less

Submitted 11 June, 2026; originally announced July 2026.

Comments: 19 pages, 9 figures

Report number: LA-UR-26-24722

Magnetic-field dependence of spin-phonon relaxation and dephasing due to g-factor fluctuations from first principles

Authors: Joshua Quinton, Mayada Fadel, Junqing Xu, Adela Habib, Mani Chandra, Yuan Ping, Ravishankar Sundararaman

Abstract: The electron spin decay lifetime in materials can be characterized by relaxation (T1) and irreversible (T2) and reversible (T2*) decoherence processes. Their interplay leads to a complex dependence of spin relaxation times on the direction and magnitude of magnetic fields, relevant for spintronics and quantum information applications. Here, we use real-time first-principles density matrix dynamics… ▽ More The electron spin decay lifetime in materials can be characterized by relaxation (T1) and irreversible (T2) and reversible (T2*) decoherence processes. Their interplay leads to a complex dependence of spin relaxation times on the direction and magnitude of magnetic fields, relevant for spintronics and quantum information applications. Here, we use real-time first-principles density matrix dynamics simulations to directly simulate Hahn echo measurements, disentangle dephasing from decoherence, and predict T1, T2 and T2* spin lifetimes. We show that g-factor fluctuations lead to non-trivial magnetic field dependence of each of these lifetimes in inversion-symmetric crystals of CsPbBr3 and silicon, even when only intrinsic spin-phonon scattering is present. Most importantly, fluctuations in the off-diagonal components of the g-tensor lead to a strong magnetic field dependence of even the T1 lifetime in silicon. Our calculations elucidate the detailed role of anisotropic g-factors in determining the spin dynamics even in simple, low spin-orbit coupling materials such as silicon. △ Less

Submitted 5 March, 2025; v1 submitted 27 November, 2024; originally announced November 2024.

Comments: 9 pages, 5 figures

Journal ref: Phys. Rev. B 111, 115113 (2025)

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs

Authors: Adela Habib, Joshua Finkelstein, Anders M. N. Niklasson

Abstract: In recent years, a new kind of accelerated hardware has gained popularity in the Artificial Intelligence (AI) and Machine Learning (ML) communities which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI/ML hardware, to develop a mixed precision approac… ▽ More In recent years, a new kind of accelerated hardware has gained popularity in the Artificial Intelligence (AI) and Machine Learning (ML) communities which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI/ML hardware, to develop a mixed precision approach for computing a dense matrix factorization of the inverse overlap matrix in electronic structure theory, $S^{-1}$. This factorization of $S^{-1}$, written as $ZZ^T=S^{-1}$, is used to transform the general matrix eigenvalue problem into a standard matrix eigenvalue problem. Here we present a mixed precision iterative refinement algorithm where $Z$ is given recursively using matrix-matrix multiplications and can be computed with high performance on Tensor cores. To understand the performance and accuracy of Tensor cores, comparisons are made to GPU-only implementations in single and double precision. Additionally, we propose a non-parametric stopping criteria which is robust in the face of lower precision floating point operations. The algorithm is particularly useful when we have a good initial guess to $Z$, for example, from previous time steps in quantum-mechanical molecular dynamics simulations or from a previous iteration in a geometry optimization. △ Less

Submitted 29 April, 2024; originally announced April 2024.

Comments: 12 pages, 4 figures, 1 table and a few algorithms

Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles

Authors: Adela Habib, Nicholas Lubbers, Sergei Tretiak, Benjamin Nebgen

Abstract: Highly energetic electron-hole pairs (hot carriers) formed from plasmon decay in metallic nanostructures promise sustainable pathways for energy-harvesting devices. However, efficient collection before thermalization remains an obstacle for realization of their full energy generating potential. Addressing this challenge requires detailed understanding of physical processes from plasmon excitation… ▽ More Highly energetic electron-hole pairs (hot carriers) formed from plasmon decay in metallic nanostructures promise sustainable pathways for energy-harvesting devices. However, efficient collection before thermalization remains an obstacle for realization of their full energy generating potential. Addressing this challenge requires detailed understanding of physical processes from plasmon excitation in metal to their collection in a molecule or a semiconductor, where atomistic theoretical investigation may be particularly beneficial. Unfortunately, first-principles theoretical modeling of these processes is extremely costly, limiting the analysis to systems with a few 100s of atoms. Recent advances in machine learned interatomic potentials suggest that dynamics can be accelerated with surrogate models which replace the full solution of the Schroedinger Equation. Here, we modify an existing neural network, Hierarchically Interacting Particle Neural Network (HIP-NN), to predict plasmon dynamics in Ag nanoparticles. We demonstrate the model's capability to accurately predict plasmon dynamics in large nanoparticles of up to 561 atoms not present in the training dataset. More importantly, with machine learning models we gain a speed-up of about 200 times as compared with the rt-TDDFT calculations when predicting important physical quantities such as dynamic dipole moments in Ag55 and about 4000 times for extended nanoparticles that are 10 times larger. This underscores the promise of future machine learning accelerated electron/nuclear dynamics simulations for understanding fundamental properties of plasmon-driven hot carrier devices. △ Less

Submitted 7 March, 2023; originally announced March 2023.

Unconventionally Fast Transport through Sliding Dynamics of Rodlike Particles in Macromolecular Networks

Authors: Xuanyu Zhang, Xiaobin Dai, Md Ahsan Habib, Ziyang Xu, Lijuan Gao, Wenlong Chen, Wenjie Wei, Zhongqiu Tang, Xianyu Qi, Xiangjun Gong, Lingxiang Jiang, Li-Tang Yan

Abstract: Transport of rodlike particles in confinement environments of macromolecular networks plays crucial roles in many important biological processes and technological applications. The relevant understanding has been limited to thin rods with diameter much smaller than network mesh size, although the opposite case, of which the dynamical behaviors and underlying physical mechanisms remain unclear, is… ▽ More Transport of rodlike particles in confinement environments of macromolecular networks plays crucial roles in many important biological processes and technological applications. The relevant understanding has been limited to thin rods with diameter much smaller than network mesh size, although the opposite case, of which the dynamical behaviors and underlying physical mechanisms remain unclear, is ubiquitous. Here, we solve this issue by combining experiments, simulations and theory. We find a nonmonotonic dependence of translational diffusion on rod length, characterized by length commensuration-governed unconventionally fast dynamics which is in striking contrast to the monotonic dependence for thin rods. Our results clarify that such a fast diffusion of thick rods with length of integral multiple of mesh size follows sliding dynamics and demonstrate it to be "anomalous yet Brownian". Moreover, good agreement between theoretical analysis and simulations corroborates that the sliding dynamics is an intermediate regime between hopping and Brownian dynamics, and provides a mechanistic interpretation based on the rod-length dependent entropic free energy barrier. The findings yield a principle, that is, length commensuration, for optimal design of rodlike particles with highly efficient transport in confined environments of macromolecular networks, and might enrich the physics of the diffusion dynamics in heterogeneous media. △ Less

Submitted 19 November, 2023; v1 submitted 26 December, 2022; originally announced December 2022.

Giant Spin Lifetime Anisotropy and Spin-Valley Locking in Silicene and Germanene from First-Principles Density-Matrix Dynamics

Authors: Junqing Xu, Hiroyuki Takenaka, Adela Habib, Ravishankar Sundararaman, Yuan Ping

Abstract: Through First-Principles real-time Density-Matrix (FPDM) dynamics simulations, we investigate spin relaxation due to electron-phonon and electron-impurity scatterings with spin-orbit coupling in two-dimensional Dirac materials - silicene and germanene, at finite temperatures and under external fields. We discussed the applicability of conventional descriptions of spin relaxation mechanisms by Elli… ▽ More Through First-Principles real-time Density-Matrix (FPDM) dynamics simulations, we investigate spin relaxation due to electron-phonon and electron-impurity scatterings with spin-orbit coupling in two-dimensional Dirac materials - silicene and germanene, at finite temperatures and under external fields. We discussed the applicability of conventional descriptions of spin relaxation mechanisms by Elliott-Yafet (EY) and D'yakonov-Perel' (DP) compared to our FPDM method, which is determined by a complex interplay of intrinsic spin-orbit coupling, external fields, and electron-phonon coupling strength, beyond crystal symmetry. For example, the electric field dependence of spin relaxation time is close to DP mechanism for silicene at room temperature, but rather similar to EY mechanism for germanene. Due to its stronger spin-orbit coupling strength and buckled structure in sharp contrast to graphene, germanene has a giant spin lifetime anisotropy and spin valley locking effect under nonzero Ez and relatively low temperature. More importantly, germanene has extremely long spin lifetime (~100 ns at 50 K) and ultrahigh carrier mobility, which makes it advantageous for spin-valleytronic applications. △ Less

Submitted 3 October, 2021; originally announced October 2021.

Comments: 9 pages, 4 figures

Electric fields and substrates dramatically accelerate spin relaxation in graphene

Authors: Adela Habib, Junqing Xu, Yuan Ping, Ravishankar Sundararaman

Abstract: Electrons in graphene are theoretically expected to retain spin states much longer than most materials, making graphene a promising platform for spintronics and quantum information technologies. Here, we use first-principles density-matrix (FPDM) dynamics simulations to show that interaction with electric fields and substrates strongly enhance spin relaxation through scattering with phonons. Conse… ▽ More Electrons in graphene are theoretically expected to retain spin states much longer than most materials, making graphene a promising platform for spintronics and quantum information technologies. Here, we use first-principles density-matrix (FPDM) dynamics simulations to show that interaction with electric fields and substrates strongly enhance spin relaxation through scattering with phonons. Consequently, the relaxation time at room temperature reduces from microseconds in free-standing graphene to nanoseconds in graphene on hexagonal boron nitride (hBN) substrate, the order of magnitude typically measured in experiments. Further, inversion symmetry breaking by hBN introduces a stronger asymmetry in electron and hole spin lifetimes, than predicted by the conventional D'yakonov-Perel' (DP) model for spin relaxation. Deviations from the conventional DP model are stronger for in-plane spin relaxation, resulting in out-of-plane to in-plane lifetime ratios much greater than 1/2 with a maximum close to the Dirac point. These FPDM results, independent of symmetry-specific assumptions or material-dependent parameters, also validate recent modifications of the DP model to explain such deviations. Overall, our results indicate that spin-phonon relaxation in the presence of substrates may be more important in graphene than typically assumed, requiring consideration for graphene-based spin technologies at room temperature. △ Less

Submitted 16 March, 2022; v1 submitted 21 December, 2020; originally announced December 2020.

Comments: 9 pages, 6 figures

Journal ref: Phys. Rev. B 105, 115122 (2022)

Ab initio Ultrafast Spin Dynamics in Solids

Authors: Junqing Xu, Adela Habib, Ravishankar Sundararaman, Yuan Ping

Abstract: Spin relaxation and decoherence is at the heart of spintronics and spin-based quantum information science. Currently, theoretical approaches that can accurately predict spin relaxation of general solids including necessary scattering pathways and capable for ns to ms simulation time are urgently needed. We present a first-principles real-time density-matrix approach based on Lindblad dynamics to s… ▽ More Spin relaxation and decoherence is at the heart of spintronics and spin-based quantum information science. Currently, theoretical approaches that can accurately predict spin relaxation of general solids including necessary scattering pathways and capable for ns to ms simulation time are urgently needed. We present a first-principles real-time density-matrix approach based on Lindblad dynamics to simulate ultrafast spin dynamics for general solid-state systems. Through the complete first-principles descriptions of pump, probe and scattering processes including electron-phonon, electron-impurity and electron-electron scatterings with self-consistent electronic spin-orbit couplings, our method can directly simulate the ultrafast pump-probe measurements for coupled spin and electron dynamics over ns at any temperatures and doping levels. We first apply this method to a prototypical system GaAs and obtain excellent agreement with experiments. We find that the relative contributions of different scattering mechanisms and phonon modes differ considerably between spin and carrier relaxation processes. In sharp contrast to previous work based on model Hamiltonians, we point out that the electron-electron scattering is negligible at room temperature but becomes dominant at low temperatures for spin relaxation in n-type GaAs. We further examine ultrafast dynamics in novel spin-valleytronic materials - monolayer and bilayer WSe2 with realistic defects. We find that spin relaxation is highly sensitive to local symmetry and chemical bonds around defects. Our work provides a predictive computational platform for spin dynamics in solids, which has unprecedented potentials for designing new materials ideal for spintronics and quantum information technology. △ Less

Submitted 30 September, 2021; v1 submitted 15 December, 2020; originally announced December 2020.

Comments: 10 pages, 8 figures

Spin-phonon relaxation from a universal \emph{ab initio} density-matrix approach

Authors: Junqing Xu, Adela Habib, Sushant Kumar, Feng Wu, Ravishankar Sundararaman, Yuan Ping

Abstract: Designing new quantum materials with long-lived electron spin states urgently requires a general theoretical formalism and computational technique to reliably predict intrinsic spin relaxation times. We present a new, accurate and universal first-principles methodology based on Lindbladian dynamics of density matrices to calculate spin-phonon relaxation time ($τ_s$) of solids with arbitrary spin m… ▽ More Designing new quantum materials with long-lived electron spin states urgently requires a general theoretical formalism and computational technique to reliably predict intrinsic spin relaxation times. We present a new, accurate and universal first-principles methodology based on Lindbladian dynamics of density matrices to calculate spin-phonon relaxation time ($τ_s$) of solids with arbitrary spin mixing and crystal symmetry. This method describes contributions of Elliott-Yafet (EY) and D'yakonov-Perel' (DP) mechanisms to spin relaxation for systems with and without inversion symmetry on an equal footing. We show that intrinsic spin and momentum relaxation times both decrease with increasing temperature; however, for the DP mechanism, spin relaxation time varies inversely with extrinsic scattering time. We predict large anisotropy of spin lifetime in transition metal dichalcogenides. The excellent agreement with experiments for a broad range of materials underscores the predictive capability of our method for properties critical to quantum information science. △ Less

Submitted 2 April, 2020; v1 submitted 30 October, 2019; originally announced October 2019.

Comments: 12 pages, 7 figures

Ultrafast Studies of Hot-Hole Dynamics in Au/p-GaN Heterostructures

Authors: Giulia Tagliabue, Joseph S. DuChene, Mohamed Abdellah, Adela Habib, Yocefu Hattori, Kaibo Zheng, Sophie E. Canton, David J. Gosztola, Wen-Hui Cheng, Ravishankar Sundararaman, Jacinto Sa, Harry A. Atwater

Abstract: Harvesting non-equilibrium hot carriers from photo-excited metal nanoparticles has enabled plasmon-driven photochemical transformations and tunable photodetection with resonant nanoantennas. Despite numerous studies on the ultrafast dynamics of hot electrons, to date, the temporal evolution of hot holes in metal-semiconductor heterostructures remains unknown. An improved understanding of the carri… ▽ More Harvesting non-equilibrium hot carriers from photo-excited metal nanoparticles has enabled plasmon-driven photochemical transformations and tunable photodetection with resonant nanoantennas. Despite numerous studies on the ultrafast dynamics of hot electrons, to date, the temporal evolution of hot holes in metal-semiconductor heterostructures remains unknown. An improved understanding of the carrier dynamics in hot-hole-driven systems is needed to help expand the scope of hot-carrier optoelectronics beyond hot-electron-based devices. Here, using ultrafast transient absorption spectroscopy, we show that plasmon-induced hot-hole injection from gold (Au) nanoparticles into the valence band of p-type gallium nitride (p-GaN) occurs within 200 fs, placing hot-hole transfer on a similar timescale as hot-electron transfer. We further observed that the removal of hot holes from below the Au Fermi level exerts a discernible influence on the thermalization of hot electrons above it, reducing the peak electronic temperature and decreasing the electron-phonon coupling time relative to Au samples without a pathway for hot-hole collection. First principles calculations corroborate these experimental observations, suggesting that hot-hole injection modifies the relaxation dynamics of hot electrons in Au nanoparticles through ultrafast modulation of the d-band electronic structure. Taken together, these ultrafast studies substantially advance our understanding of the temporal evolution of hot holes in metal-semiconductor heterostructures and suggest new strategies for manipulating and controlling the energy distributions of hot carriers on ultrafast timescales. △ Less

Submitted 9 October, 2018; originally announced October 2018.

Comments: 12 pages, 4 figures

Hot carrier dynamics in plasmonic transition metal nitrides

Authors: Adela Habib, Fred Florio, Ravishankar Sundararaman

Abstract: Extraction of non-equilibrium hot carriers generated by plasmon decay in metallic nanostructures is an increasingly exciting prospect for utilizing plasmonic losses, but the search for optimum plasmonic materials with long-lived carriers is ongoing. Transition metal nitrides are an exciting class of new plasmonic materials with superior thermal and mechanical properties compared to conventional no… ▽ More Extraction of non-equilibrium hot carriers generated by plasmon decay in metallic nanostructures is an increasingly exciting prospect for utilizing plasmonic losses, but the search for optimum plasmonic materials with long-lived carriers is ongoing. Transition metal nitrides are an exciting class of new plasmonic materials with superior thermal and mechanical properties compared to conventional noble metals, but their suitability for plasmonic hot carrier applications remains unknown. Here, we present fully first-principles calculations of the plasmonic response, hot carrier generation and subsequent thermalization of all group IV, V and VI transition metal nitrides, fully accounting for direct and phonon-assisted transitions as well as electron-electron and electron-phonon scattering. We find the largest frequency ranges for plasmonic response in ZrN, HfN and WN, between those of gold and silver, while we predict strongest absorption in the visible spectrum for the VN, NbN and TaN. Hot carrier generation is dominated by direct transitions for most of the relevant energy range in all these nitrides, while phonon-assisted processes dominate only below 1 eV plasmon energies primarily for the group IV nitrides. Finally, we predict the maximum hot carrier lifetimes to be around 10 fs for group IV and VI nitrides, a factor of 3 - 4 smaller than noble metals, due to strong electron-phonon scattering. However, we find longer carrier lifetimes for group V nitrides, comparable to silver for NbN and TaN, while exceeding 100 fs (twice that of silver) for VN, making them promising candidates for efficient hot carrier extraction. △ Less

Submitted 2 May, 2018; v1 submitted 2 February, 2018; originally announced February 2018.

Comments: 9 pages, 7 figures, 2 tables. Supplemental information in source archive (SI.pdf)

Journal ref: J. Opt. 10, 064001 (2018)