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Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

All-Atom Biomolecular Simulation in the Exascale Era

Exascale supercomputers have opened the door to dynamic simulations, facilitated by AI/ML techniques, that model biomolecular motions over unprecedented length and time scales. This new capability holds the potential to revolutionize our understanding of fundamental biological processes. Herein we report on some of the major advances that were discussed at a recent CECAM workshop in Pisa, Italy, on the topic with a primary focus on atomic-level simulations. First, we highlight examples of current large-scale biomolecular simulations and the future possibilities enabled by crossing the exascale threshold. Next, we discuss challenges to be overcome in optimizing the usage of these powerful resources. Finally, we close by listing several grand challenge problems that could be investigated with this new computer architecture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A model for trapping and re-solution regarding intra-granular bubbles in UO 2 , linked to atomic-scale simulations

In the literature, a clear definition of the irradiation re-solution frequency of gas from bubbles in the UO 2 fuel is absent. Moreover, for intra-granular bubbles, a detailed calculation of the cumulated displaced gas quantities in function of the distance from the radius of the bubble after a re-solution event has never been published. The assessment of these two elements is very useful if we want to increase the adherence of fission gas release codes to our present knowledge of the behavior of fission gases. Hence, we suggest to link the definition of the re-solution frequency to atomic-scale simulations. Furthermore, we present the cumulated displaced gas quantities obtained from Molecular Dynamics calculations, from which we have derived a re-solution profile that can be exploited to better consider the irradiation re-solution phenomenon inside Fission Gas Release codes. On top of that, we have built a new trapping/re-solution model for intra-granular bubbles linked to Molecular Dynamics simulations that can be easily incorporated into Fission Gas Release codes. In conclusion, we also check that the model is properly built through the comparison of the new model against a reference.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗

Three-Qubit Encoding in Ytterbium-171 Atoms for Simulating 1+1D Quantum Chromodynamics

Simulating nuclear matter described by quantum chromodynamics using quantum computers is notoriously inefficient because of the assortment of quark degrees of freedom such as matter/antimatter, flavor, color, and spin. Here, we propose to address this resource efficiency challenge by encoding three qubits within individual ytterbium-171 atoms of a neutral atom quantum processor. The three qubits are encoded in three distinct sectors: an electronic “clock” transition, the spin-1/2 nucleus, and the lowest two motional states in one radial direction of the harmonic trapping potential. We develop a family of composite sideband pulses and demonstrate a universal gate set and readout protocol for this three-qubit system. We then apply it to single-flavor quantum chromodynamics in 1+1D axial gauge for which the three qubits directly represent the occupancy of quarks in the three colors. We show that two atoms are sufficient to simulate both vacuum persistence oscillations and a screened hadron-number transition. We consider resource requirements and connections to error detection/correction. Our work is a step toward resource-efficient digital simulation of nuclear matter and opens new opportunities for versatile qubit encoding in neutral atom quantum processors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cold-atom quantum simulator for string and hadron dynamics in non-Abelian lattice gauge theory

We propose an analog quantum simulator for simulating real-time dynamics of (1+1)-dimensional non-Abelian gauge theory well within the existing capacity of ultracold-atom experiments. The scheme calls for the realization of a two-state ultracold fermionic system in a one-dimensional bipartite lattice, and the observation of subsequent tunneling dynamics. Being based on the loop string hadron formalism of SU(2) lattice gauge theory, this simulation technique is completely SU(2) invariant and simulates accurate dynamics of physical phenomena such as string breaking and/or pair production. The scheme is scalable and particularly effective in simulating the theory in the weak-coupling regime, and also a bulk limit of the theory in the strong-coupling regime up to certain approximations. This paper also presents a numerical benchmark comparison of the exact spectrum and real-time dynamics of lattice gauge theory to that of the atomic Hamiltonian with an experimentally realizable range of parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

Chemical and steric effects in simulating noncontact atomic force microscopy images of organic molecules on a Cu (111) substrate

Noncontact mode of atomic force microscopy (nc-AFM) employing a CO-functionalized tip is a very powerful tool for studying molecular structures. However, interpreting nc-AFM images for nonplanar molecules can sometimes be problematic. To illustrate and resolve the nature of such problematic systems, we employ real-space pseudopotentials constructed within density functional theory to simulate nc-AFM images. In this work, we focus on several representative nonplanar organic molecules (pentacene, naphthanthrone, olympicene, and 6-phenylhexa-1,3,5-triynybenzene (PHTB)) on a typical substrate: the Cu (111) surface. This substrate results in significant distortions in the molecular geometries of pentacene and naphthanthrone. Including these distortions in simulated nc-AFM imaging notably improves the agreement between the simulated and measured images. In naphthanthrone, the relatively large interaction between the O atom and the Cu substrate offers a straightforward explanation for the absence of the C = O bond in the measured image. Nonplanar features such as tilting or twisting are also apparent in olympicene and PHTB. A “triangular” bright feature associated with the –CH 2 group in olympicene appears in simulated and measured nc-AFM images. This feature is directly related to the tilting angle of the molecule with respect to the Cu substrate. The “defective” benzene ring feature and the faint ellipsoidal C ≡ C feature in PHTB can be ascribed to its twisted nature. The ability to simulate such subatomic images in nc-AFM reflects the accuracy and efficiency of calculating quantum forces in real space.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Molecular Dynamics Simulation of Atomic Interactions in the Vancomycin Binding Site

Vancomycin is a glycopeptide antibiotic produced by Amycolaptopsis orientalis used to treat serious infections by Grampositive pathogens including methicillin-resistant Staphylococcus aureus. Vancomycin inhibits cell wall biosynthesis by targeting lipid II, which is the membrane-bound peptidoglycan precursor. The heptapeptide aglycon structure of vancomycin binds to the D-Ala-D-Ala of the pentapeptide stem structure in lipid II. The third residue of vancomycin aglycon is asparagine, which is not directly involved in the dipeptide binding. Nonetheless, asparagine plays a crucial role in substrate recognition, as the vancomycin analogue with asparagine substituted by aspartic acid (V D ) shows a reduction in antibacterial activities. To characterize the function of asparagine, binding of vancomycin and its aspartic-acid-substituted analogue V D to L-Lys-D-Ala-D-Ala and L-Lys-D-Ala-D-Lac was investigated using molecular dynamic simulations. Binding interactions were analyzed using root-mean-square deviation (RMSD), two-dimensional (2D) contour plots, hydrogen bond analysis, and free energy calculations of the complexes. The analysis shows that the aspartate substitution introduced a negative charge to the binding cleft of V D , which altered the aglycon conformation that minimized the repulsive lone pair interaction in the binding of a depsipeptide. Our findings provide new insight for the development of novel glycopeptide antibiotics against the emerging vancomycin-resistant pathogens by chemical modification at the third residue in vancomycin to improve its binding affinity to the D-Ala-D-Lac-terminated peptidoglycan in lipid II found in vancomycin-resistant enterococci and vancomycinresistant S. aureus.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ORNL_AISD-Ex: Quantum chemical prediction of UV/Vis absorption spectra for over 10 million organic molecules

We performed calculations of electronic excitation energies and associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method [1]. The SMILES (Simplified molecular-input line-entry system) strings of the molecules from the AISD HOMO-LUMO database [2] were converted to a 3D atomistic structure and stored in a PDB file after preliminary geometry optimization using the Merck Molecular Force Field (MMFF94) in RDKit [3,4]. The primary information stored in the PDB file archive consists of Cartesian coordinates for each atom of the molecule in their 3D location in space, along with summary information about the structure, sequence, and experiment. We then performed molecular geometry optimization using the density-functional tight-binding (DFTB) method [5] in the electronic ground state, followed by single-point excited states calculations, as described below. We note that, since RDKit employs a random choice for the generation of molecular conformers, the molecular geometries obtained in this dataset could be different from the ones that were generated when the AISD HOMO-LUMO dataset was generated. The computed excitation energies and associated oscillator strengths can be converted to predict UV/Vis absorption spectra, where excitation energies correspond to absorption peak positions, and oscillator strengths are a good measure of the probability of absorption of visible or UV light in transitions between electronic ground and excited states. The conversion of SMILES strings to 3D Cartesian coordinates of fully DFTB-optimized molecules was successful for 10,502,904 out of 10,502,917 molecules. For these molecules, both geometry optimizations and excited states calculations were successful. The DFTB calculations did not complete for 13 molecules of the original AISD HOMO-LUMO dataset. We still provide information about the geometry of these molecules. The molecules are diverse for chemical compositions (which span 5 non-hydrogen elements: oxygen, carbon, nitrogen, fluorine, sulfur) and molecular size (the smallest molecule contains 5 non-hydrogen atoms, and the largest molecule contains 71 non-hydrogen atoms). The DFTB method [5] is an approximation to density functional theory (DFT), utilizing a minimal basis set in conjunction with a two-center approximation to the electronic Hamiltonian and overlap matrix elements. The DFTB total energy is the sum of an electronic and a repulsive energy contribution, and their calculation requires optimized electronic parameters and diatomic repulsive potential energy functions. All DFTB calculations were performed using the DFTB+ code [6] (version 21.2) and the wrapper for DFTB+ in the Atomic Simulation Environment (ASE) (version 3.22.1) [7], which performed an internal conversion of Cartesian coordinates from PDB to the .gen file format. For the geometry optimizations on the electronic ground state potential energy surface of the molecules, we have chosen the third-order DFTB (DFTB3) method [5c] and employed the matching 3ob set of electronic parameters and repulsive potentials [8]. The empirical γ-damping for hydrogen bond correction, and Grimme's D3 empirical dispersion correction with Becke-Johnson damping (D3(BJ)) [9] dispersion correction was included to improve the description of non-covalent interactions. For excited states single-point energy calculations, we employed the TD-DFTB method in conjunction with the DFTB2 method [5b] and the matching mio [5b,10] and halorg [11] parameter sets. We opted to request the simultaneous calculation of 50 excited states for singlet transition to investigate sufficient number of excited states, based on linear response theory using the Casida equation [Ref: T. A. Niehaus, S. Suhai, F. Della Sala, P Lugli, M. Elstner, G. Seifert, and Th. Frauenheim. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 63:085108, 2001] and the ARPACK diagonalizer [R. B. Lehoucq, D. C. Sorensen, and C. Yang. Arpack users guide: Solution of large-scale eigenvalue problems by implicitly restarted arnoldi methods, 1997. 46, 51]. The dataset contains 1001 tar.gz files. Tar files are named as “ornl_aisd_ex_1.tar.gz†through “ornl_aisd_ex_1000.tar.gzâ€. Additionally, the 13 failed molecules are in “ornl_aisd_ex_unprocessed.tar.gzâ€. Except for the tar files listed below, each tar file contains 10,500 molecules. Tar files numbered 34, 121, 128, 352, 360, 429, 495, 509, 518, 627, 676, 668, and 862 contain 10,499 molecules each. The last tar file numbered 1000 contains 13,417 molecules. The total size of the uncompressed dataset is over 283 Gigabytes. The code for calculating the electronic excitation energies and statistical analysis of the dataset is provided at the following GitLab repository: https://github.com/ORNL/Analysis-of-Large-Scale-Molecular-Datasets-with-Python Calculating the UV spectrum of a molecule requires performing 3 main operations: 1. Converting the smiles string representation of a molecule into a geometric structure where each atom is assigned XYZ coordinates. The geometric structure is written to the file smiles.pdb. 2. Using smiles.pdb to compute the relaxed geometry of the molecule, which corresponds with the position of the atoms at the position of equilibrium at the ground state. This generates the files band.out, detailed.out, and geo_end.gen. 3. Using geo_end.gen to calculate the UV spectrum of the molecule which is written into the file EXC.DAT. Every molecule in the dataset has its own directory. The files contained in each molecule directory are as follows: 1. geo_end.gen 2. detailed.out 3. band.out 4. EXC.DAT 5. smiles.pdb REFERENCES [1] Niehaus, T. A.; Suhai, S.; Della Salla, F.; Lugli, P.; Elstner, M.; Seifert, G.; Frauenheim, Th. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 2001, 63, 085108/1-9. [2] Blanchard, A.; Gounley, J.; Metha, K.; Yoo, P.; Irle, S. AISD HOMO-LUMO. DOI: 10.13139/ORNLNCCS/1869409 [3] RDKit: Cheminformatics and Machine Learning Software. 2013, [http://www.rdkit.org] [4] Tosco, P.; Stiefl, N. and Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. J Cheminform. 2014, 6, 1–4. [5] a) Porezag, D.; Frauenheim, T.; Kohler, T.; Seifert, G.; Kaschner, Construction of tight-binding-like potentials on the basis of density-functional theory: Application to carbon, R. Phys. Rev. B 1995, 51, 12947-12957; b) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, Th.; Suhai, S.; Seifert, G.; Phys. Rev. B 1998, 58, 7260-7268; c) Gaus, M.; Cui, Q.; Elstner, M. DFTB3: Extension of the Self-Consistent-Charge Density-Functional Tight-Binding Method (SCC-DFTB), J. Chem. Theory Comput. 2011, 7, 931-948; d) Cui, Q.; Elstner, M. Density functional tight binding: values of semi-empirical methods in an ab initio era, Phys. Chem. Chem. Phys. 2014, 16, 14368-14377. [6] Hourahine, B. et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 2020, 152, 124101/1-19. [7] Larsen, A. H. et al. The atomic simulation environment—a Python library for working with atoms. J. Phys.: Cond. Matter 2017, 29, 273002. [8] Kubillus, M.; Kubar, T.; Gaus, M.; Rezac, J.; Elstner, M. Parameterization of the DFTB3 Method for Br, Ca, Cl, F, I, K, and Na in Organic and Biological Systems, J. Chem. Theory Comput. 2015, 11, 332-342. [9] Brandenburg, J. G.; Grimme, S. Accurate Modeling of Organic Molecular Crystals by Dispersion-Corrected Density Functional Tight Binding (DFTB), J. Phys. Chem. Lett. 2014, 5, 1785−1789. [10] a) Niehaus, T. A.; Elstner, M.; Frauenheim, Th.; Suhai, S. Application of an approximate density-functional method to sulfur containing compounds. J. Mol. Struct.: THEOCHEM 2001, 541, 185-94; b) Elstner, M.; Hobza, P.; Frauenheim, Th.; Suhai, S.; Kaxiras, E. Hydrogen bonding and stacking interactions of nucleic acid base pairs: A density-functional-theory based treatment. J. Chem. Phys. 2001, 114, 5149-55. [11] Kubar, T.; Bodrog, Z.; Gaus, M.; Köhler, C.; Aradi, B.; Frauenheim, Th.; Elstner, M. Parametrization of the SCC-DFTB Method for Halogens. J. Chem. Theory Comput. 2013, 9, 2939-49.

36 MATERIALS SCIENCE↗

Simulating quantum mechanics with a $\theta$-term and an ’t Hooft anomaly on a synthetic dimension

A topological θ-term in gauge theories, including quantum chromodynamics in 3 +1 dimensions, gives rise to a sign problem that makes classical Monte Carlo simulations impractical. Quantum simulations are not subject to such sign problems and are a promising approach to studying these theories in the future. In the near term, it is interesting to study simpler models that retain some of the physical phenomena of interest and their implementation on quantum hardware. For example, dimensionally reducing gauge theories on small spatial tori produces quantum mechanical models which, despite being relatively simple to solve, retain interesting vacuum and symmetry structures from the parent gauge theories. We consider quantum mechanical particle-on-a-circle models, related by dimensional reduction to the 1 + 1d Schwinger model, that possess a θ-term and realize an ’t Hooft anomaly or global inconsistency at θ = π. These models also exhibit the related phenomena of spontaneous symmetry breaking and instanton-anti-instanton interference in real time. We propose an experimental scheme for the real-time simulation of a particle on a circle with a θ-term and a $\mathbb{Z}_n$ potential using a synthetic dimension encoded in a Rydberg atom. Simulating the Rydberg atom with realistic experimental parameters, we demonstrate that the essential physics can be well captured by the experiment, with expected behavior in the tunneling rate as a function of θ. Similar phenomena and observables can also arise in more complex quantum mechanical models connected to higher-dimensional non-Abelian gauge theories by dimensional reduction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

Molecular dynamics study of silicon atomic layer etching by chlorine gas and argon ions

Classical molecular dynamics (MD) is used to simulate atomic layer etching processes of silicon by alternating exposure to chlorine gas and argon ions. In order to validate our model, a rigorous comparison is done with ion beam experiments found in the literature [Park et al., Jpn. J. Appl. Phys. 44, 389 (2005)]. Here it is shown that the etch per cycle (EPC) as a function of argon ion energy from simulations is in quantitative agreement with experimental results if the correct argon ion fluence is used in the simulations. The EPC as a function of ion irradiation time and amount of chlorine exposure also show good agreement with the experiment. The MD simulations also show the formation of an amorphous silicon region with chlorine atoms mixed uniformly throughout following ion bombardment. Finally, the etch products during the ion irradiation step are analyzed and discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. Here, in this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

42 ENGINEERING↗

ase

[Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/): A Python library for working with atoms

Mazeau, EmilyJ [Oak Ridge National Lab. (ORNL), Oa↗

Electronic effects in radiation-induced collision cascades in nickel

The accurate treatment of electronic effects in multi-million-atom simulations of radiation-induced collision cascades is crucial for reliable predictions of primary radiation damage. In this work, we explore the fidelity of a recently developed two-temperature molecular dynamics model implementing an electron density-dependent coupling of electronic and atomic subsystems for cascade simulations in nickel. We show that the parameter-free model realistically captures the instantaneous energy losses during all stages of the highly nonequilibrium cascade process. Our simulations predict two distinct coupling regimes, corresponding to the rapid energy losses through electronic stopping in the early stages of the cascade and to the slow equilibration through the electron-phonon coupling mechanism in the later stages, without the use of separate models or coupling terms. The intermediate stage of the cascade dynamics displays a complex energy transfer between the subsystems, which cannot be interpreted by comparison to either electronic stopping or electron-phonon coupling theories. We therefore compare the predicted atomic mixing, which is sensitive to the energy losses during the intermediate cascade stage, with experimental ion beam mixing measurements. We find good agreement with the experiments, validating the coupling model for the intermediate stage of the cascade. Predictions of final defect numbers and cluster sizes are found in line with the results from conventional electronic stopping-based methods, while significantly reducing the theoretical uncertainty in the outcomes of conventional models stemming from arbitrary choices of thresholds for different coupling terms. Our results represent a notable improvement in cascade damage predictions in nickel, providing validation of the electron density-dependent coupling model for radiation damage simulations in general. The results lead us to propose an interpretation of the electronic energy losses in the intermediate regime of velocities, where we find an effectively nonlinear dissipation.

Crystal defects↗

Nanocrystal programmable assembly beyond hard spheres (or shapes) and other (simple) potentials

Ligands are the key to almost any strategy in the assembly of programmable nanocrystals (or nanoparticles) and must be accurately considered in any predictive model. Hard Spheres (or Shapes) provide the simplest and yet quite successful approach to assembly, with remarkable sophisticated predictions verified in experiments. There are, however, many situations where hard spheres/shapes predictions fail. This prompts three important questions: In what situations should hard spheres/shapes models be expected to work? and when they do not work, Is there a general model that successfully corrects hard sphere/shape predictions? and given other successful models where ligands are included explicitly, and of course, numerical simulations, can we unify hard sphere/shape models, explicit ligand models and all atom simulations? . Further, the Orbifold Topological Model (OTM) provides a positive answer to these three questions. In this paper, I give a detailed review of OTM, describing the concept of ligand vortices and how it leads to spontaneous valence and nanoparticle “eigenshapes” while providing a prediction of the lattice structure, without fitting parameters, which accounts for many body effects not captured by (two-body) potentials. I present a thorough survey of experiments and simulations and show that, to this date, they are in full agreement with the OTM predictions. I conclude with a discussion on whether NC superlattices are equilibrium structures and some significant challenges in structure prediction.

36 MATERIALS SCIENCE↗