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

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DOE OSTI2021

Brassica rapa Domestication: Untangling Wild and Feral Forms and Convergence of Crop Morphotypes

The study of domestication contributes to our knowledge of evolution and crop genetic resources. Human selection has shaped wild Brassica rapa into diverse turnip, leafy, and oilseed crops. Despite its worldwide economic importance and potential as a model for understanding diversification under domestication, insights into the number of domestication events and initial crop(s) domesticated in B. rapa have been limited due to a lack of clarity about the wild or feral status of conspecific noncrop relatives. To address this gap and reconstruct the domestication history of B. rapa, we analyzed 68,468 genotyping-by-sequencing-derived single nucleotide polymorphisms for 416 samples in the largest diversity panel of domesticated and weedy B. rapa to date. To further understand the center of origin, we modeled the potential range of wild B. rapa during the mid-Holocene. Our analyses of genetic diversity across B. rapa morphotypes suggest that noncrop samples from the Caucasus, Siberia, and Italy may be truly wild, whereas those occurring in the Americas and much of Europe are feral. Clustering, tree-based analyses, and parameterized demographic inference further indicate that turnips were likely the first crop type domesticated, from which leafy types in East Asia and Europe were selected from distinct lineages. These findings clarify the domestication history and nature of wild crop genetic resources for B. rapa, which provides the first step toward investigating cases of possible parallel selection, the domestication and feralization syndrome, and novel germplasm for Brassica crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Modeling the Performance of an Algebraic Multigrid Cycle Using Hybrid MPI/OpenMP

The rise of multicore cluster architectures has led to intense interest in using a combination of MPI and OpenMP to more effectively program these machines. We present a performance model for hybrid implementation of the solve cycle of algebraic multigrid (AMG), a popular iterative solver for large sparse linear systems and a key component of many scientific simulations. We validate the model on two leading parallel platforms, and discuss implications for applications programmed in a hybrid model on future machines.

Gahvari, Hormozd↗
DOE OSTI2016

Summary of VERA Core Simulator Performance Improvements

This report describes the performance improvements made to the VERA Core Simulator (VERA CS) during FY2016. At the beginning of the year, a timing study was performed to identify areas of the code where the run-times could be improved. This study identified six broad areas for improvement: • Cross section lookup and CMFD stabilization, • CTF parallel partitioning, • MOC methodology, • Subgroup methodology, • MOC parallel partitioning, and • CMFD Krylov solution techniques. The goal of this work was to reduce the VERA-CS run-times so a complete cycle depletion could be run with 1,000 cores overnight (i.e., the “1,000 core depletion” criterion). This goal was set by our industry partners so they could achieve reasonable turnaround on medium-sized computer clusters. The results presented in this report show a code speed-up by a factor of 5, which successfully satisfies the goal set by industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Massively parallel X-ray scattering simulations

Although present X-ray scattering techniques can provide tremendous information on the nano-structural properties of materials that are valuable in the design and fabrication of energy-relevant nano-devices, a primary challenge remains in the analyses of such data. In this paper we describe a high-performance, flexible, and scalable Grazing Incidence Small Angle X-ray Scattering simulation algorithm and codes that we have developed on multi-core/CPU and many-core/GPU clusters. We discuss in detail our implementation, optimization and performance on these platforms. Our results show speedups of ~125x on a Fermi-GPU and ~20x on a Cray-XE6 24-core node, compared to a sequential CPU code, with near linear scaling on multi-node clusters. To our knowledge, this is the first GISAXS simulation code that is flexible to compute scattered light intensities in all spatial directions allowing full reconstruction of GISAXS patterns for any complex structures and with highresolutions while reducing simulation times from months to minutes.

Sarje, Abhinav↗
DOE OSTI2015

Linear-Scaling Coupled Cluster with Perturbative Triple Excitations: The Divide–Expand–Consolidate CCSD(T) Model

Here, we propose a reformulation of the traditional (T) triples correction to the coupled cluster singles and doubles (CCSD) energy in terms of local Hartree–Fock (HF) orbitals such that its structural form aligns with our recently developed linear-scaling divide–expand–consolidate (DEC) coupled cluster family of local correlation methods. In a DEC-CCSD(T) calculation, a basis of local occupied and virtual HF orbitals is used to partition the correlated calculation on the full system into a number of independent atomic fragment and pair fragment calculations, each performed within a truncated set of the complete orbital space. In return, this leads to a massively parallel algorithm for the evaluation of the DEC-CCSD(T) correlation energy, which formally scales linearly with the size of the full system and has a tunable precision with respect to a conventional CCSD(T) calculation via a single energy-based input threshold. The theoretical developments are supported by proof of concept DEC-CCSD(T) calculations on a series of medium-sized molecular systems.

Algorithms↗
DOE OSTI2022

A quantum processor based on coherent transport of entangled atom arrays

The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is key for building scalable quantum information systems. In most state-of-the-art approaches, qubits interact locally, constrained by the connectivity associated with their fixed spatial layout. Here we demonstrate a quantum processor with dynamic, non-local connectivity, in which entangled qubits are coherently transported in a highly parallel manner across two spatial dimensions, between layers of single- and two-qubit operations. Our approach makes use of neutral atom arrays trapped and transported by optical tweezers; hyperfine states are used for robust quantum information storage, and excitation into Rydberg states is used for entanglement generation. We use this architecture to realize programmable generation of entangled graph states, such as cluster states and a seven-qubit Steane code state. Furthermore, we shuttle entangled ancilla arrays to realize a surface code state with thirteen data and six ancillary qubits and a toric code state on a torus with sixteen data and eight ancillary qubits. Finally, we use this architecture to realize a hybrid analogue–digital evolution and use it for measuring entanglement entropy in quantum simulations, experimentally observing non-monotonic entanglement dynamics associated with quantum many-body scars. Realizing a long-standing goal, these results provide a route towards scalable quantum processing and enable applications ranging from simulation to metrology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Water–Hydrocarbon Interactions in Anionic Pyrene Monohydrate

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond timescales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the linewidth and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Furthermore, our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

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

A k-mer based approach for classifying viruses without taxonomy identifies viral associations in human autism and plant microbiomes

Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples, even if they do not have a taxonomy. To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses to create a database of metagenomic viruses. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. We then integrated the viral classification database with databases created with genomes from NCBI for use with ParaKraken (a parallelized version of Kraken provided in Supplemental Zip 1), a metagenomic/transcriptomic classifier. To illustrate the breadth of our utility for classifying metagenome viruses, we analyzed data from a plant metagenome study identifying genotypic and compartment specific differences between two Populus genotypes in three different compartments. We also identified a significant increase in abundance of eight viral sequences in post mortem brains in a human metatranscriptome study comparing Autism Spectrum Disorder patients and controls. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we validate the accuracy of viral classification with NCBI databases containing viruses with taxonomy to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples. Our method represents the compulsory first step in better understanding the role of viruses in the microbiome by allowing for a more complete identification of sequences without taxonomy. Better classification of viruses will improve identifying associations between viruses and their hosts as well as viruses and other microbiome members. Despite the lack of taxonomy, this database of metagenomic viruses can be used with any tool that utilizes a taxonomy, such as Kraken, for accurate classification of viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Parallel Evolution of Chemokine Binding by Structurally Related Herpesvirus Decoy Receptors

A wide variety of pathogens targets chemokine signaling networks in order to disrupt host immune surveillance and defense. Here, we report a structural and mutational analysis of rodent herpesvirus Peru encoded R17, a potent chemokine inhibitor that sequesters CC and C chemokines with high affinity. R17 consists of a pair of β-sandwich domains linked together by a bridging sheet, which form an acidic binding cleft for the chemokine CCL3 on the opposite face of a basic surface cluster that binds glycosaminoglycans. R17 promiscuously engages chemokines primarily through the same N-loop determinants used for host receptor recognition while residues located in the chemokine 40s loop drive kinetically stable complex formation. Here, the core fold adopted by R17 is unexpectedly similar to that of the M3 chemokine decoy receptor encoded by MHV-68, although, strikingly, neither the location of ligand engagement nor the stoichiometry of binding is conserved, suggesting that their functions evolved independently.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Exact quantum scattering calculations of transport properties for the H{sub 2}O–H system

Transport properties for collisions of water with hydrogen atoms are computed by means of exact quantum scattering calculations. For this purpose, a potential energy surface (PES) was computed for the interaction of rigid H{sub 2}O, frozen at its equilibrium geometry, with a hydrogen atom, using a coupled-cluster method that includes all singles and doubles excitations, as well as perturbative contributions of connected triple excitations. To investigate the importance of the anisotropy of the PES on transport properties, calculations were performed with the full potential and with the spherical average of the PES. We also explored the determination of the spherical average of the PES from radial cuts in six directions parallel and perpendicular to the C{sub 2} axis of the molecule. Finally, the computed transport properties were compared with those computed with a Lennard-Jones 12-6 potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Interactions of model biomolecules. Benchmark CC calculations within MOLCAS

We present results using the OVOS approach (Optimized Virtual Orbitals Space) aimed at enhancing the effectiveness of the Coupled Cluster calculations. This approach allows to reduce the total computer time required for large-scale CCSD(T) calculations about ten times when the original full virtual space is reduced to about 50% of its original size without affecting the accuracy. The method is implemented in the MOLCAS computer program. When combined with the Cholesky decomposition of the two-electron integrals and suitable parallelization it allows calculations which were formerly prohibitively too demanding. We focused ourselves to accurate calculations of the hydrogen bonded and the stacking interactions of the model biomolecules. Interaction energies of the formaldehyde, formamide, benzene, and uracil dimers and the three-body contributions in the cytosine – guanine tetramer are presented. Other applications, as the electron affinity of the uracil affected by solvation are also shortly mentioned.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Catalog of narrow Mg II absorption lines in the Baryon Oscillation Spectroscopic Survey

Using the Data Release 9 Quasar spectra from the Baryonic Oscillation Spectroscopic Survey, which does not include quasar spectra from the Sloan Digital Sky Survey Data Release 7, we detect narrow Mg ii λλ2796, 2803 absorption doublets in the spectral data redward of 1250 Å (quasar rest frame) until the red wing of the Mg ii λ2800 emission line. Our survey is limited to quasar spectra with a median signal-to-noise ratio 〈S/N〉 ⩾4 pixel{sup −1} in the surveyed spectral region, resulting in a sample that contains 43,260 quasars. We have detected a total of 18,598 Mg ii absorption doublets with 0.2933 ≤ z{sub abs} ≤ 2.6529. About 75% of absorbers have an equivalent width at rest frame of W{sub r}{sup λ2796}⩾1 A-ring . About 75% of absorbers have doublet ratios (DR=W{sub r}{sup λ2796}/W{sub r}{sup λ2803}) in the range of 1 ≤ DR ≤ 2, and about 3.2% lie outside the range of 1 − σ{sub DR} ≤ DR ≤ 2 + σ{sub DR}. We characterize the detection false positives/negatives by the frequency of detected Mg ii absorption doublets in the limits of the S/N of the spectral data. The S/N = 4.5 limit is assigned a completeness fraction of 53% and tends to be complete when the S/N is greater than 4.5. The redshift number densities of all of the detected Mg ii absorbers moderately increase from z ≈ 0.4 to z ≈ 1.5, which parallels the evolution of the cosmic star formation rate density. Limiting our investigation to those quasars whose emission redshift can be determined from narrow emission lines, the relative velocities (β) of Mg ii absorbers have a complex distribution which probably consists of three classes of Mg ii absorbers: (1) cosmologically intervening absorbers; (2) environmental absorbers that reside within the quasar host galaxies or galaxy clusters; (3) quasar outflow absorbers. After subtracting contributions from cosmologically intervening absorbers and environmental absorbers, the β distribution of the Mg iiabsorbers might mainly be contributed by the quasar outflow absorbers and peaks at υ ≈ 1500 km s{sup −1}. This peak velocity is lower than the value of 2000 km s{sup −1} found in statistical analysis of C iv absorbers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Collaborative research: Dynamics of electrostatic solitary waves and their effects on current layers

The project has accomplished the following achievements including the goals outlined in the original proposal. Generation and measurements of Debye-scale electron holes in laboratory: We have generated by beam injections electron solitary waves in the LAPD experiments. The measurements were made possible by the fabrication of the state-of-the-art microprobes at UCLA to measure Debye-scale electric fields [Chiang et al., 2011]. We obtained a result that challenged the state of knowledge about electron hole generation. We found that the electron holes were not due to two-stream instability, but generated by a current-driven instability that also generated whistler-mode waves [Lefebvre et al., 2011, 2010b]. Most of the grant supported a young research scientist Bertrand Lefebvre who led the dissemination of the laboratory experimental results. In addition to two publications, our work relevant to the laboratory experiments on electron holes has resulted in 7 invited talks [Chen, 2007, 2009; Pickett et al., 2009a; Lefebvre et al., 2010a; Pickett et al., 2010; Chen et al., 2011c, b] (including those given by the co-I Jolene Pickett) and 2 contributed talks [Lefebvre et al., 2009b, a]. Discovery of elecctron phase-space-hole structure in the reconnection electron layer: Our theoretical analyses and simulations under this project led to the discovery of an inversion electric field layer whose phase-space signature is an electron hole within the electron diffusion layer in 2D anti-parallel reconnection [Chen et al., 2011a]. We carried out particle tracing studies to understand the electron orbits that result in the phase-space hole structure. Most importantly, we showed that the current density in the electron layer is limited in collisionless reconnection with negligible guide field by the cyclotron turning of meandering electrons. Comparison of electrostatic solitary waves in current layers observed by Cluster and in LAPD: We compared the ESWs observed in a supersubstorm by the Cluster spacecraft and those measured in LAPD. One of the similarities in the characteristics of ESWs observed in space and in LAPD is that the time duration tends to be approximately the inverse of the electron plasma frequency [Pickett et al., 2009b]. Discovery of suprathermal electron bursts inside a series of magnetic islands: Our effort in examining the roles of ESWs in reconnection current layers resulted in the serendipitous discovery that was published in Nature Physics. In earth’s magnetosphere, we observed through the measurements from the four Cluster spacecraft, a series of magnetic islands and suprathermal electron bursts within the islands. The islands were identified to be effectively acceleration sites for electrons [Chen et al., 2008, 2009].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Genarris 2.0: A Random Structure Generator for Molecular Crystals

Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine. Program summary Program Title: Genarris 2.0 Program Files doi: http://dx.doi.org/10.17632/grx6mz4pjn.1 Licensing provisions: BSD-3 Clause Programming language: Python, C External routines/libraries: Spglib, ASE, pymatgen, SciPy, mpi4py, scikit-learn, PyTorch, FHI-aims. Nature of problem: Molecular crystal structure prediction. Solution method: Genarris 2.0 generates molecular crystal structures over the 230 space groups, on general and special Wyckoff positions, using physical constraints. Down-sampling of the generated structures may be performed subsequently, based on molecular crystal packing descriptors and an unsupervised machine learning algorithm. Lastly, ab initio structure relaxation may be performed for the final pool. Depending on the user-defined workflow implemented, Genarris may be used to generate diverse molecular crystal datasets to seed evolutionary algorithms or to train machine learning algorithms or as a standalone crystal structure prediction method. Restrictions: For crystal structure generation, the molecule of interest must be semi-rigid with no bond rotational degrees of freedom. Unusual features: Genarris 2.0 is a highly distributed program, making use of MPI for Python parallelization. The user has the ability to design and implement workflows by executing a user-defined list of procedures. Genarris 2.0 offers new features including a machine learning model for estimating the molecular volume in the solid state from the single molecule structure, structure generation in special Wyckoff positions of space groups, hierarchical structure checks including rigorous treatment of non-orthogonal structures, and clustering and down-selection workflows combining first principles simulations with machine learning. (C) 2020 Elsevier B.V. All rights reserved.

Crystal structure prediction↗
DOE OSTI2011

Cluster synthesis of monodisperse rutile-TiO2 nanoparticles and dielectric TiO2-vinylidene fluoride oligomer nanocomposites

The embedding of oxide nanoparticles in polymer matrices produces a greatly enhanced dielectric response by combining the high dielectric strength and low loss of suitable host polymers with the high electric polarizability of nanoparticles. The fabrication of oxide-polymer nanocomposites with well-controlled distributions of nanoparticles is, however, challenging due to the thermodynamic and kinetic barriers between the polymer matrix and nanoparticle fillers. In the present study, monodisperse TiO2 nanoparticles having an average particle size of 14.4 nm and predominant rutile phase were produced using a cluster-deposition technique without high-temperature thermal annealing and subsequently coated with uniform vinylidene fluoride oligomer (VDFO) molecules using a thermal evaporation source, prior to deposition as TiO2-VDFO nanocomposite films on suitable substrates. The molecular coatings on TiO2 nanoparticles serve two purposes, namely to prevent the TiO2 nanoparticles from contacting each other and to couple the nanoparticle polarization to the matrix. Parallel-plate capacitors made of TiO2-VDFO nanocomposite film as the dielectric exhibit minimum dielectric dispersion and low dielectric loss. Dielectric measurements also show an enhanced effective dielectric constant in TiO2-VDFO nanocomposites as compared to that of pure VDFO. This study demonstrates for the first time a unique electroactive particle coating in the form of a ferroelectric VDFO that has high-temperature stability as compared to conventionally used polymers for fabricating dielectric oxide-polymer nanocomposites.

Balasubramanian, B↗
DOE OSTI2026

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. Here, we introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

Thomas, Phillip S. [Lawrence Berkeley National Lab↗
DOE OSTI2020

How good are polarizable and flexible models for water: Insights from a many-body perspective

We present a systematic analysis of state-of-the-art polarizable and flexible water models from a many-body perspective, with a specific focus on their ability to represent the Born–Oppenheimer potential energy surface of water from the gas to the liquid phase. Using coupled cluster data in the completed basis set limit as a reference, we examine the accuracy of the polarizable models in reproducing individual many-body contributions to interaction energies and harmonic frequencies of water clusters and compare their performance with that of MB-pol, an explicit many-body model that has been shown to correctly predict the properties of water across the entire phase diagram. Based on these comparisons, we use MB-pol as a reference to analyze the ability of the polarizable models to reproduce the energy landscape of liquid water under ambient conditions. We find that, while correctly reproducing the energetics of minimum-energy structures, the polarizable models examined in this study suffer from inadequate representations of many-body effects for distorted configurations. To investigate the role played by geometry-dependent representations of 1-body charge distributions in reproducing coupled cluster data for both interaction and many-body energies, we introduce a simplified version of MB-pol that adopts fixed atomic charges and demonstrate that the new model retains the same accuracy as the original MB-pol model. Based on the analyses presented in this study, we believe that future developments of both polarizable and explicit many-body models should continue in parallel and would benefit from synergistic efforts aimed at integrating the best aspects of the two theoretical/computational frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗