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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The equation of state and shock-driven decomposition of polymethylmethacrylate (PMMA)

We present new equations of state (EOS) for polymethylmethacrylate and its shock-driven decomposition products, generated in both tabular form and as linear U S – u p fits to all previously available shock data. Different approaches are taken for materials shocked above and below the apparent threshold for chemical reactions at pressures P ≈ 30 GPa. Both EOSs are calibrated to and compared with a broad array of experimental results, as well as new ab initio molecular dynamics simulations presented here. Comparisons are good in most cases, and we focus our particular attention on those observables that test the distinction between reactants and products.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Complete Initial Evaluation of Novel Complexants for Tc Holdback for Simplified Single Cycle Separations.

Management of technetium at the back end of nuclear fuel cycle is complicated by its unique physico-chemical character, but must be addressed to due to the environmental, storage and reprocessing challenges of this fission product. In a single-cycle scenario, the recovery and purification of uranium is particularly challenging due to the tendency of a pertechnetate anion to follow uranyl cation. This report summarizes initial studies directed towards finding the solution for technetium management. Two options for controlling technetium’s chemistry in solvent extraction scenarios were studied. Molecular recognition of pertechnetate by aqueous complexants based on guanidinium moieties was compared to redox manipulation of technetium using dihydrazide reagents. Solvent extraction, potentiometric and nuclear magnetic resonance spectroscopy studies were performed. The influence of guanidinium reagents on the liquid-liquid partitioning of technetium is less pronounced, relative to dihydrazides. Strong impact exerted by dihydrazides originates from the technetium-catalyzed decomposition of such compounds which reduces technetium to a tetravalent, non-extractable state. Although this route of technetium management is very effective the destruction of dihydrazides is undesirable. Guanidinium complexants show a more tempered influence on technetium. The effect on the liquid-liquid partitioning of pertechnetate is evident and likely guided by anion recognition due to ion-pair and hydrogen bond formation. Guanidiniums are stable in presence of technetium as evidenced by nuclear magnetic resonance studies. The steady state chemistry of guanidiniums identify this class of aqueous complexants as solid candidates for structure-function pertechnetate recognition studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Thermal conductance enhanced via inelastic phonon transport by atomic vacancies at Cu/Si interfaces

Understanding and controlling heat transfer across interfaces has become an important issue for the performance of micro- and nanoscale electronics, as well as achieving a high figure of merit for thermoelectrics. Intrinsic and extrinsic defects can have a significant impact on thermal transport in bulk materials and across interfaces, but the mechanism is not well understood. Here, nonequilibrium molecular dynamics simulations are used to determine the impact of interfacial atomic vacancies on thermal transport across a Cu/Si junction. In contrast to the reduction in thermal transport typically seen with bulk defects, we find that by introducing atomic vacancies at a concentration of 6.3% near the interface in either or both materials, the interfacial thermal conductance can be increased by up to 76%. By controlling the initial positions of the vacancies and keeping track of their movements and population, we find that interfacial thermal transport is dependent on temperature, vacancy concentration, and distribution, and a positive correlation between the conductance and point defect activities (extent of vacancy migration, rate of Frenkel defect creation and annihilation) is observed. Further calculations based on the phonon density of states and normal mode decomposition reveal that the increase in interfacial thermal conductance originates primarily from high-frequency phonons, supported by enhanced inelastic phonon transport which contributes to more than 60% of the increase. Our findings suggest a practical way to manipulate inelastic phonon conversion through the presence of defects, which provides an alternative perspective on improving thermal transport between materials with a large lattice mismatch.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Controls on Soil Organic Matter Degradation and Subsequent Greenhouse Gas Emissions Across a Permafrost Thaw Gradient in Northern Sweden

Warming-induced permafrost thaw could enhance microbial decomposition of previously stored soil organic matter (SOM) to carbon dioxide (CO 2 ) and methane (CH 4 ), one of the most significant potential feedbacks from terrestrial ecosystems to the atmosphere in a changing climate. The environmental parameters regulating microbe-organic matter interactions and greenhouse gas (GHG) emissions in northern permafrost peatlands are however still largely unknown. The objective of this work is to understand controls on SOM degradation and its impact on porewater GHG concentrations across the Stordalen Mire, a thawing peat plateau in Northern Sweden. Here, we applied high-resolution mass spectrometry to characterize SOM molecular composition in peat soil samples from the active layers of a Sphagnum-dominated bog and rich fen sites in the Mire. Microbe-organic matter interactions and porewater GHG concentrations across the thaw gradient were controlled by aboveground vegetation and soil pH. An increasingly high abundance of reduced organic compounds experiencing greater humification rates due to enhanced microbial activity were observed with increasing thaw, in parallel with higher CH 4 and CO 2 porewater concentrations. Bog SOM however contained more Sphagnum-derived phenolics, simple carbohydrates, and organic- acids. The low degradation of bog SOM by microbial communities, the enhanced SOM transformation by potentially abiotic mechanisms, and the accumulation of simple carbohydrates in the bog sites could be attributed in part to the low pH conditions of the system associated with Sphagnum mosses. We show that Gibbs free energy of C half reactions based on C oxidation state for OM can be used as a quantifiable measure for OM decomposability and quality to enhance current biogeochemical models to predict C decomposition rates. We found a direct association between OM chemical diversity and δ 13 C-CH 4 in peat porewater; where higher substrate diversity was positively correlated with enriched δ 13 C-CH 4 in fen sites. Oxidized sulfur-containing compounds, produced by Sphagnum, were further hypothesized to control GHG emissions by acting as electron acceptors for a sulfate-reducing electron transport chain, inhibiting methanogenesis in peat bogs. These results suggest that warming-induced permafrost thaw might increase organic matter lability, in subset of sites that become wetlands, and shift biogeochemical processes toward faster decomposition with an increasing proportion of carbon released as CH 4 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Electronic Structure Calculations of the Fundamental Interactions in Solvent Extraction Desalination

Solvent extraction desalination (SED) is a promising membrane-free desalination technology, but new solvents are still needed that can improve the molecular-level water selectivity, while minimizing solvent contamination in the aqueous phase. Improvements in solvent design for SED require a fundamental understanding of the molecular interactions governing solvation behavior. Herein, quantum chemical calculations are used to delineate different fundamental interactions in water-solvent systems involving 38 different solvents, with a particular focus on the role of the electrostatic potential characteristics. Furthermore, these interactions are rigorously analyzed using the independent gradient model based on Hirshfeld partition (IGMH), Symmetry-Adapted Perturbation Theory (SAPT), as well as the energy decomposition analysis based on force field (EDA-FF) to compare against a standard force field model. The solvation free energies and partition coefficients are also calculated to estimate water extraction performance in a bulk solvent system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An advanced workflow for single-particle imaging with the limited data at an X-ray free-electron laser

An improved analysis for single-particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental data: inaccessibility of information from half of the detector and a small fraction of single hits. The general SPI analysis workflow was upgraded with the expectation-maximization based classification of diffraction patterns and mode decomposition on the final virus-structure determination step. The presented processing pipeline allowed us to determine the 3D structure of bacteriophage PR772 without symmetry constraints with a spatial resolution of 6.9 nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Formation of large loop-hydrogen complexes and related effects on mechanical properties of Zirconium investigated with molecular dynamics method

Here, using molecular dynamics (MD) method, interaction between hydrogen (H) atoms and interstitial or vacancy dislocation loops in Zr is extensively studied. The results show that the binding of hydrogen atoms to dislocation loops is anisotropic (attractive or repulsive), depending on the position of the hydrogen atoms with respect to the loop’s core. The anisotropy is governed by excess volume and stress field induced by the loop. For a 1/3[$2\bar1$$\bar1$$0$] interstitial dislocation loop, hydrogen atoms preferentially segregate near the outside of the loop and close to the decomposition knots of the loop. While for a 1/3[$2\bar1$$\bar1$$0$] or 1/6[$20$$\bar2$$3$] vacancy loop, hydrogen atoms prefer to segregate near the inside of the loop. The present work indicates large loop-hydrogen complexes could form in Zr. The binding of hydrogen to loops is stable up to 600 K, while dissociation is observed at 900 K. Formation of loop-hydrogen complexes affect the activation of slip system, resulting in higher yield stress of Zr. The effect increases with the increasing ratio of H to vacancies or interstitials in the vacancy or interstitial loops. The results imply the effects of large loop-hydrogen complexes should be considered to fully understand radiation damage in Zr.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Transport and Morphology of a Proton Exchange Membrane Based on a Doubly Functionalized Perfluorosulfonic Imide Side Chain Perflourinated Polymer

There is a critical need for higher performing proton exchange membranes for electrochemical energy conversion devices that would enable higher temperature and drier operating conditions to be utilized. A novel approach is to utilize multiacid side chains in a perfluorinated polymer, maintaining the mechanical properties of the material, while dramatically increasing the ion-exchange capacity; however, as we show in this paper, the more complex side chain gives rise to unexpected physical phenomena in the material. In this work we have thoroughly investigated a doubly functionalized perfluorosulfonic imide acid side chain perfluorinated polymer (PFIA), the simplest of many possible multiacid side chains currently being developed. The material is compared to its simpler perfluorosulfonic acid (PFSA) analogue via a battery of characterization and modeling investigations. The doubly functional side chain profoundly influences the properties of the PFIA polymer as it gives rise to both inter- and intraside chain interactions. These affect the nature of thermal decomposition of the material but, more importantly, force the backbone of the polymer into an unusually highly ordered more crystalline configuration. Under water saturated conditions, the PFIA has the same proton conductivity as the PFSA material, indicating that the additional proton does not contribute to the ionic conductivity, but the PFIA shows higher proton conductivity at lower RH conditions owing to dynamic changes in its local molecular environment. A transition is observed between 30 and 60 °C, indicating an order/disorder transition that is not present in the PFSA analogue. The mechanism of proton transport in the PFIA is due to more delocalized protons and more flexible side chains with better-dispersed, smaller water clusters forming the hydrophilic domains than in the PFSA analogue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Learning Latent Representations to Bridge Coarse-Grained and Atomistic Resolutions in Polymer Simulations

We present a machine-learning-based framework for learning reduced-order representations of polymer chain conformations across coarse-grained (CG) and united-atom (UA) fidelities. By employing linear singular value decomposition and nonlinear autoencoders, we compress high-dimensional polymer configurations into latent spaces with minimal loss of structural accuracy. Crucially, we demonstrate a near-perfect linear mapping between CG and UA latent spaces, enabling an efficient super-resolution back-mapping procedure that reconstructs high-fidelity UA configurations from CG simulations. While minor structural inaccuracies occur, they are effectively corrected through a brief molecular dynamics relaxation, forming a practical hybrid machine learning−physics scheme. This approach establishes the key structural prerequisites for accelerated polymer dynamics simulations: a compact and accurate latent encoding of polymer chain conformations and a validated multi-fidelity mapping that permits reconstruction of UA structures from CG configurations. The extension of this framework to explicit time evolution within the latent space, enabling dynamics to be propagated at CG fidelity and decoded to UA resolution only when required, represents a natural and well-motivated direction for future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Characterization of plasma catalytic decomposition of methane: role of atomic O and reaction mechanism

In this work, we investigated atmospheric pressure plasma jet (APPJ)-assisted methane oxidation over a Ni-SiO 2 /Al 2 O 3 catalyst. We evaluated possible reaction mechanisms by analyzing the correlation of gas phase, surface and plasma-produced species. Plasma feed gas compositions, plasma powers, and catalyst temperatures were varied to expand the experimental parameters. Real-time Fourier-transform infrared spectroscopy was applied to quantify gas phase species from the reactions. The reactive incident fluxes generated by plasma were measured by molecular beam mass spectroscopy using an identical APPJ operating at the same conditions. A strong correlation of the quantified fluxes of plasma-produced atomic oxygen with that of CH 4 consumption, and CO and CO 2 formation implies that O atoms play an essential role in CH 4 oxidation for the investigated conditions. With the integration of APPJ, the apparent activation energy was lowered and a synergistic effect of 30% was observed. We also performed in-situ diffuse reflectance infrared Fourier-transform spectroscopy to analyze the catalyst surface. The surface analysis showed that surface CO abundance mirrored the surface coverage of CH n at 25 °C. This suggests that CH n adsorbed on the catalyst surface as an intermediate species that was subsequently transformed into surface CO. We observed very little surface CH n absorbance at 500 °C, while a ten-fold increase of surface CO and stronger CO 2 absorption were seen. This indicates that for a nickel catalyst at 500 °C, the dissociation of CH 4 to CHn may be the rate-determining step in the plasma-assisted CH 4 oxidation for our conditions. We also found the CO vibrational frequency changes from 2143 cm –1 for gas phase CO to 2196 cm –1 for CO on a 25 °C catalyst surface, whereas the frequency of CO on a 500 °C catalyst was 2188 cm –1 . Here, the change in CO vibrational frequency may be related to the oxidation of the catalyst.

methane oxidation↗
DOE OSTI2024

Strategies to Obtain Reliable Energy Landscapes from Embedded Multireference Correlated Wavefunction Methods for Surface Reactions

Embedded correlated wavefunction (ECW) theory is a powerful tool for studying ground- and excited-state reaction mechanisms and associated energetics in heterogeneous catalysis. Several factors are important to obtaining reliable ECW energies, critically the construction of consistent active spaces (ASs) along reaction pathways when using a multireference correlated wavefunction (CW) method that relies on a subset of orbital spaces in the configuration interaction expansion to account for static electron correlation, e.g., complete AS self-consistent field theory, in addition to the adequate partitioning of the system into a cluster and environment, as well as the choice of a suitable basis set and number of states included in excited-state simulations. Here, in this work, we conducted a series of systematic studies to develop best-practice guidelines for ground- and excited-state ECW theory simulations, utilizing the decomposition of NH 3 on Pd(111) as an example. We determine that ECW theory results are relatively insensitive to cluster size, the aug-cc-pVDZ basis set provides an adequate compromise between computational complexity and accuracy, and that a fixed-clean-surface approximation holds well for the derivation of the embedding potential. Additionally, we demonstrate that a merging approach, which involves generating ASs from the molecular fragments at each configuration, is preferable to a creeping approach, which utilizes ASs from adjacent structures as an initial guess, for the generation of consistent potential energy curves involving open-d-shell metal surfaces, and, finally, we show that it is essential to include bands of excited states in their entirety when simulating excited-state reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Density Functional Theory Study of the Adsorption and Dissociation of Copper(I) Acetamidinates on Ni(110): The Effect of the Substrate

In order to assess the role of a metal substrates on the thermal chemistry of adsorbed acetamidinate metalorganic compounds, we have studied the surface chemistry of copper(I)–N,N'-dimethylacetamidinate on Ni(110) using density functional theory and contrasted it with similar calculations we previously carried out on Cu(110). At low coverages, it was found that, in its most stable configuration, the molecular adsorption of copper(I)–N,N'-dimethylacetamidinate dimers occurs with the Cu atoms occupying surface hollow sites. In this work, the ligands reorient away from those metal centers, and the N atoms develop new direct bonds with surface Ni atoms. However, this configuration is not stable and decomposes by losing both ligands to the surface. In the final state, the two ligands bind via their N atoms to Ni sites one lattice space away from the sites where the Cu atoms remain, with their molecular planes perpendicular to that of the surface. This is in contrast with what happens in the case of adsorption on Cu(110), where the Cu atoms from the metalorganic complex still occupy hollow sites but where only one of the ligands breaks away and binds directly to the surface; the other remains on top of the two Cu ions. In terms of the energetics of adsorption and decomposition, the reactions on Ni(110) are much more exothermic than on Cu(110). Further analysis of the distribution of charge within the adsorbates shows a minor reduction of the Cu atoms of the dimer upon interaction with the surface; full reduction to metallic copper is complete only when both ligands have fully migrated to their new Ni surface sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Unmixing Symmetries

The low-lying spectra of atomic nuclei display diverse behaviors, for example, rotational bands, which can be described phenomenologically by simple symmetry groups such as spatial SU(3). This leads to the idea of dynamical symmetry, where the Hamiltonian commutes with the Casimir operator(s) of a group, and is block diagonal in subspaces defined by the group’s irreducible representations or irreps. Detailed microscopic calculations, however, show these symmetries are in fact often strongly mixed and the wave function fragmented across many irreps. More commonly, the fragmentation across members of a band are similar, which is called a quasidynamical symmetry. In this Letter I explicitly, albeit numerically, construct unitary transformations from a quasidynamical symmetry to a dynamical symmetry, adapting the similarity renormalization group (SRG) in order to transform away the symmetry-mixing parts of the Hamiltonian. In this work, the standard SRG produces unsatisfactory results, forcing the induced dynamical symmetry to be dominated by high-weight irreps irrespective of the original decomposition. Using spectral distribution theory to rederive and diagnose standard SRG, I introduce a new form of SRG. The new SRG transforms a quasidynamical symmetry to a dynamical symmetry, that is, unmixes the mixed symmetries, with intuitively more appealing results.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Triiodide Attacks the Organic Cation in Hybrid Lead Halide Perovskites: Mechanism and Suppression

Molecular I 2 can be produced from iodide-based lead perovskites under thermal stress; triiodide, I 3 − , is formed from this I 2 and I − . Triiodide attacks protic cation MA + - or FA + -based lead halide perovskites (MA + , methylammonium; FA + , formamidinium) as explicated through solution-based nuclear magnetic resonance (NMR) studies: triiodide has strong hydrogen-bonding affinity for MA + or FA + , which leads to their deprotonation and perovskite decomposition. Triiodide is a catalyst for this decomposition that can be obviated through perovskite surface treatment with thiol reducing agents. In contrast to methods using thiol incorporation into perovskite precursor solutions, no penetration of the thiol into the bulk perovskite is observed, yet its surface application stabilizes the perovskite against triiodide-mediated thermal stress. Thiol applied to the interface between FAPbI 3 and Spiro-OMeTAD (“Spiro”) prevents oxidized iodine species penetration into Spiro and thus preserves its hole-transport efficacy. Surface-applied thiol affects the perovskite work function; it ameliorates hole injection into the Spiro overlayer, thus improving device performance. It helps to increase interfacial adhesion (“wetting”): fewer voids are observed at the Spiro/perovskite interface if thiols are applied. Perovskite solar cells (PSCs) incorporating interfacial thiol treatment maintain over 80% of their initial power conversion efficiency (PCE) after 300 h of 85 °C thermal stress.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Completely Multipolar Model for Many-Body Water–Ion and Ion–Ion Interactions

This work constructs an advanced force field, the Completely Multipolar Model (CMM), to quantitatively reproduce each term of an energy decomposition analysis (EDA) for aqueous solvated alkali metal cations and halide anions and their ion pairings. We find that all individual EDA terms remain well-approximated in the CMM for ion-water and ion-ion interactions, except for polarization, which shows errors due to the partial covalency of ion interactions near their equilibrium. We quantify the onset of the dative bonding regime by examining the change in molecular polarizability and Mayer bond indices as a function of distance, showing that partial covalency manifests by breaking the symmetry of atomic polarizabilities while strongly damping them at short-range. This motivates an environment-dependent atomic polarizability parameter that depends on the strength of the local electric field experienced by the ions to account for strong damping, with anisotropy introduced by atomic multipoles. The resulting CMM model for ions provides accurate dimer surfaces and three-body polarization and charge transfer compared to EDA, and shows excellent performance on various ion benchmarks including vibrational frequencies and cluster geometries.

Heindel, Joseph P↗
DOE OSTI2023

Studying performance portability of LAMMPS across diverse GPU-based platforms

The molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA's fast-fourier transform (FFT) library, and, more recently, also support for AMD's Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU-based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle-particle particle-mesh (PPPM) long-range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting communication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard-Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. In conclusion, the selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard–Jones potentials on Crusher and Summit.

97 MATHEMATICS AND COMPUTING↗