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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Detection of uranium-photofission neutrons with a 4 He scintillation detector

The use of photon active interrogation to detect special nuclear material has held significant theoretical promise, as the interrogating source particles, photons, are fundamentally different from one of the main signatures of special nuclear material: neutrons produced in nuclear fission. However, neutrons produced by photonuclear reactions in the accelerator target, collimator, and environment can obscure the fission neutron signal. These (γ, n) neutrons could be discriminated from fission neutrons by their energy spectrum, but common detectors sensitive to the neutron spectrum, like organic scintillators, are typically hampered by the intense photon background characteristic of photon-based active interrogation. In contrast, high-pressure 4 ⁢He-based scintillation detectors are well-suited to photon active interrogation, as they are similarly sensitive to fast neutrons and can measure their spectrum, but show little response to gamma rays. Here, in this work, a photon active interrogation system utilizing a 4 ⁢He scintillation detector and a 9 MeV linac-bremsstrahlung x-ray source was experimentally evaluated. The detector was shown to be capable of operating in intense gamma-ray environments and detecting photofission neutrons from 238 ⁢U when interrogated by this x-ray source. The photofission neutrons show clear spectral separation from (γ, n) neutrons produced in lead, a common shielding material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Two-nucleon 𝑆-wave interactions at the SU(3) flavor-symmetric point with 𝑚 𝑢⁢𝑑 ≈ 𝑚$^{phys}_𝑠$: A first lattice QCD calculation with the stochastic Laplacian Heaviside method

We report on the first application of the stochastic Laplacian Heaviside method for computing multiparticle interactions with lattice QCD to the two-nucleon system. Like the Laplacian Heaviside method, this method allows for the construction of interpolating operators which can be used to construct a set of positive-definite two-nucleon correlation functions, unlike nearly all other applications of lattice QCD to two nucleons in the literature. It also allows for a variational analysis in which optimal linear combinations of the interpolating operators are formed that couple predominantly to the eigenstates of the system. Utilizing such methods has become of paramount importance to help resolve the discrepancy in the literature on whether two nucleons in either isospin channel form a bound state at pion masses heavier than physical, with the discrepancy persisting even in the SU(3)-flavor-symmetric point with all quark masses near the physical strange quark mass. This is the first in a series of papers aimed at resolving this discrepancy. In the present work, we employ the stochastic Laplacian Heaviside method without a hexaquark operator in the basis at a lattice spacing of 𝑎 ≈0.086 fm, lattice volume of 𝐿 = 48⁢𝑎 ≈ 4.1 fm and pion mass 𝑚 𝜋 ≈ 714 MeV. With this setup, the observed spectrum of two-nucleon energy levels strongly disfavors the presence of a bound state in either the deuteron or dineutron channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Multicomponent mutual diffusion in the warm, dense matter regime

In this work, we present the formulation, simulations, and results for multicomponent mutual diffusion coefficients in the warm, dense matter regime. While binary mixtures have received considerable attention for mass transport, far fewer studies have addressed ternary and more complex systems. We therefore explicitly examine ternary systems utilizing the Maxwell-Stefan formulation that relates diffusion to gradients in the chemical potential. Onsager coefficients then connect the macroscopic diffusion to microscopic particle motions, evinced in trajectories characterized by positions and velocities, through various autocorrelation functions (ACFs). These trajectories are generated by molecular dynamics (MD) simulations either through the Born-Oppenheimer approximation, which treats the ions classically and the electrons quantum-mechanically by an orbital-free density-functional theory, or through a classical MD approach with Yukawa pair-potentials, whose effective ionizations and electron screening length derive from quantal considerations. We employ the reference-mean form of the ACFs and determine the center-of-mass coefficients through a simple reference-frame-dependent similarity transformation. The Onsager terms in turn determine the mutual diffusion coefficients. We examine a representative sample of ternary mixtures as a function of density and temperature from those with only light elements (D-Li-C, D-Li-Al) to those with highly asymmetric mass components (D-Li-Cu, D-Li-Ag, H-C-Ag). We also follow trends in the diffusion as a function of number concentration and evaluated the efficacy of various approximations such as the Darken approximation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A new Kirkpatrick–Baez-based scanning microscope for the Submicron Resolution X-ray Spectroscopy (SRX) beamline at NSLS-II

The development, construction, and first commissioning results of a new scanning microscope installed at the 5-ID Submicron Resolution X-ray Spectroscopy (SRX) beamline at NSLS-II are reported. The developed system utilizes Kirkpatrick–Baez mirrors for X-ray focusing. The instrument is designed to enable spectromicroscopy measurements in 2D and 3D with sub-200 nm spatial resolution. The present paper focuses on the design aspects, optical considerations, and specifics of the sample scanning stage, summarizing some of the initial commissioning results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards Full Field-of-View Fourier Ptychography for Extreme Ultraviolet Microscope

We evaluate various Fourier ptychographic microscopy (FPM) reconstruction algorithms using both simulated and experimental data acquired from an Extreme Ultraviolet (EUV, 13.5 nm wavelength) microscope. We specifically focus on the algorithms' ability to robustly address field-dependent aberrations, which enables increased spatial resolution and quantitative phase imaging across an expanded field of view. We systematically compare the algorithms' performance under aberrations for a single zoneplate imaging system, utilizing Fourier Ring Correlation (FRC) as a systematic metric for assessing reconstruction quality. Furthermore, we explore the impact of systematic errors on the reconstruction of experimental data, aiming to increase the effective field of view by 25-fold, from the nominal 5x5 um2 diffraction-limited area. Additionally, our evaluation incorporates innovative FPM-adjacent methodologies, including the Angular Ptychographic Imaging with Closed-form method (APIC), for reconstructing EUV images.

Gu, Chaoying↗
DOE OSTI2012

Improving I/O Throughput with PRIMACY: Preconditioning ID-Mapper for Compressing Incompressibility

The ability to efficiently handle massive amounts of data is necessary for the continuing development towards exascale scientific data-mining applications and database systems. Unfortunately, recent years have shown a growing gap between the size and complexity of data produced from scientific applications and the limited I/O bandwidth available on modern high-performance computing systems. Utilizing data compression in order to lower the degree of I/O activity offers a promising means to addressing this problem. However, the standard compression algorithms previously explored for such use offer limited gains on both the end-to-end throughput and storage fronts. In this paper, we introduce an in-situ compression scheme aimed at improving end-to-end I/O throughput as well as reduction of dataset size. Our technique, PRIMACY (Preconditioning Id-MApper for Compressing incompressibility), acts as a preconditioner for standard compression libraries by modifying representation of original floating-point scientific data to increase byte-level repeatability, allowing standard loss less compressors to take advantage of their entropy-based byte-level encoding schemes. We additionally present a theoretical model for compression efficiency in high-performance computing environments and evaluate the efficiency of our approach via comparative analysis. Based on our evaluations on 20 real-world scientific datasets, PRIMACY achieved up to 38% and 22% improvements upon standard end-to-end write and read throughputs respectively in addition to a 25% increase in compression ratios paired with 3-to-4-fold improvement in both compression and decompression throughput over general purpose compressors.

Computer Science↗
DOE OSTI2017

Model Reduction for Fast Assessment of Grid Impact of High Penetration PV

A key challenge in properly analyzing the impact of solar photovoltaics (PV) during planning, interconnection and operation in the distribution grid is computational complexity. Such studies require the use of Quasi-Steady-Time-Series (QSTS) power flow to capture the complex interaction of PV with voltage regulating equipment and protection devices and a large number of scenario studies are needed to capture location specific constraints and uncertainties. In addition, a typical distribution feeder can have thousands of nodes and there can be thousands of such feeders in a given utility system. To solve this problem, a new and systematic method for distribution network reduction is proposed. The objective is to reduce the size of distribution systems by more than 80% while preserving the accuracy of power flow results. To this end, an extended Ward-equivalent method has been proposed to create an equivalent circuit. Moreover, load and PV aggregation based on the backward sweep method has been developed to further simplify the feeder. The proposed method is tested with a modified IEEE 123-node distribution test system. The simulation results demonstrate the high efficiency and accuracy of the proposed approach for distribution network reduction.

reduced order systems, load flow, load modeling, v↗
DOE OSTI2023

A Blockchain-Enabled Sustainable Safety Management Framework for Connected Vehicles

The notion of an intelligent transportation system (ITS) aims to boost the performance of transportation networks, which has gained more and more traction in both academic and commercial circles. ITS is a constantly evolving vision that combines cutting-edge transportation approaches with new information, communication, computers, and other technology. ITS should discover consequence routes to enhance the sustainability, safety, and trustworthiness of the entire transportation system utilizing emerging technologies. In this paper, a sustainable safety management framework for connected vehicles is proposed by integrating blockchain. It introduces smart transportation equipment called an AI-enabled vehicle smart device (AVSD) for vehicular communications. AVSD can reduce energy consumption by decreasing the computational costs in vehicular communications. Smart contracts are used to identify vehicles automatically and establish secure communication among vehicles and emergency service stations (ESSs) like hospitals, police stations, and fire stations. The experiment results show that the proposed framework provides a communication environment for sustainable safety and security using the introduced smart transportation device. In conclusion, the proposed blockchain-enabled sustainable safety management framework has the potential to improve safety and sustainability in the transportation industry by creating a secure, decentralized, and transparent platform for managing safety data and promoting safe and sustainable driving behaviors.

42 ENGINEERING↗
DOE OSTI2013

Joint surface reconstruction and 4D deformation estimation from sparse data and prior knowledge for marker-less Respiratory motion tracking

Purpose: The intraprocedural tracking of respiratory motion has the potential to substantially improve image-guided diagnosis and interventions. The authors have developed a sparse-to-dense registration approach that is capable of recovering the patient's external 3D body surface and estimating a 4D (3D + time) surface motion field from sparse sampling data and patient-specific prior shape knowledge.Methods: The system utilizes an emerging marker-less and laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is recovered, which describes the spatio-temporal 4D deformation of the complete patient body surface, depending on the type and state of respiration. It yields both a reconstruction of the instantaneous patient shape and a high-dimensional respiratory surrogate for respiratory motion tracking. The method is validated on a 4D CT respiration phantom and evaluated on both real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured-light scanner.Results: In the experiments, the authors estimated surface motion fields with the proposed algorithm on 256 datasets from 16 subjects and in different respiration states, achieving a mean surface reconstruction accuracy of ±0.23 mm with respect to ground truth data—down from a mean initial surface mismatch of 5.66 mm. The 95th percentile of the local residual mesh-to-mesh distance after registration did not exceed 1.17 mm for any subject. On average, the total runtime of our proof of concept CPU implementation is 2.3 s per frame, outperforming related work substantially.Conclusions: In external beam radiation therapy, the approach holds potential for patient monitoring during treatment using the reconstructed surface, and for motion-compensated dose delivery using the estimated 4D surface motion field in combination with external-internal correlation models.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-I-85: Absorbed Dose Estimation for a Commercially Available MicroCT Scanner

Purpose: To quantify the simulated absorbed dose delivered for a typical scan from a commercially available microCT scanner in order to aid in the dose estimation. Methods: The simulations were conducted using the Geant4 Monte Carlo Toolkit (version 10) with the standard electromagnetic classes. The Quantum FX microCT scanner (PerkinElmer, Waltham, MA) was modeled incorporating the energy fluence and angular distributions of generated photons, spatial dimensions of nominal source-to-object and source-to-detector distances. The energy distribution was measured using a spectrometer (X-123CdTe, Amptek Inc., Bedford, USA) with a 300 angular spread from the source for the 90 kVp X-ray beams with no additional filtration. The nominal distances from the source to object consisted of three setups: 154.0 mm, 104.0 mm, and 51.96 mm. Our simulations recorded the dose absorbed in a cylindrical phantom of PMMA with a fixed length of 2 cm and varying radii (10, 20, 30 and 40 mm) using 100 million incident photons. The averaged absorbed dose in the object was then quantified for all setups. An exposure measurement of 417 mR was taken using a Radcal 9095 system utilizing 10×9–180 ion chamber with the given technique of 90 kVp, 63 μA, and 12 s. The exposure rate was also simulated with same setup to calculate the conversion factor of the beam current and the number of incident photons. Results: For a typical cone-beam scan with non-filtered 90kVp, the dose coefficients (the absorbed dose per mAs) were 2.614, 2.549 and 2.467 μGy/mAs under source to object distance of 104 mm for the object diameters of 10 mm, 20 mm and 30 mm, respectively. Conclusion: A look-up table was developed where an investigator can estimate the delivered dose using this particular microCT given the scanning protocol (kVp and mAs) as well as the size of the scanned object.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Sci-Thur AM: YIS – 07: Optimizing dual-energy x-ray parameters using a single filter for both high and low-energy images to enhance soft-tissue imaging

Objective: To optimize dual-energy parameters of ExacTrac stereoscopic x-ray imaging system for lung SBRT patients Methods: Simulated spectra and a lung phantom were used to optimize filter material, thickness, kVps, and weighting factors to obtain bone subtracted dual-energy images. Spektr simulations were used to identify material in the atomic number (Z) range [3–83] based on a metric defined to separate spectrums of high and low energies. Both energies used the same filter due to time constraints of image acquisition in lung SBRT imaging. A lung phantom containing bone, soft tissue, and a tumor mimicking material was imaged with filter thicknesses range [0–1] mm and kVp range [60–140]. A cost function based on contrast-to-noise-ratio of bone, soft tissue, and tumor, as well as image noise content, was defined to optimize filter thickness and kVp. Using the optimized parameters, dual-energy images of anthropomorphic Rando phantom were acquired and evaluated for bone subtraction. Imaging dose was measured with dual-energy technique using tin filtering. Results: Tin was the material of choice providing the best energy separation, non-toxicity, and non-reactiveness. The best soft-tissue-only image in the lung phantom was obtained using 0.3 mm tin and [140, 80] kVp pair. Dual-energy images of the Rando phantom had noticeable bone elimination when compared to no filtration. Dose was lower with tin filtering compared to no filtration. Conclusions: Dual-energy soft-tissue imaging is feasible using ExacTrac stereoscopic imaging system utilizing a single tin filter for both high and low energies and optimized acquisition parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Acarbose impairs gut Bacteroides growth by targeting intracellular glucosidases

ABSTRACT Acarbose is a type 2 diabetes medicine that prevents dietary starch breakdown into glucose by inhibiting host amylase and glucosidase enzymes. Numerous gut species in theBacteroidesgenus enzymatically break down starch and change in relative abundance within the gut microbiome in acarbose-treated individuals. To mechanistically explain this observation, we used two model starch-degradingBacteroides,Bacteroides ovatus(Bo), andBacteroides thetaiotaomicron(Bt). Bt growth on starch polysaccharides is severely impaired by acarbose, whereas Bo growth is much less affected by the drug. TheBacteroidesuse a starch utilization system (Sus) to grow on starch. We hypothesized that Bo and Bt Sus enzymes are differentially inhibited by acarbose. Instead, we discovered that although acarbose primarily targets the Sus periplasmic GH97 enzymes in both organisms, the drug affects starch processing at multiple other points. Acarbose competes for transport through the TonB-dependent SusC proteins and binds to the Sus transcriptional regulators. Furthermore, Bo expresses a non-Sus GH97 (BoGH97D) when grown in starch with acarbose. The Bt homolog, BtGH97H, is not expressed in the same conditions, nor can overexpression of BoGH97D complement the Bt growth inhibition in the presence of acarbose. This work informs us about unexpected complexities of Sus function and regulation inBacteroides, including variation between related species. Furthermore, this indicates that the gut microbiome may be a source of variable response to acarbose treatment for diabetes. IMPORTANCE Acarbose is a type 2 diabetes medication that works primarily by stopping starch breakdown into glucose in the small intestine. This is accomplished by the inhibition of host enzymes, leading to better blood sugar control via reduced ability to derive glucose from dietary starches. The drug and undigested starch travel to the large intestine where acarbose interferes with the ability of some bacteria to grow on starch. However, little is known about how gut bacteria interact with acarbose, including microbes that can use starch as a carbon source. Here, we show that two gut species,Bacteroides ovatus(Bo) andBacteroides thetaiotaomicron(Bt), respond differently to acarbose: Bt growth is inhibited by acarbose, while Bo growth is less affected. We reveal a complex set of mechanisms involving differences in starch import and sensing behind the different Bo and Bt responses. This indicates the gut microbiome may be a source of variable response to acarbose treatment for diabetes via complex mechanisms in common gut microbes.

Microbiology↗
DOE OSTI2016

Study of collective flows of protons and $ \pi^{{-}}_{}$ π - -mesons in p+C, Ta and He+Li, C collisions at momenta of 4.2, 4.5 and 10 AGeV/c

Collective flows of protons and $\pi^{-}$ -mesons are studied at the momenta of 4.2, 4.5 and 10AGeV/c for p+C, Ta and He+Li, C interactions. The data were obtained from the streamer chamber (SKM-200-GIBS) and from the Propane Bubble Chamber (PBC-500) systems utilized at JINR. A method of Danielewicz and Odyniec has been employed in determining a directed transverse flow of particles. The values of the transverse flow parameter and the strength of the anisotropic emission were defined for each interacting nuclear pair. It is found that the directed flows of protons and pions decrease with increasing the energy and the mass numbers of colliding nucleus pairs. The $ \pi^{{-}}_{}$ -meson and proton flows exhibit opposite directions in all studied interactions, and the flows of protons are directed in the reaction plane. Lastly, the Ultra-relativistic Quantum Molecular Dynamical Model (UrQMD) coupled with the Statistical Multi-fragmentation Model (SMM), satisfactorily describes the obtained experimental results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Study of Azimuthal Correlations in the Target Fragmentation Region in p, d, He, C+C, Ta and C+Ne, Cu Collisions at a Momentum of 4.2, 4.5 and 10 AGeV/c

Azimuthal correlations between the same type of particles (protons or pions) in the target fragmentation region was studied in d, He, C + C, Ta (4.2 AGeV/c), C + Ne, Cu (4.5AGeV/c) and p + C, Ta (10 GeV/c) interactions. The data were obtained from the SKM-200-GIBS streamer chamber and from Propane Bubble Chamber (PBL-500) systems utilized at JINR. Study of multiparticle azimuthal correlations offers unique information about space-time evolution of the interactions. Azimuthal correlations were investigated by using correlation function C($\Delta\phi$)=dN/d($\Delta\phi$), where $\Delta\phi$ represents the angle between the sums of transverse momenta vectors for particles emitted in the forward and backward hemispheres. For protons a "back-to back" ("negative") azimuthal correlations were observed in the above mentioned interactions. The absolute values of the correlation coefficient $|\xi|$ -- the slope parameter of C($\Delta\phi$), strongly depend on the mass number of the target ($A_T$) nuclei in the nucleon-nucleus and nucleus-nucleus collisions. Namely, $|\xi|$ -- decreases with increase of $A_T$ in p+C and p+Ta collisions, while $|\xi|$ decreases from d+C up to C+Ne and then almost does not change with increase of $A_P$, $A_T$ in (d+He)Ta, C+Cu and C+Ta collisions. For pions a "back-to-back" correlations were obtained for a light targets (C, Ne), and a "side-by-side" ("positive") correlations for a heavy targets (Cu, Ta). The $|\xi|$ insignificantly changes with increase of the momenta per nucleon and almost does not change with increase of $A_P$ and $A_T$. Models, used for description of the data -- the Ultra relativistic Quantum Molecular Dynamic (UrQMD) and Quark-Gluon String Model (QGSM), satisfactorily describe the obtained experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Quantifying the Impact of Advanced Web Platforms on High Performance Computing Usage

The deployment of Science Gateways for High Performance Computing (HPC) systems can alter long-accepted usage patterns on supercomputing systems in positive ways as an ever-increasing number of users migrate their workflows to HPC systems. Idaho National Laboratory (INL) has deployed two separate advanced web platforms, Open OnDemand and NICE DCV, for integration with HPC resources to improve web accessibility for HPC users. Researchers conducted a multi-year study on how HPC usage pat- terns changed in the presence of these platforms. This work reports the results of that study and quantifies the observed impacts, including adoption by visualization and Jupyter Notebook/Lab users, decreased job submission friction, rapid uptake of HPC by Windows users, and increased overall system utilization. The most significant impacts were observed from the deployment of Open OnDemand, and this work also identifies some best practices for Open OnDemand deployment for HPC datacenters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Bismuth Enables the Formation of Disordered Birnessite in Rechargeable Alkaline Batteries

Recent advances in rechargeable Zn/MnO$_2$ alkaline batteries have shown promise for scalable energy storage systems which provide a safe, low-cost alternative with a demonstrated lifetime over thousands of cycles. This cathode technology is based on a 2-electron Mn redox process where a layered birnessite-type phase has been shown to form after the first cycle with excellent reversibility between the discharge product, Mn(OH)$_2$. Herein, we investigate the reversible reaction between birnessite and Mn(OH)$_2$ with and without a Bi$_2$O$_3$ additive using multimodal structural characterization techniques during active battery cycling. Diffraction results provide evidence of Bi$^{3+}$ residing in the interlayer of birnessite which prevents irreversible Mn$_3$O$_4$ formation by limiting Mn$^{3+}$ diffusion within the crystal lattice. Also, upon charge no MnOOH intermediate phases are observed. Instead, X-ray absorption and Raman spectroscopy indicate a disordered, non-crystalline birnessite-type phase consisting of mostly neutral H$_2$O within the interlayer. Birnessite phases will reform without Bi$_2$O$_3$ present, but Mn$_3$O$_4$ formation severely polarizes the potential they are formed at, leading to capacity fade. Also, we discuss the reversible Bi$_2$O$_3$ conversion to Bi$^0$ and its contribution to the observed capacity. We expect the results will provide crucial insight into the development of aqueous, rechargeable battery systems utilizing MnO 2 .

25 ENERGY STORAGE↗
DOE OSTI2021

Artificial Diversity and Defense Security (ADDSec)

Artificial Diversity and Defense Security (ADDSec) machine learning algorithms are used to classify and cluster threats so that an appropriate response can be initiated as a mitigation strategy. The package includes an ensemble of machine learning algorithms such as Support Vector Machines, naïve bayes, logistic regression, and random forest that evolve with the data to recognize anomalous behavior at the host and network levels. Inputs into the machine learning algorithms include end host system calls, system utilization, packet captures, and syslog messages. The machine learning algorithms can be retrained based on user defined intervals or on the number of packets received. ADDSEC's threat responses include Internet Protocol (IP) Address randomization, application port number randomization, and application library randomization. The IP randomization implementation is built on top of a Software Defined Networking (SDN) framework. The SDN controller installs flows on each of the SDN switches with randomized source and destination IP addresses. The application port numbers are randomized using iptables. The application library randomization is created with a LLVM compiler. All randomization schemes are transparent to the endpoints on the network. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3379 O

Cox, RebeccaE.↗
DOE OSTI2021

PYSEQM

PYSEQM is a package for performing semi-empirical quantum mechanical (SEQM) simulations on molecular systems utilizing PyTorch. SEQM simulations determine molecular properties (energy, electron density, dipole moment, ect.) by solving an approximate Schrödinger equation for the motions of electrons in a molecule. The use of PyTorch provides three specific advantages. First, it allows the calculations to be offloaded to GPU accelerators, giving an order of magnitude increase in speed. Second, back propagation is used to get atomic forces (derivative of the total energy with respect to atomic position) at the same computational cost as the energy calculation itself. Finally, the use of PyTorch makes for a natural interface to modern machine learning methods, which can be used to adjust the semi-empirical parameters build into SEQM methods. Additionally, PYSEQM implements various other optimizations for performing quantum mechanics based molecular dynamics, including SP2 for rapid GPU based solution of the self-consistent field algorithm, and the extended Lagrangian method for rapid QM-MD.

Nebgen, Benjamin↗