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Trident: A Universal Tool for Generating Synthetic Absorption Spectra from Astrophysical Simulations

Hydrodynamical simulations are increasingly able to accurately model physical systems on stellar, galactic, and cosmological scales; however, the utility of these simulations is often limited by our ability to directly compare them with the data sets produced by observers: spectra, photometry, etc. To address this problem, we have created trident, a Python-based open-source tool for post-processing hydrodynamical simulations to produce synthetic absorption spectra and related data. trident can (i) create absorption-line spectra for any trajectory through a simulated data set mimicking both background quasar and down-the-barrel configurations; (ii) reproduce the spectral characteristics of common instruments like the Cosmic Origins Spectrograph; (iii) operate across the ultraviolet, optical, and infrared using customizable absorption-line lists; (iv) trace simulated physical structures directly to spectral features; (v) approximate the presence of ion species absent from the simulation outputs; (vi) generate column density maps for any ion; and (vii) provide support for all major astrophysical hydrodynamical codes. trident was originally developed to aid in the interpretation of observations of the circumgalactic medium and intergalactic medium, but it remains a general tool applicable in other contexts.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-P-48: The Quantitative Evaluation and Comparison of Image Distortion and Loss of X-Ray Images Between Anti-Scattered Grid and Moire Compensation Processing in Digital Radiography

Purpose: To quantitatively analyze the influence image processing for Moire elimination has in digital radiography by comparing the image acquired from optimized anti-scattered grid only and the image acquired from software processing paired with misaligned low-frequency grid. Methods: Special phantom, which does not create scattered radiation, was used to acquire non-grid reference images and they were acquired without any grids. A set of images was acquired with optimized grid, aligned to pixel of a detector and other set of images was acquired with misaligned low-frequency grid paired with Moire elimination processing algorithm. X-ray technique used was based on consideration to Bucky factor derived from non-grid reference images. For evaluation, we analyze by comparing pixel intensity of acquired images with grids to that of reference images. Results: When compared to image acquired with optimized grid, images acquired with Moire elimination processing algorithm showed 10 to 50% lower mean contrast value of ROI. Severe distortion of images was found with when the object’s thickness was measured at 7 or less pixels. In this case, contrast value measured from images acquired with Moire elimination processing algorithm was under 30% of that taken from reference image. Conclusion: This study shows the potential risk of Moire compensation images in diagnosis. Images acquired with misaligned low-frequency grid results in Moire noise and Moire compensation processing algorithm used to remove this Moire noise actually caused an image distortion. As a result, fractures and/or calcifications which are presented in few pixels only may not be diagnosed properly. In future work, we plan to evaluate the images acquired without grid but based on 100% image processing and the potential risks it possesses.

60 APPLIED LIFE SCIENCES↗

The Application of Current Mineral Processing and Extractive Metallurgy Technologies to Potential Rare Earth Ores in the U.S. Coal Measures: Near-Term Opportunities to Fill Out the U.S. Value Chain

This report will consider the potential for currently available mineral processing and extractive metallurgy technologies to produce separated rare earth compounds from U.S. coal and coal byproducts. Implementation of production as such would require restoration of elements of the rare earth value chain that have recently been absent in the U.S., notably for chemical extraction of rare earth compounds from the mineral form (i.e. hydrometallurgical extraction). A variety of existing technologies are available for use in both mineral processing and extractive metallurgy applied to RE production in the U.S. As will be discussed, once a mineral concentrate is produced, the contained rare earth value can be large compared with transportation costs, and the sections of the value chain dealing with chemical extraction (the largest cost) and separation into individual rare earth compounds can be remotely located. Also, as will be discussed, this has been the rule rather than exception in the history of the rare earth industry in the U.S. A strategy, possibly to include repurposing of existing metallurgical processing facilities, will be presented for near-term production, using a decentralized set of facilities. Also presented will be research results from the Office of Fossil Energy (FE) and the National Energy Technology Laboratory (NETL), within the U.S. Department of Energy, relevant to economic feasibility of rare earth production, notably from the standpoint of establishing which materials are capable of providing economic production. Simple methodologies are presented for both establishment of cutoff grades and economic evaluation of a process. The goal of this report is to present an overview of methods and pathways that will result in “the achievement of near-term rare earth production, using currently available technologies to produce a mixed, chemical extracted rare earth concentrate, and existing and new facilities to produce separated rare earths that can “plug in” to the metals and magnet production facilities.” A set of recommendations appears at the end of this work, involving both research and project development activities which will enable the achievement of this noble goal. A set of recommendations appears at the end of this work, involving both research and project development activities.

58 GEOSCIENCES↗

A Molten Salt Electrochemical Process for the Preparation of Cost-Effective p-Block (Coating) Materials

Solar energy applications rely heavily on p-block elements and transition metals. Silicon is, by far, the most commonly used material in photovoltaic cells and accounts for about 85% of modules sold presently. Of late, thin film photovoltaic cells have gained momentum because of their higher efficiencies. Most of these thin film devices are made out of just five elements, namely, cadmium, tellurium, selenium, indium, gallium and copper. The present manuscript describes an elegant and inexpensive molten salt-based electrolytic process for fabricating a tellurium-coated metallic substrate. A three-electrode set up was employed to coat iridium with tellurium from a molten bath containing lithium chloride, lithium oxide and tellurium tetrachloride (LiCl-Li 2 O-TeCl 4 ) at 650 °C for a duration ranging from 30 to 120 min under a galvanostatic mode. The tellurium coating was observed to be thick, uniform, smooth and homogeneous. Additionally, the deposited tellurium did not chemically react with the iridium substrate to form intermetallic compounds, which is a good feature from the standpoint of the device’s performance characteristics. The present process, being generic in nature, shows the potential for the manufacture of both the coated substates and high-purity elements not just for tellurium but also for other p-block elements.

36 MATERIALS SCIENCE↗

Uncertainty Quantification for Smooth Functional Data with Application to Material Properties

This document outlines a method for processing functional output (i.e., curves) for the ultimate purpose of sampling curves under specified input conditions for use in modeling and simulation uncertainty quantification (UQ) studies. A set of benchmark curves sufficiently representative of the relevant scenario(s) being simulated are provided to the process and formatted as described in Section 1. Principal Component Analysis (PCA) is utilized to discover the components of uncertainty in the benchmark curves and is outlined in Section 2. Section 3 describes the application of uncertainty quantification to the PCA results for the purpose of sampling curves to be used in UQ analysis. Section 4 applies these techniques to an example benchmark dataset. Concluding remarks are provided in the final section.

36 MATERIALS SCIENCE↗

A microscopic and crystallographic study of proton irradiated alloy 718

Solution annealing and age hardening are important processes for achieving good engineering and chemical properties of alloy 718. The composition of alloy 718 also plays an important role as it can affect both mechanical (γ”- and γ’-phase formation) and irradiation behaviors. Therefore, in this study five different sets of alloy 718 samples with two different chemical compositions were fabricated using different processing conditions and irradiated up to 4 dpa. Based on the effects of irradiation on the microstructural data of γ”- and γ’-phases, irradiation-induced dislocation statistics, and crystallographic data, it can be inferred that the samples processed at high solution annealing temperature (1093°C) behave better under irradiation compared to the samples processed at low solution annealing temperatures (945 and 1065°C).

36 MATERIALS SCIENCE↗

A review on the processing accuracy of two-photon polymerization

Two-photon polymerization (TPP) is a powerful and potential technology to fabricate true three-dimensional (3D) micro/nanostructures of various materials with subdiffraction-limit resolution. And it has been applied to microoptics, electronics, communications, biomedicine, microfluidic devices, MEMS and metamaterials. These applications, such as microoptics and photon crystals, put forward rigorous requirements on the processing accuracy of TPP, including the dimensional accuracy, shape accuracy and surface roughness and the processing accuracy influences their performance, even invalidate them. In order to fabricate precise 3D micro/nanostructures, the factors influencing the processing accuracy need to be considered comprehensively and systematically. In this paper, we review the basis of TPP micro/nanofabrication, including mechanism of TPP, experimental set-up for TPP and scaling laws of resolution of TPP. Then, we discuss the factors influencing the processing accuracy. Finally, we summarize the methods reported lately to improve the processing accuracy from improving the resolution and changing spatial arrangement of voxels.

36 MATERIALS SCIENCE↗

Planck intermediate results

We present the NPIPE processing pipeline, which produces calibrated frequency maps in temperature and polarization from data from the Planck Low Frequency Instrument (LFI) and High Frequency Instrument (HFI) using high-performance computers. NPIPE represents a natural evolution of previous Planck analysis efforts, and combines some of the most powerful features of the separate LFI and HFI analysis pipelines. For example, following the LFI 2018 processing procedure, NPIPE uses foreground polarization priors during the calibration stage in order to break scanning-induced degeneracies. Similarly, NPIPE employs the HFI 2018 time-domain processing methodology to correct for bandpass mismatch at all frequencies. In addition, NPIPE introduces several improvements, including, but not limited to: inclusion of the 8% of data collected during repointing manoeuvres; smoothing of the LFI reference load data streams; in-flight estimation of detector polarization parameters; and construction of maximally independent detector-set split maps. For component-separation purposes, important improvements include: maps that retain the CMB Solar dipole, allowing for high-precision relative calibration in higher-level analyses; well-defined single-detector maps, allowing for robust CO extraction; and HFI temperature maps between 217 and 857 GHz that are binned into 0'.9 pixels (Nside = 4096), ensuring that the full angular information in the data is represented in the maps even at the highest Planck resolutions. The net effect of these improvements is lower levels of noise and systematics in both frequency and component maps at essentially all angular scales, as well as notably improved internal consistency between the various frequency channels. Based on the NPIPE maps, we present the first estimate of the Solar dipole determined through component separation across all nine Planck frequencies. The amplitude is (3366.6 ± 2.7) μK, consistent with, albeit slightly higher than, earlier estimates. From the large-scale polarization data, we derive an updated estimate of the optical depth of reionization of τ = 0.051 ± 0.006, which appears robust with respect to data and sky cuts. There are 600 complete signal, noise and systematics simulations of the full-frequency and detector-set maps. As a Planck first, these simulations include full time-domain processing of the beam-convolved CMB anisotropies. The release of NPIPE maps and simulations is accompanied with a complete suite of raw and processed time-ordered data and the software, scripts, auxiliary data, and parameter files needed to improve further on the analysis and to run matching simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Adaptive hybrid simulations for multiscale stochastic reaction networks

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

ATLAS toward the High Luminosity era: challenges on electronic systems

To maximize the physics reach, the Large Hadron Collider (LHC) plans to increase its instantaneous luminosity to $7.5×10^{34} cm^{-2} s^{-1}$ and deliver $3 - 4 ab^{-1}$ of data at a center-of-mass energy of 14 TeV. To profit from this high-luminosity LHC operation with a pile-up up to 200 inelastic collisions per bunch crossing, performance of the ATLAS detector needs to be maintained and in many systems, improved. The upgraded detector will have an unprecedented output data rate of up to 200 TB/s. Real-time processing of this large data volume in a short time period is extremely challenging. New sets of both front-end and back-end electronics are required for all sub-detectors. The large number of detector channels, huge volumes of input and output data, short time available to process and transmit data, harsh radiation environment, and the need of low power consumption all impose great challenges on the designs of electronic systems.

43 PARTICLE ACCELERATORS↗

Toward Better Understanding of Microphysical Processes and Resulting Precipitation Physics: A Merger Of Observations and Cloud Models (Final Report)

A large database of global disdrometer observations and a diverse set of simulations from the Regional Atmospheric Modeling System (RAMS) were compared using principal component analysis (PCA) in order to better understand warm and ice-based precipitation processes. The analysis demonstrated that six distinct precipitation groups (PGs) with common characteristics were revealed in both the observations and model simulations. These PGs were defined by similar co-variability of rain parameters. However, the model showed large concentrations of drops with a given size compared to the observations. Detailed investigations determined the parameterization of drop breakup was forcing the drops to an equilibrium size with a stronger constraint than was indicated by the observations. A series of sensitivity studies permutating the rain shape parameter in the RAMS 2-moment bulk scheme demonstrated how the assumed shape of the rain distribution influences the microphysics as well as precipitation characteristics. Results were compared to the same simulations performed with a bin microphysics scheme where the rain shape parameter is freely evolving. In the bin scheme, a wide range of shape parameters were found, with horizontal and vertical variability, in addition to being a function of storm lifetime. The results of this study highlight the limitations of a fixed assumed rain distribution in 2-moment microphysics schemes. Model simulations were used to probe the microphysical origins of the six PGs. Rain budgets from a supercell case showed that several of the groups hypothesized to be associated with strong ice microphysical processes had significant contributions from melting hail, but the complexity of ice and warm-rain processes in the supercell precluded definitive determination of microphysical origins for many of the PGs. A case study from the Mid-latitude Continental Convection and Clouds Experiment (MC3E) compared the model PGs to disdrometer observations, and demonstrated the spatial and temporal variability of the PGs which is not possible from disdrometer point measurements alone. The analyses performed during this project demonstrated how statistical analysis can provide a robust method for comparing model simulations and observations, which ultimately resulted identification of limitations in some current microphysics parameterizations as well as insights into precipitation variability which ultimately benefits both observations and modeling efforts.

54 ENVIRONMENTAL SCIENCES↗

THE PHYSICAL ENVIRONMENT OF THE MASSIVE STAR-FORMING REGION W42

We present an analysis of multi-wavelength observations from various data sets and Galactic plane surveys to study the star-formation process in the W42 complex. A bipolar appearance of the W42 complex is evident due to the ionizing feedback from the O5–O6 type star in a medium that is highly inhomogeneous. The Very Large Telescope/NACO adaptive-optics K and L{sup ′} images (resolutions ∼0.″2–0.″1) resolved this ionizing source into multiple point-like sources below ∼5000 AU scale. The position angle ∼15° of the W42 molecular cloud is consistent with the H-band starlight mean polarization angle, which in turn is close to the Galactic magnetic field, suggesting the influence of the Galactic field on the evolution of the W42 molecular cloud. Herschel sub-millimeter data analysis reveals three clumps located along the waist axis of the bipolar nebula, with the peak column densities of ∼(3–5) × 10{sup 22} cm{sup −2} corresponding to visual extinctions of A{sub V} ∼ 32–53.5 mag. The Herschel temperature map traces a temperature gradient in W42, revealing regions of 20 K, 25 K, and 30–36 K. Herschel maps reveal embedded filaments (length ∼1–3 pc) that appear to be radially pointed to the denser clump associated with the O5–O6 star, forming a hub-filament system. A total of 512 candidate young stellar objects (YSOs) are identified in the complex, ∼40% of which are present in clusters distributed mainly within the molecular cloud, including the Herschel filaments. Our data sets suggest that the YSO clusters, including the massive stars, are located at the junction of the filaments, similar to those seen in the Rosette Molecular Cloud.

79 ASTRONOMY AND ASTROPHYSICS↗

Search for an Invisible Z ' in a Final State with Two Muons and Missing Energy at Belle II

The $L_μ – L_τ$ extension of the standard model predicts the existence of a lepton-flavor-universality-violating Z' boson that couples only to the heavier lepton families. We search for such a Z' through its invisible decay in the process $e^+e^– → μ^+μ^–$Z'. We use a sample of electron-positron collisions at a center- of-mass energy of 10.58 GeV collected by the Belle II experiment in 2019-2020, corresponding to an integrated luminosity of 79.7 fb –1 . We find no excess over the expected standard-model background. We set 90%-confidence-level upper limits on the cross section for this process as well as on the coupling of the model, which ranges from 3 × 10 –3 at low Z' masses to 1 at Z' masses of 8 GeV=$c^2$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SU-E-T-475: An Accurate Linear Model of Tomotherapy MLC-Detector System for Patient Specific Delivery QA

Purpose: An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system. Methods: A leaf pattern basis (LPB) consisting of no-leaf-open, single-leaf-open, double-leaf-open and triple-leaf-open patterns are chosen to represent linear and major nonlinear effects of leaf fluence as a linear system. An arbitrary leaf pattern can be expressed as (or decomposed to) a linear combination of the LPB either pulse by pulse or weighted by dwelling time. The exit detector responses to the LPB are obtained by processing returned detector signals resulting from the predefined leaf patterns for each jaw setting. Through forward transformation, detector signal can be predicted given a delivery plan. An equivalent leaf open time (LOT) sinogram containing output variation information can also be inversely calculated from the measured detector signals. Twelve patient plans were delivered in air. The equivalent LOT sinograms were compared with their planned sinograms. Results: The whole calibration process was done in 20 minutes. For two randomly generated leaf patterns, 98.5% of the active channels showed differences within 0.5% of the local maximum between the predicted and measured signals. Averaged over the twelve plans, 90% of LOT errors were within +/−10 ms. The LOT systematic error increases and shows an oscillating pattern when LOT is shorter than 50 ms. Conclusion: The LPB method models the MLC-detector response accurately, which improves patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is sensitive enough to detect systematic LOT errors as small as 10 ms.

60 APPLIED LIFE SCIENCES↗

Hydrogeologic modeling and the development of preliminary remediation goals for the Guterl Specialty Steel Site, New York - 15431

The Former Guterl Specialty Steel Corporation Site (Guterl Site) is located 32 kilometers (20 miles) northeast of Buffalo, New York, in Lockport, Niagara County, New York. Between 1948 and 1952, up to 15,875 metric tons (35 million pounds) of natural uranium metal (U) were processed at the Guterl Site. The resulting milling dust, shavings, thermal scale, and associated on-site land disposal contaminated both the facility and soils. These combined manufacturing and disposal processes promoted the development of a large-scale uranium plume in the groundwater underlying the site. Site soils are anthropogenic fill and re-worked, glacially-derived sediments that vary between 0.6 meters (m) and 3 meters (2.0 to 10.0 feet [ft]) in thickness. These soils blanket a highly permeable weathered and fractured zone in the upper Lockport Dolostone bedrock. Aerial recharge through the thin soils flushes soluble constituents to groundwater, as exemplified by variations in specific conductivity and groundwater levels in the bedrock during precipitation events. Seasonally higher groundwater levels also promote contact with uranium contamination in deeper soil, thus complicating the transport characteristics of the site (e.g., oxidizing metallic uranium in the soil that increases leach rates). The Seasonal Soil (SESOIL) compartment model was used to simulate a series of site soil conditions and predict the leaching of uranium to groundwater. The SESOIL input included physical soil characteristics, uranium profiles common in five soil areas, climate data, and an assumed oxidation-state (or chemical valence) for metallic uranium in the soil. The iterative modeling process evaluated site-specific variables to achieve a final deterministic set of input that was applied to the five soil areas. The leaching simulations estimated time-dependent influx rates for uranium, which were input to a numerical groundwater flow (MODFLOW) and transport (MT3DMS) model. The combined modeling effort produced spatially and temporally variable transport conditions that were simulated over a 1,000-year period. The leaching models predicted a preliminary remediation goal (PRG) for uranium of 11 milligrams per kilogram (mg/kg) that is protective of groundwater. However, this low uranium PRG has field implementation concerns, so a modified direct-exposure PRG of 70 mg/kg was developed and evaluated in the flow and transport model. The primary difference in the PRGs is the longevity and location of the uranium plume, which will affect the remedial costs and potential stakeholder acceptance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Presupernova Neutrinos: Realistic Emissivities from Stellar Evolution

We present a new calculation of neutrino emissivities and energy spectra from a massive star going through the advanced stages of nuclear burning (presupernova) in the months before becoming a supernova. The contributions from β decay and electron capture, pair annihilation, plasmon decay, and the photoneutrino process are modeled in detail, using updated tabulated nuclear rates. We also use realistic conditions of temperature, density, electron fraction, and nuclear isotopic composition of the star from the state-of-the-art stellar evolution code MESA. Results are presented for a set of progenitor stars with mass between 15 M{sub ⊙} and 30 M{sub ⊙}. It is found that β processes contribute substantially to the neutrino emissivity above realistic detection thresholds of few MeV, at selected positions and times in the evolution of the star.

79 ASTRONOMY AND ASTROPHYSICS↗

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Volume of distribution at steady state (V D,ss ) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62%–71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted V D,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss but was limited in estimating the compounds with low V D,ss .

59 BASIC BIOLOGICAL SCIENCES↗

The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

Abstract Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based general-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data diversity, we visualize it with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5 M density functional theory calculations, while the ANI-1ccx data set contains 500 k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM calculated properties for the chemical elements C, H, N, and O are provided: energies, atomic forces, multipole moments, atomic charges, etc. We provide this data to the community to aid research and development of ML models for chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗