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At least 73 records · Page 4

Modeling, Measurements, and Fundamental Database Development for Nonequilibrium Hypersonic Aerothermodynamics

The design of entry vehicles requires predictions of aerothermal environment during the hypersonic phase of their flight trajectories. These predictions are made using computational fluid dynamics (CFD) codes that often rely on physics and chemistry models of nonequilibrium processes. The primary processes of interest are gas phase chemistry, internal energy relaxation, electronic excitation, nonequilibrium emission and absorption of radiation, and gas-surface interaction leading to surface recession and catalytic recombination. NASAs Hypersonics Project is advancing the state-of-the-art in modeling of nonequilibrium phenomena by making detailed spectroscopic measurements in shock tube and arcjets, using ab-initio quantum mechanical techniques develop fundamental chemistry and spectroscopic databases, making fundamental measurements of finite-rate gas surface interactions, implementing of detailed mechanisms in the state-of-the-art CFD codes, The development of new models is based on validation with relevant experiments. We will present the latest developments and a roadmap for the technical areas mentioned above

Bose, Deepak

Nucleobases and Prebiotic Molecules in Organic Residues Produced from the Ultraviolet Photo-Irradiation of Pyrimidine in NH3 and H2O+NH3 Ices

Although not yet identified in the interstellar medium (ISM), N-heterocycles including nucleobases the information subunits of DNA and RNA are present in carbonaceous chondrites, which indicates that molecules of biological interest can be formed in non-terrestrial environments via abiotic pathways. Recent laboratory experiments and ab-initio calculations have already shown that the irradiation of pyrimidine in pure H2O ices leads to the formation of a suite of oxidized pyrimidine derivatives, including the nucleobase uracil. In the present work, NH3:pyrimidine and H2O:NH3:pyrimidine ice mixtures with different relative proportions were irradiated with UV photons under astrophysically relevant conditions. Liquid- and gas-chromatography analysis of the resulting organic residues has led to the detection of the nucleobases uracil and cytosine, as well as other species of prebiotic interest such as urea and small amino acids. The presence of these molecules in organic residues formed under abiotic conditions supports scenarios in which extraterrestrial organics that formed in space and were subsequently delivered to telluric planets via comets and meteorites could have contributed to the inventory of molecules that triggered the first biological reactions on their surfaces.

Nuevo, Michel

Electrostatic Properties of Polymers Subjected to Atmospheric Pressure Plasma Treatment; Correlation of Experimental Results with Atomistic Modeling

this study, PE, PTFE, PS and PMMA were exposed to a He+O2, APGD and pre and post treatment surface chemistries were analyzed by X-ray photoelectron spectroscopy and contact angle measurements. Semi-empirical and ab-initio calculations were performed to correlate the experimental results with sonic plausible molecular and electronic structure features of the oxidation process. For the PE and PS, significant surface oxidation showing C-O, C=O, and O-C=O bonding, and a decrease in the surface contact angles was observed. For the PTFE and PM MA, little change in the surface composition was observed. The molecular modeling calculations were performed on single and multiple oligomers and showed regardless of oxidation mechanism, e.g. -OH, =O or a combination thereof, experimentally observed levels of surface oxidation were unlikely to lead to a significant change in the electronic structure of PE and PS, and that the increased hydrophilic properties are the primary reason for the observed changes in its electrostatic behavior. Calculations for PTFE and PMMA argue strongly against significant oxidation of those materials, as confirmed by the XPS results.

Trigwell, S.

Application of Ab Initio Methods in the Development of Advanced Technical Ceramics

A significant need exists to develop materials not only capable of providing desired electronic and mechanical properties but also survival at extreme temperatures during service and device fabrication, such as co-firing. Computational methods offers an efficient and systematic manner to design new materials and guide their development. As an example computational -based material approaches can be used to determine the suitability of a given materials as a practical thermoelectric for energy harvesting. In this presentation examples are given of applications to relevant technical ceramics such as thermoelectrics, dielectrics, and magnetic systems. The calculation were based on density functional theory and carried out with norm conserving and projector augmented wave (PAW) methods using commercial codes Materials Studio ( Biovia, Inc) with the Cambridge Serial Total Energy Package (CASTEP) and MedeA (Materials Design Inc.) utilizing the Vienna Ab-initio Simulation Package (VASP) as the respective computational engines. This study makes predictions of relevant technical properties of ceramic materials.

thermoelectric

Molecular Simulations of Ultrafast Radiation Induced Melting at Metal-Semiconductor Interfaces

Understanding radiation induced ultrafast melting at material interfaces is essential in designing robust electronic devices for aviation/space applications and in laser machining. While it is difficult to achieve the spatial and temporal resolution required to quantify the phenomenon experimentally, simulations can provide the detailed mechanisms of the structural changes that happen during phase transition. In this work, we use molecular simulations to study the effect of radiation damage on silicon carbide (SiC) - tungsten (W) interfaces which is of interest in high power electronics. A multi-scale approach is involved wherein the reactions at the interfaces are quantified using ab-initio molecular dynamics (MD) simulations and classical MD simulations are employed to understand the structural and diffusional changes across the material interface. Finally, coarse-grained Lennard-Jones type models are used to study the larger scale mechanisms and structures obtained due to the induced damages. We show that the response of the material to radiation damage depends on factors such as energy of the incident radiation, thermal properties, and molecular structure of the material.

Ravichandran, Ashwin

Recommended Direct Simulation Monte Carlo Collision Model Parameters for Reacting Methane Flows

While hydrocarbon combustion and gas-surface interactions have been simulated for a variety of applications in continuum solvers, such processes have been rarely investigated in Direct Simulation Monte Carlo (DSMC). Thus Variable Hard/Soft Sphere (VHS/VSS)collision parameters are not available for most molecules of interest in the decomposition of methane, a significant pyrolysis gas product and potential atmospheric species for Titan re-entries. As these properties are essential for accurate modeling of gas transport and thermochemical effects, a method must be devised to compute them for use in DSMC. In this study, the methodology outlined in Stephani et al is utilized to compute the VHS/VSS parameters by fitting the Ω(1,1)and Ω(2,2) collision integrals [1]. These collision integrals are typically computed from intermolecular potentials and are used in CFD simulations to calculate transport properties such as viscosity, thermal conductivity, and diffusion. This approach ensures consistency between micro-scale collisions and macro-scale transport properties. To produce the necessary collision integrals needed for the fitting routine, we utilize the method described by Laricchiuta et al, where collision integrals are computed based on the constituent particles’ polarizability and effective electron number [2].Preliminary computations of pure-species Ω(1,1)and Ω(2,2)collision integrals produced from the coupled approach of Stephani et al and Laricchiuta et al for methane show good agreement with those computed via available ab-initio Potential Energy Surface Computations, as seen in Figure 1. Above 300K, no more than 12% deviation is observed between the two results over the temperature range of the fitted PES data [3].Current results of this study include full collision-specificVSS transport properties for a complex-species mixture involving major byproducts of pure methane decomposition. Targeted final results will include a comprehensive list of VSS parameters relevant toDSMC simulations of Titan atmospheric entry, based on the reduced kinetic model of Savajano et al [4].

M R Gosma

A Holistic DSMC Transport Database for Re-Entry and Ablation Modeling

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity solutions of environments containing combined continuum/rarified flow. The use of DSMC, a stochastic, particle-based method, is necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally very computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the used thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. While the transport models governing CFD and DSMC simulations are starkly different, they can effectively be linked via their use of reduced Chapman-Enskog collision integrals. In CFD, these integrals are typically stored as fitted polynomial expressions and used to directly compute gas transport properties via mixing rules or the full Chapman-Enskog formulation. In DSMC, they can be used to derive the collision parameters needed for the phenomenological collision cross-section models that govern particle interactions, via a Nelder-Mead optimization scheme. The goal of this work is to provide a unified DSMC transport database encompassing the vast majority of known gas species encountered during atmospheric entry, on Earth or any other Solar body. This goal is largely possible due to recently performed ab-initio quantum chemistry calculations. Combined with other high-fidelity literature sources, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 17000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute Variable Soft Sphere (VSS) collision model parameters for DSMC, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database will be able to be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below. Equilibrium mixture transport properties for a 19-species Titan atmospheric model [4] are computed using both fitted VSS parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches is less than 5% for the entire temperature range.

M R Gosma

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

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

Model-free Rayleigh weight from x-ray Thomson scattering measurements

X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the interpretation of the measured XRTS intensity usually relies on theoretical models and approximations. In this context, a key property is given by the Rayleigh weight that describes the electronic localization around the ions. Here, we show that it is possible to extract the Rayleigh weight directly from the experimental data without the need for any model calculations or simulations. As a practical application, we consider an experimental measurement of strongly compressed Be at the National Ignition Facility [Döppner et al., Nature 618, 270–275 (2023)]. We demonstrate that experimental results for the Rayleigh weight open up new avenues for the interpretation of XRTS experiments by matching the measurement with ab initio simulations such as density functional theory or path integral Monte Carlo. Interestingly, this new procedure leads to significantly lower density compared to previously used chemical models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Excited electronic states of Na 2 and K 2 : The potential for long-lived “reservoir” states leading to collision induced population inversions

Potential energy curves (PECs) for the spin-free (ΛS) and spin–orbit (Ω) states associated with the four lowest-lying dissociation channels of Na 2 and K 2 were calculated at the SA-CASSCF/SO-CASPT2/aug-cc-pwCVQZ-DK level. The PECs of Na 2 were consistent with the experimental data and with the FS-CCSD (2,0) calculations, reproducing the double-well and the “shelf” character for some of the potentials of the excited states. For K 2 , the PECs behaved in a similar way and the spectroscopic parameters for the ground and the excited states are in good agreement with the available experimental values. The dissociation energy of K 2 was predicted to be D e = 4454 cm −1 , within an agreement of 5 cm −1 with the experiments. For Na 2 , D e = 5789 cm −1 compared to the experimental value of 6022 cm −1 . The inclusion of spin–orbit coupling effects resulted in avoided crossings, which affect the PECs. Spin–orbit changes the predicted curves for some excited Ω states arising from ΛS states that overlap each other, affecting their associated vibrational frequencies and bond distances. Here, the current studies of the low-lying states in K 2 reveal a similar structure to those of Na 2 , which suggests the accessibility of long-lived energy storing reservoir states and possible population inversions in K 2 following prior experimental work on the reaction of halogen atoms with Na 3 to produce excited states of Na 2 .

Ab-initio methods

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE

Accurate and efficient parameterization of an atomic cluster expansion (ACE) potential for ammonia under extreme conditions

We present a machine learning interatomic potential for ammonia designed to capture its complex multiphase behavior, including both molecular and superionic phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to facilitate high-fidelity molecular dynamics simulations of ammonia under extreme conditions, for pressures up to 100 GPa and for temperatures above 500 K and up to 6000 K. A diverse range of configurations was generated through high-quality ab initio molecular dynamics simulations, covering insulating and superionic ice phases, liquid ammonia, molecular nitrogen (N 2 ) and hydrogen (H 2 ), and metastable compounds that form upon dissociation, including $NH^{+}_{4}$, $H^{+}_{3}$, N 2 H 4 , and N 3 H. We demonstrate that the ammonia ACE potential accurately reproduces experimental and density functional theory predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of ammonia, including the transition from insulating molecular fluid to the superionic phase. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of ammonia under extreme thermodynamic conditions, offering a powerful tool for investigating its behavior in various phases and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

How the choice of exchange–correlation functional affects DFT-based simulations of the hydrated electron

Hydrated electrons are anionic species that are formed when an excess electron is introduced into liquid water. Building an understanding of how hydrated electrons behave in solution has been a long-standing effort of simulation methods, of which density functional theory (DFT) has come to the fore in recent years. The ability of DFT to model the reactive chemistry of hydrated electrons is an attractive advantage over semi-classical methodologies; however, relatively few density functional approximations (DFAs) have been used for the hydrated electron simulations presented in the literature. Here, we simulate hydrated electron systems using a series of exchange–correlation (XC) functionals spanning Jacob’s ladder. We calculate a variety of experimental and other observables of the hydrated electron and compare the XC functional dependence for each quantity. We find that the formation of a stable localized hydrated electron is not necessarily limited to hybrid XC functionals and that some hybrid functionals produce delocalized hydrated electrons or electrons that react with the surrounding water at an unphysically fast rate. Here, we further characterize how different DFAs impact the solvent structure and predicted spectroscopy of the hydrated electron, considering several methods for calculating the hydrated electron’s absorption spectrum for the best comparison between structures generated using different density functionals. None of the dozen or so DFAs that we investigated are able to correctly predict the hydrated electron’s spectroscopy, vertical detachment energy, or molar solvation volume.

Ab-initio molecular dynamics

GPU acceleration of hybrid functional calculations in the SPARC electronic structure code

We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing hybrid functional calculations in generalized Kohn–Sham density functional theory. In particular, we develop a batch variant of the recently formulated Kronecker product-based linear solver for the simultaneous solution of multiple linear systems. We then develop a modular, math kernel based implementation for hybrid functionals on NVIDIA architectures, where computationally intensive operations are offloaded to the GPUs, while the remaining workload is handled by the central processing units (CPUs). Considering bulk and slab examples, we demonstrate that GPUs enable up to 8× speedup in node-hours and 80× in core-hours compared to CPU-only execution, reducing the time to solution on V100 GPUs to around 300 s for a metallic system with over 6000 electrons, and significantly reducing the computational resources required for a given wall time.

Kohn-Sham density functional theory

Infrared spectral signatures of interfacial water at TiO 2 –electrolyte interfaces from deep potential molecular dynamics

Vibrational spectroscopy is a powerful tool for probing water at oxide–electrolyte interfaces, but its molecular interpretation can be challenging. Here, we employ deep potential long-range molecular dynamics simulations with layer-resolved spectral analysis to investigate the microscopic origins of the infrared (IR) response of water at the interface with anatase TiO 2 (101), a prototypical oxide surface. The calculated interfacial spectra exhibit characteristic modifications compared to bulk water IR spectra, including enhanced intensities, a red shifted and broadened stretching band, and a higher-frequency shoulder, in qualitative agreement with experiments. Spectral decomposition shows that these signatures originate mainly from the first interfacial water layer, dominated by surface-bound H 2 O at Ti 5C sites, with secondary contributions from the second layer. A moderate salt concentration (0.4 M NaCl) leaves both the interfacial structure and the spectra essentially unchanged, while tuning the pH strongly modulates the spectral intensity. We establish a scaling relation linking the spectral intensity to the surface water dissociation fraction and the dipole moment, both governed by interfacial electric fields. These findings provide a microscopic framework for interpreting IR spectra of oxide–electrolyte interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH