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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prediction of dislocation - grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods

Mechanical properties of metals such as strength and toughness are strongly correlated to complex interactions between various defects in the crystalline structure. While elementary interactions between these defects have been investigated using recent micro- and nano-characterization techniques, understanding of the detailed interaction mechanisms has hardly been obtained. To understand defect-driven plasticity at various time and length scales, it is necessary to formulate a general guideline to predict both the interaction type (transmission or reflection) and the dislocation's subsequent slip system after the interaction. Many criteria based on the geometric alignment of the defects have been developed to predict this phenomenon, but these have yet to be found to be accurate when applied to general data sets of grain boundaries (GBs). With this motivation, we conduct a systematic study using molecular dynamics (MD) models of bicrystals to analyze defect interaction process between a prismatic dislocation loop and eleven different grain boundaries of the following character: three tilt, three twist, and five mixed. Based on the MD observations, two new prediction methods are developed: the first is a new data-driven parametric score function based on the classical geometric criteria, and the second is by applying Gaussian process machine learning methods to find the probability distribution of a hidden function. In conclusion, the proposed data-driven prediction methods could pave a new way to predict the unit interaction of dislocations with various GBs, which could show much higher accuracy compared to pre-existing geometric criteria.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theoretical Examination of the Hydroxide Transport in Cobaltocenium-Containing Polyelectrolytes

Polymers incorporating cobaltocenium groups have received attention as promising components of anion-exchange membranes (AEMs), exhibiting a good balance of chemical stability and high ionic conductivity. In this work, we analyze the hydroxide diffusion in the presence of cobaltocenium cations in an aqueous environment based on the molecular dynamics of model systems confined in one dimension to mimic the AEM channels. In order to describe the proton hopping mechanism, the forces are obtained from the electronic structure computed at the density-functional tight-binding level. We find that the hydroxide diffusion depends on the channel size, modulation of the electrostatic interactions by the solvation shell, and its rearrangement ability. Hydroxide diffusion proceeds via both the vehicular and structural diffusion mechanisms with the latter playing a larger role at low diffusion coefficients. The highest diffusion coefficient is observed under moderate water densities (around half the density of liquid water) when there are enough water molecules to form the solvation shell, reducing the electrostatic interaction between ions, yet there is enough space for the water rearrangements during the proton hopping. Furthermore, the effects of cobaltocenium separation, orientation, chemical modifications, and the role of nuclear quantum effects are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Meta-Generalized Gradient Approximation for the Cavity-Dependent Exchange-Correlation Interaction in Strongly Coupled Light–Matter Systems

Strong light–matter coupling in optical cavities enables the manipulation of chemical and physical properties without altering molecular composition. Theoretical modeling of such phenomena requires exchange-correlation (XC) functionals that account for both electron–electron and electron–photon (ep) interactions within quantum electrodynamical density functional theory (QEDFT). In this work, we develop a meta-generalized gradient approximation (meta-GGA) specifically targeting the cavity-dependent XC interaction in strongly coupled light–matter systems. This novel approximation is built upon a new semilocal polarizability approximation, which draws from the jellium-with-a-gap model, and can be extended to a “global hybrid” variant that goes beyond the isotropic model from previous approximations. The polarizability model yields significantly improved dispersion coefficients and benchmark calculations with the cavity-dependent XC functional demonstrate improved agreement with QED Hartree–Fock (QED-HF) reference energies. Application to the regioselectivity of brominated nitrobenzene intermediates reveals the functional’s capacity to capture cavity-induced energetic shifts. In conclusion, our results advance the Jacob’s ladder of functionals for QEDFT and provide a practical tool for modeling polaritonic chemistry.

Approximation↗
DOE OSTI2020

Role of Intact Hydrogen-Bond Networks in Multiproton-Coupled Electron Transfer

The essential role of a well-defined hydrogen-bond network in achieving chemically reversible multiproton translocations triggered by one-electron electrochemical oxidation/reduction is investigated by using pyridylbenzimidazole–phenol models. The two molecular architectures designed for these studies differ with respect to the position of the N atom on the pyridyl ring. In one of the structures, a hydrogen-bond network extends uninterrupted across the molecule from the phenol to the pyridyl group. Experimental and theoretical evidence indicates that an overall chemically reversible two-protoncoupled electron-transfer process (E2PT) takes place upon electrochemical oxidation of the phenol. This E2PT process yields the pyridinium cation and is observed regardless of the cyclic voltammogram scan rate. In contrast, when the hydrogen-bond network is disrupted, as seen in the isomer, at high scan rates (~1000 mV s –1 ) a chemically reversible process is observed with an E 1/2 characteristic of a one-proton-coupled electron-transfer process (E1PT). At slow cyclic voltammetric scan rates (<1000 mV s –1 ) oxidation of the phenol results in an overall chemically irreversible two-proton-coupled electron-transfer process in which the second proton-transfer step yields the pyridinium cation detected by infrared spectroelectrochemistry. In this case, we postulate an initial intramolecular proton-coupled electron-transfer step yielding the E1PT product followed by a slow, likely intermolecular chemical step involving a second proton transfer to give the E2PT product. Insights into the electrochemical behavior of these systems are provided by theoretical calculations of the electrostatic potentials and electric fields at the site of the transferring protons for the forward and reverse processes. Furthermore, this work addresses a fundamental design principle for constructing molecular wires where protons are translocated over varied distances by a Grotthuss-type mechanism.

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

Ga + -Chabazite Zeolite: A Highly Selective Catalyst for Nonoxidative Propane Dehydrogenation

Ga-chabazite zeolites (Ga-CHA) have been found to efficiently catalyze propane dehydrogenation with high propylene selectivity (96%). In situ FTIR spectroscopy and pulse titrations are employed to determine that upon reduction, surface Ga 2 O 3 is reduced and diffuses into the zeolite pores, displacing the Brønsted acid sites (BAS) and forming extra-framework Ga + sites. This isolated Ga + site reacts reversibly with H 2 to form GaHx (2034 cm -1 ) with an enthalpy of formation of ~ -51.2 kJ·mol -1 , a result supported by Density functional theory (DFT) calculations. The initial C 3 H 6 dehydrogenation rates decrease rapidly (40%) during the first 100 min and then decline slowly afterward, while the C 3 H 6 selectivity is stable at ~ 96%. The reduction in the reaction rate is correlated with the formation of polycyclic aromatics inside the zeolite (using UV-vis spectroscopy) indicating that the accumulation of polycyclic aromatics is the main cause of the deactivation. The carbon species formed can be easily oxidized at 600 °C with complete recovery of the PDH catalytic properties. The correlations between GaH x vs. Ga/Al ratio, and PDH rates vs. Ga/Al ratio show that extra-framework Ga + is the active center catalyzing propane dehydrogenation. The higher reaction rate on Ga + than In + in CHA zeolites, by a factor of 43, is the result of differences in the stabilization of the transition state due to the higher stability of Ga 3+ vs. In 3+ . The uniformity of the Ga + sites in this material makes it an excellent model for the molecular understanding of metal cation exchanged hydrocarbon interactions in zeolites.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Development of facile approaches to convert plastic waste into liquid fuels under neat conditions is highly desired but challenging, particularly without noble metal catalysts and an external hydrogen source. Herein, highly efficient and selective polyethylene-to-gasoline oil (branched C 6 –C 12 alkanes) conversion was achieved under mild conditions (<170 °C) using commercially available AlCl 3 -containing molten salts as reaction media and to provide catalytic sites (no extra solvents, additives, or hydrogen feeding). The high catalytic efficiency and selectivity was ensured by the abundant active Al sites with strong Lewis acidity (comparable to the Al type in acidic zeolite) and highly ionic nature of the molten salts to stabilize the carbenium intermediates. Dynamic genesis of the Al sites was elucidated via time-resolved Al K-edge soft X-ray and 27 Al NMR, confirming the tricoordinated Al 3+ as active sites and its coordination with the as-generated alkene/aromatic intermediates. Further, the carbenium formation and polyethylene chain variation was illustrated by inelastic neutron scattering (INS) and an isotope-labeling experiment. Theoretical simulations further demonstrated the successive hydride abstraction, β-scission, isomerization, and internal hydrogen transfer reaction pathway with AlCl 3 as active sites. This facile catalytic system can further achieve the conversion of robust, densely assembled, and high molecular weight plastic model compounds to liquid alkane products in the diesel range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dislocation-Grain Boundary Interaction Dataset for FCC Cu

Interactions between dislocations and grain boundaries play a major role in controlling the strength and ductility of structural materials. Experimentally, assessing and probing geometric and stress-based criteria at the local level for dislocation transmission through grain boundaries remains challenging. Therefore, there have been many efforts to systematically generate datasets of dislocation-grain boundary interactions (DGI) via computational models such as molecular dynamics simulations. So far, most DGI datasets have focused only on the subset of nominal minimum-energy grain boundary structures, which limits their applicability, especially to materials processed far from equilibrium. We present a comprehensive database of dislocation-grain boundary interactions for edge, screw, and 60° mixed dislocation with 330 <110> and 257 <112> symmetric tilt grain boundaries (total of 587) in FCC Cu consisting of 73 minimum-energy grain boundary structures and 514 metastable structures. The dataset contains the outcomes for 5234 unique interactions for various dislocation types, grain boundary structures, and applied shear stresses.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multifunctional textured graphene-based coatings on elastomeric gloves for chemical protection

Nanotechnology offers a variety of new tools for the design of next-generation personal protective equipment (PPE). One example is the use of two-dimensional materials as coatings that enhance the performance and ergonomics of elastomeric gloves designed to protect users from hazardous chemicals. Desirable features in such coatings may include molecular barrier function, liquid droplet repellency, stretchability for compatibility with the elastomer, breathability, and an ultrathin profile that preserves the user's manual dexterity and tactile sensation. The present work explores the potential of engineered graphene-based films with out-of-plane texturing as a novel platform to meet these multifold requirements. Graphene-based films in different formulations were fabricated from water-borne inks by vacuum filtration and solution casting methods on glove-derived nitrile rubber substrates. The various coatings were then subjected to tests of molecular permeation by model volatile organic compounds, droplet contact angle, breathability, and mechanical stability during stretching and solvent immersion. The films dramatically improve the barrier properties of glove-derived nitrile. The out-of-plane graphene texturing imparts stretchability through microscale folding/unfolding, while also enhancing droplet repellency in some cases through a lotus-like roughening effect. The combined results suggest that engineered textured graphene-based films are a promising platform for creating multifunctional coatings for a next generation of chemically protective gloves and other elastomer-based PPE.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scaling of silicon nanoparticle growth in low temperature flowing plasmas

Low temperature plasmas are an emerging method to synthesize high quality nanoparticles (NPs). An established and successful technique to produce NPs is using a capacitively coupled plasma (CCP) in cylindrical geometry. Although a robust synthesis technique, optimizing or specifying NP properties using CCPs, is challenging. In this paper, results from a computational investigation for the growth of silicon NPs in flowing inductively coupled plasmas (ICPs) using Ar/SiH 4 gas mixtures of up to a few Torr are discussed. ICPs produce more locally constrained and quiescent plasma potentials. These positive plasma potentials produce an electrostatic trap for negatively charged NPs, which can significantly extend the residence time of NPs in the plasma, which in turn provides a controllable period for particle growth. The computational platforms used in this study consist of a two-dimensional plasma hydrodynamics model, a three-dimensional nanoparticle growth and trajectory tracking model, and a molecular dynamics simulation for deriving reactive sticking coefficients of silane radicals on Si NPs. Trends for the nanoparticle growth as a function of SiH 4 inlet fraction, gas residence time, energy deposition per particle, pressure, and reactor diameter are discussed. The general path for particle synthesis is the trapping of small NPs in the positive electrostatic potential, followed by entrainment in the gas flow upon reaching a critical particle size. Optimizing or controlling NP synthesis then depends on the spatial distribution of plasma potential, the density of growth species, and the relative time that particles spend in the electrostatic trap and flowing through higher densities of growth species upon leaving the trap.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data

In this work, we present a machine learning approach to calculating electronic specific heat capacities for a variety of benchmark molecular systems. Our models are based on data from density matrix quantum Monte Carlo, which is a stochastic method that can calculate the electronic energy at finite temperature. As these energies typically have noise, numerical derivatives of the energy can be challenging to find reliably. In order to circumvent this problem, we use Gaussian process regression to model the energy and use analytical derivatives to produce the specific heat capacity. From there, we also calculate the entropy by numerical integration. We compare our results to cubic splines and finite differences in a variety of molecules in which Hamiltonians can be diagonalized exactly with full configuration interaction. We finally apply this method to look at larger molecules where exact diagonalization is not possible and make comparisons with more approximate ways to calculate the specific heat capacity and entropy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Bayesian inference of nuclear incompressibility from collective flow in mid-central Au+Au collisions at 400–1500 MeV/nucleon

The incompressibility K of symmetric nuclear matter (SNM) is determined through a Bayesian analysis of collective flow data from Au + Au collisions at beam energies $E = 400 -1500$ MeV/nucleon. This analysis utilizes a Gaussian process (GP) emulator applied to the isospin-dependent quantum molecular dynamics (IQMD) model for heavy-ion collisions, both with and without incorporating the momentum dependence of the single-nucleon potentials. Specifically, at the 68% confidence level, using rapidity and transverse velocity dependence of proton elliptic flow data with and without consideration of the momentum dependence, the inferred incompressibility values are $K=188.9^{+2.9}_{-4.5}$ MeV and $256.1^{+8.2}_{-8.7}$ MeV at $E = 400$ MeV/nucleon, respectively. When the transverse momentum dependence of proton-like directed flow data is included, the inferred incompressibility values become $K=222.3^{+9.0}_{-9.9}$ MeV and $K=285.5^{+6.7}_{-7.3}$ MeV, respectively. Furthermore, we found that the value of K derived from observables of proton elliptic flow increases with beam energy. Finally, this indicates that the equation of state (EoS) of nuclear matter hardens at higher densities and temperatures in reactions with higher beam energies.

Bayesian inference↗
DOE OSTI2026

Measurement of fifth- and sixth-order fluctuations of (net-)proton number in Au + Au collisions from phase II of the beam energy scan program at RHIC

We report high-statistics measurements of fifth- and sixth-order factorial cumulants and cumulant ratios of (net-)proton multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7–27GeV, using data from the STAR experiment collected during the Beam Energy Scan Phase II at RHIC. Protons and antiprotons are identified at midrapidity (|𝑦| < 0.5) with transverse momentum 0.4 < 𝑝 𝑇 < 2.0GeV/𝑐. The proton factorial cumulants 𝜅 4 , 𝜅 5 , and 𝜅 6 increase with order but exhibit no sign alternation within current uncertainties, offering no evidence for a two-component structure in the proton multiplicity distribution, as might be expected near a first-order phase transition. The cumulant ratios 𝐶 5 /𝐶 1 and 𝐶 6 /𝐶 2 fluctuate around zero in collisions at 0–40% centrality. The results are consistent with both the negative predictions from lattice QCD and the positive trends obtained from the ultrarelativistic quantum molecular dynamics (UrQMD) model. At $\sqrt{s_{NN}}$ ≳ 27GeV, the 𝐶 4 /𝐶 2 and 𝐶 5 /𝐶 1 results are compatible with predictions from lattice QCD, functional renormalization group (FRG), and hadron resonance gas (HRG) models, while UrQMD describes the data better at lower energies. Here, these measurements place constraints on baryon number fluctuations and offer valuable insights into the QCD phase structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Localized basis set for plutonium

The implementation of optimal strictly localized atomic orbitals basis for plutonium (Pu) using norm-conserving pseudopotential density-functional theory (DFT) is presented. The basis set was applied to the α, β, γ, δ, δ', and ε phases of Pu, δ-Pu surface, and δ-PuGa alloys. The computed properties of the Pu phases and δ-Pu surface were in good agreement with both available experimental data and prior DFT calculations based on plane-wave methodologies. Results for the δ-PuGa alloys were also in good agreement with experimental data. Finally, the reliability of the basis set was further demonstrated by using ab initio molecular dynamics to model the diffusion coefficient and activation barrier for atomic diffusion in a δ-PuGa alloy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Pressure-induced polyamorphic transition in CaA l 2 O 4 glass

In situ high-pressure ultrasonic velocity measurements of CaAl 2 O 4 glass reveal abrupt irreversible discontinuities in the elastic wave velocities at ~8–10 GPa. Total structure factor and pair distribution functions measured by synchrotron x-ray diffraction show a rapid change in the intermediate range structure attributed to a rearrangement of calcium ions over this narrow pressure region. Atomistic models obtained from molecular dynamics simulations reveal that this intermediate range structure is explained by a transition of Ca–O void radius distribution from a bimodal distribution with peaks at ~2.1 and ~2.4 Å to a single distribution centered at ~2.1 Å. Further, these abrupt structural changes involving the rapid increase in elastic wave velocity are markedly different to the continuous transformations observed in conventional network-forming glasses, such as SiO 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Search for in-band transitions in the candidate superdeformed band in Si 28

Background: Superdeformed (SD) bands are suggested by theory around Ca 40 and in lighter alpha-conjugate nuclei such as Mg 24 , Si 28 , and S 32 . Such predictions originate from a number of theoretical models including mean-field models and antisymmetrized molecular dynamics (AMD) calculations. While SD bands have been identified in Ca 40 and its near neighbors, evidence of their existence in the lighter, midshell nuclei is circumstantial at best. Additionally, the key evidence of superdeformation would be the observation of transitions with high B ( E 2 ) transition strengths connecting states in a rotational sequence. This is challenging information to obtain since the bands lie at a high excitation energy and competition from out-of-band decay is dominant. Purpose: The purpose of the present study is to establish a new methodology to circumvent the difficulties in identifying and quantifying in-band transitions through directly populating candidate states in the SD band in Si 28 through inelastic alpha scattering, selecting such states with a spectrometer, and measuring their gamma-ray decay with a large array of high-purity germanium detectors, allowing direct access to electromagnetic transition strengths. Methods: Excited states in Si 28 were populated in the Si 28 ( α , α ' ) reaction using a 130-MeV He 4 beam from the K140 AVF cyclotron at the Research Center for Nuclear Physics. Outgoing alpha particles were analyzed using the Grand Raiden spectrometer positioned at an angle of 9 . 1 ° to favor the population of states with J ≈ 4 . Coincident gamma rays were detected with the CAGRA array of 12 HPGe clover detectors augmented by a set of four large LaBr 3 detectors. Results: Data analysis showed that it was possible to identify additional low-energy transitions in competition with high-energy decays from excited states in Si 28 in the vicinity of 10 MeV. However, while the candidate 4 + SD state at 10.944 MeV was populated, a 1148-keV transition to the candidate 2 + SD state at 9.796 MeV was not observed, and only an upper limit for its transition strength of B ( E 2 ) < 43 W.u. could be established. This contradicts AMD predictions of ≈ 200 W.u. for such a transition. Conclusion: The present study strongly rejects the hypothesis that the candidate set of states identified in Si 28 represents an SD band, which demonstrates the potential of the methodology devised here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Impact of fragment formation on shear viscosity in the nuclear liquid-gas phase transition region

Within the improved quantum molecular dynamics (ImQMD) model we follow the evolution of nuclear matter for planar Couette flow in a periodic box. We focus on the region of liquid-gas phase transition and extract the shear viscosity coefficient from the local stress tensor, directly following the viscosity definition. Here, by switching on and off the mean field and thus inducing the phase transition, we are able to observe the impact of clumping in the phase transition region on the viscosity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗