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At least 73 records · Page 4

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer Simulation of Proton Transport in Fuel Cell Membranes (Final Report)

This DOE-supported research grant focused on understanding the nature of proton transport in complex systems such as proton exchange membranes (PEMs). The most unique aspect of the research was the development and implementation of a novel multiscale reactive molecular dynamics (MS-RMD) methodology. In this approach, covalent bonds can dynamically break and form, allowing one to accurately treat the proton hopping process essential to capturing the physics of proton transport. The Voth group applied this method to proton exchange membrane systems, providing insight into their proton transport mechanism. They found that protons can diffuse most rapidly in the water-rich regions, but that protons actually spend so little time in such regions that transport along the hydrophobic – hydrophilic interface controls the membrane performance. In addition, the group worked to increase understanding of acidic solutions, developing methods for simulating and interpreting experimental infrared vibrational spectroscopy for excess protons (acidic solutions). The group also implemented novel tools for developing proton transport reactive MD models using a relative entropy minimization scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Boltzmann machine modeling of layered MoS 2 synthesis on a quantum annealer

Two-dimensional layered materials are usually synthesized by chemical vapor deposition (CVD). Here we use the Restricted Boltzmann Machine (RBM) and its enhancement called Limited Boltzmann Machine (LBM) on a quantum computer to model the chemical vapor deposition (CVD) growth data for a MoS 2 monolayer. The CVD data for Boltzmann machines are generated by reactive molecular dynamics (RMD) simulations. The Boltzmann machines give insight into the semiconducting (2H) and metallic (1T) phases and defects generated during the CVD growth of MoS 2 . We compare the performances of the two types of Boltzmann machine models, i.e. RBM versus augmented topologies with limited intra-layer coupling between the hidden units (LBM). We show that limited topologies have a performance advantage over restricted topologies. We examine connectivity within our topological variants, explore hardware qubit mapping schemes, and discuss what performance differences may imply about locality within the data without prior knowledge.

36 MATERIALS SCIENCE↗

Nanomechanical investigation of the interplay between pore morphology and crack orientation of amorphous silica

Porous amorphous silica (a-SiO 2 ) is of both fundamental and practical interests, as they exhibit a large specific surface area and tunable porous network. However, the brittle nature of a-SiO 2 and the presence of pre-existing cracks at both micro- and nano-scales lead to complex mechanical behavior. Here, we systematically investigate the effects of pre-existing crack and its orientation on the mechanical properties of a-SiO 2 with varying pore shapes using reactive molecular dynamics simulations. We demonstrate that pore shape will primarily influence the Young’s modulus (E) and critical energy release rate (G IC ). We further investigate the impact of pore shape and crack orientation by local characterization of the structural parameters. By defining the high stress and inter-mediate regions, the overall mechanical properties are found to be greatly influenced by the pore shape which can be reflected through the spatial distribution of von Mises stress. Overall, G IC is found to increase with the increase of ligament length (also known as pore wall thickness). Meanwhile, the effect of the pre-existing crack on the crack propagation process is confirmed by analyzing the density distribution evolution. These results highlight the interplay between pore morphology and crack orientation in controlling the fracture behaviors in brittle porous materials.

42 ENGINEERING↗

Plasma-assisted chemical-looping combustion: Mechanistic insights into low temperature methane oxidation with CuO

The low-temperature oxidation of CH 4 by CuO in a coaxial, fixed bed, double dielectric barrier discharge (DBD) reactor was investigated with time-dependent species measurements by an electron-ionization molecular beam mass spectrometer (EI-MBMS). In the experiment, 10% methane carried by noble gasses was flown at 50 sccm through 1 g CuO dispersed in quartz wool both under plasma and non-plasma conditions, while time-dependent gas-phase species profiles were collected. Plasma conditions were explored from 300 to 600 °C while the non-plasma conditions were set from 300 to 900 °C. Mechanistic insights into the oxidation of CH 4 by CuO with plasma discharge at lower temperatures (≤ 600 °C) were obtained by quantifying the fuel oxidation, intermediate species, and CO 2 production in comparison to the non-plasma conditions. Here, we observed significant enhancement of fuel oxidation from the plasma discharge between 400 and 500 °C. The CO 2 production at 500 °C with plasma was greater than that at 700 °C without plasma, reducing fuel oxidation temperature by 200+ °C. During tests, three distinct reaction stages were observed: a gas-phase transport limited stage, a surface reaction limited kinetic stage, and an oxygen ion diffusion limited stage. It was observed that plasma greatly improved the reactivity of the second stage at low temperature. In addition, no carbon deposits were observed on the resultant particles, even under the presence of plasma. M. species such as C 4 H 2 and C 6 H 6 not previously observed or predicted in CuO/CH 4 chemical looping were observed, with some species such as CH 3 OH only becoming detectable as total flowrate was increased from 50 to 1500sccm. A non-plasma reaction pathway for CH 4 based the observed species from the MBMS spectrum and previous predictions from reactive molecular dynamics simulations was created, providing a framework from which more complex plasma CuO mechanisms can be crafted from.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation

In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves. By contrast, simple and inexpensive physics-based models, such as the well-established Morse potential, do not suffer from any such limitations. This work leverages the Morse potential to improve reactive MLIPs by augmenting the training data set with inexpensive Morse data along the dissociation pathways. Further, this physics-constrained data augmentation (PCDA) approach results in MLIPs with smooth bond dissociation curves as well as near coupled-cluster level BDEs, all without requiring any expensive multireference quantum mechanical calculations. A case study for methane combustion demonstrates how the PCDA approach can improve an existing reactive MLIP, namely, ANI-1xnr. In conclusion, not only are the BDEs and bond dissociation curves for all radicals and molecules significantly improved compared to ANI-1xnr but the PCDA-trained MLIP retains the reliability of ANI-1xnr when performing reactive molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Semi-Automated Creation of Density Functional Tight Binding Models through Leveraging Chebyshev Polynomial-Based Force Fields

Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. Here, we have focused our workflow on TiH 2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insight into the Chemistry of PETN Under Shock Compression Through Ultrafast Broadband Mid-Infrared Absorption Spectroscopy

In this study, thin films of pentaerythritol tetranitrate (PETN) were shock compressed using the laser driven shock apparatus at Los Alamos National Laboratory (LANL). Two spectroscopic probes were available to this apparatus: visible white light transient absorption spectroscopy (VIS) from 400 to 700 nm and mid-infrared transient absorption spectroscopy (MIR) from 1150 to 3800 cm –1 . Important PETN vibrational modes are the symmetric and antisymmetric NO 2 stretches at 1280 and 1650 cm –1 , respectively, as well as CH stretches at ~2900 cm –1 . Shock strength was varied from approximately 3 to 55 GPa to span from the chemically unreactive regime to the regime in which fast chemical reaction took place on the 250 ps time scale of the measurements. VIS and MIR results suggest irreversible chemistry was induced in PETN at pressures above 30 GPa. At lower shock pressures, the spectroscopy showed minimal changes attributable to pressure induced effects. Under the higher-pressure reactive conditions, the frequency region at the antisymmetric NO 2 stretch mode had a significantly increased absorption while the region around the symmetric NO 2 stretch did not. No observable increased absorption occurred in the higher frequency regions where CH-, NH-, and OH- bond absorptions would be observed. A broad absorption appeared on the shoulder at the red-edge of the CO 2 vibrational band around 2200 cm –1 . In addition to the experiments, reactive molecular dynamics were carried out under equivalent shock conditions to correlate the evolution of the infrared spectrum to molecular processes. The simulations show results consistent to experiments up to 30 GPa but suggest that NO and NO 2 related features provided the strongest contributions to the shocked infrared changes. Proposed mechanisms for shocked PETN chemistry are analyzed as consistent or inconsistent with the data presented here. Our experimental data suggests C≡O or N 2 O bond formation, nitrite formation, and absence of significant hydroxyl or amine concentrations in the initial chemistry steps in PETN shocked above 30 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning

When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Segregation of Liquid Metal Plasma-Facing Component Alloys: A ReaxFF Investigation

Engineering liquid metal alloys offers a transformative pathway for plasma-facing components by enabling chemically tailored surfaces that can simultaneously optimize plasma-material interactions, reduce divertor heat flux, and enhance core plasma confinement, thereby advancing the commercial viability of nuclear fusion power plants. This study, employing an atomistic simulation approach, provides direct evidence that incorporating nonmetal surface-active agents (such as O and H, or their combination) enables strong surface segregation. This capability makes tin−aluminum (Sn−Al) and tin−lithium (Sn−Li) alloys, with suitable compositions, good candidates for PFC applications. Specifically, the presence of low-Z solutes (Li, Al) leads to preferential surface enrichment, which imparts low-Z sputtering characteristics, while the Sn solvent maintains thermophysical stability. To systematically examine this behavior, we developed a ReaxFF force field spanning the full Sn/Al/Li/O/H chemistry, validated it against formation energies and elastic constants, and applied it in reactive molecular dynamics simulations at fusion-relevant temperatures. We also introduced an overlapbased segregation index that captures interfacial compositional separation directly from atomistic density distributions. Here, this metric reveals a clear hierarchy of segregation regimes and provides a unified view across all systems studied. Together, these findings establish a mechanistic link between nonmetal chemistry and interfacial structure, providing a predictive framework for designing self-adaptive, low-sputtering liquid metal alloys for fusion applications.

Alloys↗

Extemporaneous Mechanochemistry: Shock-Wave-Induced Ultrafast Chemical Reactions Due to Intramolecular Strain Energy

We report regions of energy localization referred to as hotspots are known to govern shock initiation and the run-to-detonation in energetic materials. Mounting computational evidence points to accelerated chemistry in hotspots from large intramolecular strains induced via the interactions between the shock wave and microstructure. However, definite evidence mapping intramolecular strain to accelerated or altered chemical reactions has so far been elusive. From a large-scale reactive molecular dynamics simulation of the energetic material 1,3,5-triamino-2,4,6-trinitrobenzene, we map decomposition kinetics to molecular temperature and intramolecular strain energy prior to reaction. Both temperature and intramolecular strain are shown to accelerate chemical kinetics. A detailed analysis of the atomistic trajectory shows that intramolecular strain can induce a mechanochemical alteration of decomposition mechanisms. The results in this paper could inform continuum-level chemistry models to account for a wide range of mechanochemical effects.

36 MATERIALS SCIENCE↗

Surface Transfer Doping in MoO 3– x /Hydrogenated Diamond Heterostructure

Surface transfer doping is proposed to be a potential solution for doping diamond, which is hard to dope for applications in high-power electronics. While MoO 3 is found to be an effective surface electron acceptor for hydrogen-terminated diamond with a negative electron affinity, the effects of commonly existing oxygen vacancies remain elusive. We have performed reactive molecular dynamics simulations to study the deposition of MoO 3–x on a hydrogenated diamond (111) surface and used first-principles calculations based on density functional theory to investigate the electronic structures and charge transfer mechanisms. We find that MoO 3–x is an effective surface electron acceptor and the spatial extent of doped holes in hydrogenated diamond is extended, promoting excellent transport properties. Charge transfer is found to monotonically decrease with the level of oxygen vacancy, providing guidance for engineering of the surface transfer doping process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ReaxFF Simulations of Laser-Induced Graphene (LIG) Formation for Multifunctional Polymer Nanocomposites

Irradiation of polymer films by a CO 2 infrared laser under ambient conditions converts the polymer into porous graphene or laser-induced graphene (LIG). In this work, we simulate the formation of LIG from five different commercially available polymers using reactive molecular dynamics. We determined that the molecular structure of the parent polymer has a significant effect on the final graphitic structure. CO is liberated during the initial part of the LIG formation process when the polymer is converted into an amorphous structure, while H 2 is evolved steadily as the amorphous structure is converted to an ordered graphitic structure. The LIG structure has out-of-plane undulations and bends due to a significant number of 5- and 7-member carbon rings present throughout the structure. We find that the simulated molecular structure compares well with recent experimental observations from the literature. We also demonstrate that the yield of LIG is higher in inert conditions, compared to environments with oxygen. Polybenzimidazole-derived LIG has the highest surface area and yield among the five polymers examined. These findings provide knowledge of LIG formation mechanisms that can be leveraged for bulk LIG applications such as sensors, electrocatalysts, microfluidics, and targeted heating for welding polymers.

36 MATERIALS SCIENCE↗

Atomistic Mechanisms of Stress-Dependent Molten Salt Corrosion in NiCr Alloys

Ni-based structural alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni 0.75 Cr 0.25 exposed to molten FLiNaK at 800 °C. A Σ5(210) grain boundary model is subjected to tensile (+4%) to compressive (−4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary evolution. Tensile strain accelerates intergranular corrosion susceptibility by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain can suppress corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.

36 - MATERIALS SCIENCE↗

Hydration-Controlled Proton Transport in Respiratory Complex I

Proton pumping by respiratory complex I is one essential element for generating the proton motive force that drives ATP synthesis in mitochondria. Although it is understood that electrons from NADH reduce ubiquinone at the peripheral arm and that four protons are transferred in the membrane domain, the mechanism by which this redox reaction initiates proton translocation remains unclear. A lateral pathway linking the quinone binding site to the membrane domain via ND1, ND3, and ND4L subunits has been proposed as a possible initial path of an excess proton. However, experimental structures indicate that the hydration connectivity between D66 ND3 and E34 ND4L is comparatively weaker than in neighboring segments, suggesting a potential regulatory point for proton transfer. Using multiscale reactive molecular dynamics (MS-RMD) and a water wire connectivity metric, we directly simulate proton transport through this region as coupled to the hydration by water molecules. Our results reveal that proton transfer is thermodynamically feasible when transient hydration aligns with the presence of an excess proton, revealing the strong coupling between hydration and proton transfer (PT) in this region of Complex I. These findings support a model where proton injection enhances local hydration, dynamically opening the pathway for proton transfer and regulating the onset of proton pumping in Complex I.

Chemical structure↗

Corrosive Influence of Carbon Dioxide on Crack Initiation in Quartz: Comparison With Liquid Water and Vacuum Environments

The stimulation of crack growth in quartz and siliceous materials by injecting carbon dioxide (CO 2 ) represents a key technology in long-term carbon storage and in the development of natural gas wells. While this technology is widely used, the molecular impact of CO 2 interactions on the solid matrix is only incompletely understood. In this work, we employ reactive molecular dynamics simulations to study how the CO 2 fluid environment affects the mechanical properties of pre-cracked single-crystal quartz. The thermodynamic conditions of interest are those relevant to subsurface reservoirs. We report how structural properties of quartz—bond length distribution and crack tip shape—evolve upon introduction of a fluid. These properties are directly related to macroscopic quantities of the global stress-strain curves, thus reaffirming the inherent coupling across multiple scales for fluid-solid interactions in the subsurface. Here, we find that CO 2 reduces the fracture toughness of quartz by 12.1% compared to that of quartz in vacuum, thereby promoting crack growth and enhancing fluid transport in the subsurface.

58 GEOSCIENCES↗

Cost-effective carbon fiber precursor selections of polyacrylonitrile-derived blend polymers: carbonization chemistry and structural characterizations

Blending polyacrylonitrile (PAN) with plastic wastes and bio-based polymers provides a convenient and inexpensive method to realize cost-effective carbon fiber (CF) precursors. In this work, PAN-based blend precursors are investigated using ReaxFF reactive molecular dynamics simulations with respect to the formation of all-carbon rings, the evolutions of oxygen-containing and nitrogen-containing species, and the migration of carbon atoms to form turbostratic graphene. From these simulations, we identify that PAN/cellulose (CL) blend manifests the highest carbon yield and the most substantial all-carbon ring formation. This ReaxFF-based finding is confirmed by Raman and TEM experiments indicating high crystallinity for PAN/CL-derived blend CFs. We trace the pathway of gasification and carbonization of PAN/CL to elaborate the mechanism of the formation of all-carbon ring networks. We discover that the acetals of CL can catalyze the cyclization of the blend precursor, allowing for the search for CL derivatives or the other kinds of bio-based polymers with similar functionalities as alternative blends. In addition, we examine the structural characteristics using the carbon–carbon (C–C) radial distribution functions, C–C bond length distributions, and sp2 C atom ratios for the four representative precursors, i.e., PAN, oxidized PAN, PAN/nylon 6,6, and PAN/CL. Our simulation results show the most extensive all-carbon ring cluster and graphitic structure growths for PAN/CL. Here, we propose PAN/CL as a cost-effective alternative CF precursor, since (a) CL is naturally abundant and eco-friendly for production, (b) the blend precursor PAN/CL does not require oxidation treatment, (c) PAN/CL has a high carbon yield with substantial all-carbon ring formation, and (d) PAN/CL based CFs potentially provide a mechanical property enhancement.

36 MATERIALS SCIENCE↗