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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 OSTI2023

Unraveling Joint Evolution of Bars, Star Formation, and Active Galactic Nuclei of Disk Galaxies

We aim to unravel the interplay between bars, star formation (SF), and active galactic nuclei (AGNs) in barred galaxies. To this end, we utilize the SDSS DR12 to select a sample of nearby (0.02 < z < 0.06) disk galaxies that are suitable for bar examination (M r < –20.12 and inclination ≲53°). We identify 3662 barred galaxies and measure the length and axis ratio of each bar. We invent new bar parameters that mitigate the stellar and bulge mass biases and show, for the first time, that the evolution of non-AGN and AGN-hosting barred galaxies should be tracked using different bar parameters: the bar length for non-AGN galaxies and the bar axis ratio for AGN-hosting galaxies. Our analysis confirms that barred galaxies have a higher specific SF rate than unbarred control galaxies. Moreover, we find a positive correlation of bar length with both the SF enhancement and the centrally star-forming galaxy fraction, indicating the interconnectivity of bars and SF through the bar-driven gas inflow. We also find that, while the AGN fraction of barred galaxies is the same as that of the unbarred control sample, galaxies hosting more massive black holes (BHs) have rounder (i.e., higher axis ratio) bars, implying that the bar is not a cause of AGN activity; rather, AGNs appear to regulate bars. Our findings corroborate theoretical predictions that bars in non-AGN galaxies grow in length, and bars in AGN-hosting galaxies become rounder as BHs grow and eventually get destroyed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Facets control charge separation during photoelectrochemical water oxidation with strontium titanate (SrTiO 3 ) single crystals

The photocatalytic overall water splitting reaction provides a pathway to hydrogen fuel from sunlight. Photocatalysts must achieve the reaction without the application of an external bias, which requires an effective charge separation mechanism. Photolabeling studies and electrostatic simulations for the well-known CoOOH/Al:SrTiO 3 /Rh/Cr 2 O 3 photocatalyst suggest that charge separation is driven by work function differences at the (100) and (110) facets of SrTiO 3 , which are electron and hole selective, respectively. Here we use hydrogen annealed SrTiO 3–x single crystals to obtain the first quantitative assessment of the charge separation ability of the (100), or (110), or (111) facets during oxygen evolution. Under UV illumination (60 mW cm –2 ), the crystals exhibit variable water oxidation photocurrents (0.34, 0.82, 1.36 mA cm –2 at 1.23 V versus RHE) and photovoltage values of 1.40, 1.52 and 1.52 V for (100), (110), and (111) SrTiO 3–x , respectively. A surface photovoltage increase in that same order (0.31 V < 0.57 V < 0.67 V) is confirmed independently with vibrating Kelvin probe surface photovoltage spectroscopy (VKP-SPV) under 375 nm (1.91 mW cm –2 ) illumination. Mott Schottky measurements in aqueous K 3/4 [Fe(CN) 6 ] reveal facet-dependent flatband positions of –0.58, –0.71, and –0.74 V RHE for the (100), (110), and (111) crystals respectively. This confirms that the photoelectrochemical water oxidation performance of SrTiO 3–x crystals is controlled by the work function of each facet, which determines the electron transfer barrier height of the respective solid–liquid junctions. After correcting for differences in electron donor concentrations, barriers are found to increase in the order (100) < (111) < (110) and differ by as much as 0.16 eV, similar to an earlier prediction. Altogehter, these results explain the charge separation mechanism in SrTiO 3 photocatalysts and highlight the need for faceted semiconductor crystals as light absorbers in particle-based photocatalysts.

08 HYDROGEN↗
DOE OSTI2021

Accelerating Biological Insight for Understudied Genes

Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Zoology↗
DOE OSTI2022

Illustrating galaxy–halo connection in the DESI era with illustrisTNG

ABSTRACT We employ the hydrodynamical simulation illustrisTNG to inform the galaxy–halo connection of the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples of the Dark Energy Spectroscopic Instrument (DESI) survey at redshift z ∼ 0.8. Specifically, we model the galaxy colours of illustrisTNG and apply sliding DESI colour–magnitude cuts, matching the DESI target densities. We study the halo occupation distribution (HOD) model of the selected samples by matching them to their corresponding dark matter haloes in the illustrisTNG dark matter run. We find the HOD of both the LRG and ELG samples to be consistent with their respective baseline models, but also we find important deviations from common assumptions about the satellite distribution, velocity bias, and galaxy secondary biases. We identify strong evidence for concentration-based and environment-based occupational variance in both samples, an effect known as ‘galaxy assembly bias’. The central and satellite galaxies have distinct dependencies on secondary halo properties, showing that centrals and satellites have distinct evolutionary trajectories and should be modelled separately. These results serve to inform the necessary complexities in modelling galaxy–halo connection for DESI analyses and also prepare for building high-fidelity mock galaxies. Finally, we present a shuffling-based clustering analysis that reveals a 10–15 ${{\ \rm per\ cent}}$ excess in the LRG clustering of modest statistical significance due to secondary galaxy biases. We also find a similar excess signature for the ELGs, but with much lower statistical significance. When a larger hydrodynamical simulation volume becomes available, we expect our analysis pipeline to pinpoint the exact sources of such excess clustering signatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dopant Sensitive Electrolytic Etching of Germanium with High Selectivity

Abstract The enhanced charge carrier mobility and photon absorption compared to silicon make germanium attractive for next-generation photo diodes. However, the complex oxidation behavior of germanium challenges dopant-dependent selective etching that is desired for the fabrication of backside imaging architectures. This report demonstrates electrolytic wet etching of p-doped germanium which proceeds up to 17,500x faster than etching of intrinsic germanium. Homoepitaxially grown layers of germanium were electrolytically etched in potassium hydroxide over a range of biases. Intermittent acquisition of cyclic voltammetry spectra during etching has suppressed the formation of electric double layers, maintained appreciable etch rates, and allowed for in operando process control. The observed etch rates scaled with dopant concentration. An effective etch rate of germanium removal of 2.100±0.044 µm/min was accomplished for a boron dopant concentration of 6E18cm-3. For nominally intrinsic germanium, however, an effective etch rate of only 0.00012±0.00011 µm/min was observed. A series of systematic electrolytic etch experiments have revealed the transfer of 4 electrons per germanium atom removed.

Wood, Joseph G.↗
DOE OSTI2024

Versatile allelic replacement and self-excising integrative vectors for plasmid genome mutation and complementation

ABSTRACT The ability to better understand the function of proteins expressed by bacteria has typically relied upon the development of genetic mutant strains. This approach has been especially challenging for plasmid-encoded genes, as most of the previously described allelic replacement vectors are inefficient for plasmid genome mutation as they either rely on plasmid-derived counterselection toxins or depend on other strategies suchsacB,tetA, andrpsLwhich have been proven to be less efficient for mutant selection. Integrative vectors lack chromophore indicators, thus requiring laborious screening or excision of the vector’s backbone relies on the introduction of a flippase (FLP)-expressing plasmid. The allelic replacement vector, designated here as pDG1, expresses an X-Gal hydrolyzing enzyme (BgaB) that can be used for blue/white screening allowing identification of colonies that integrated and successfully removed the mutagenesis plasmid without a bias for those still carrying it. pDG1 was further improved by including the rhamnose-inducible Tse2 toxin as a potent counterselection system. The efficacy of pDG1 was validated by deleting portions of the plasmid-encoded VirB4/D4 type IV secretion system and aerobactin-synthesizing operons inSalmonella enterica. The integrative vectors, which contain an ΦC31attPsite and genes encoding ΦC31 integrase (int), can seamlessly integrate to target ΦC31attBonSalmonellaplasmids or chromosome. These vectors were improved by insertingbgaBand FLP-encoding genes so that, following integration, most of the vector’s backbone encompassingint,bgaB, and FLP genes can be excised by FLP, without the need for another FLP-expressing vector, creating white colonies carrying a stably integrated target gene. As such, we were able to integrate a 9.3-kb DNA fragment toSalmonellachromosome and flipped out most of the integrated vector in one step, leaving the target fragment in the chromosome. IMPORTANCE In spite of the dissemination of multidrug-resistant plasmids among Gram-negative pathogens, including those carrying virulence genes, vector tools for studying plasmid-born genes are lacking. The allelic replacement vectors can be used to generate plasmid or chromosomal mutations including markless point mutations. This is the first report describing a self-excising integrative vector that can be used as a stable single-copy complementing tool to study medically important pathogens includingin vivostudies without the need for antibiotic selection. Overall, our newly developed vectors can be applied for the assessment of the function of plasmid-encoded genes by specifically creating mutations, moving large operons between plasmids and to/from the chromosome, and complementing phenotypes associated with gene mutation. Furthermore, the vectors express chromophores for the detection of target gene modification or colony isolation, avoiding time-consuming screening procedures.

Microbiology↗
DOE OSTI2023

The miniJPAS survey: AGN and host galaxy coevolution of X-ray-selected sources

Studies indicate strong evidence of a scaling relation in the local Universe between the supermassive black hole mass (MBH) and the stellar mass of their host galaxies (M * ). They even show similar histories across cosmic times of their differential terms: the star formation rate (SFR) and black hole accretion rate (BHAR). However, a clear picture of this coevolution is far from being understood. We selected an X-ray sample of active galactic nuclei (AGN) up to z = 2.5 in the miniJPAS footprint. Their X-ray to infrared spectral energy distributions (SEDs) have been modeled with the CIGALE code, constraining the emission to 68 bands, from which 54 are the narrow filters from the miniJPAS survey. For a final sample of 308 galaxies, we derived their physical properties, such as their M * , SFR, star formation history (SFH), and the luminosity produced by the accretion process of the central BH (L AGN ). For a subsample of 113 sources, we also fit their optical spectra to obtain the gas velocity dispersion from the broad emission lines and estimated the M BH . We calculated the BHAR in physical units depending on two radiative efficiency regimes. We find that the Eddington ratios (λ Edd ) and its popular proxy (L X /M * ) have a difference of 0.6 dex, on average, and a KS test indicates that they come from different distributions. Our sources exhibit a considerable scatter on the MBH - M * scaling relation, which can explain the difference between λ Edd and its proxy. We also modeled three evolution scenarios for each source to recover the integral properties at z = 0. Using the SFR and BHAR, we show a notable diminution in the scattering between MBH - M * . For the last scenario, we considered the SFH and a simple energy budget for the AGN accretion, and we retrieved a relation similar to the calibrations known for the local Universe. Our study covers ~1 deg 2 in the sky and is sensitive to biases in luminosity. Nevertheless, we show that, for bright sources, the link between the differential values (SFR and BHAR) and their decoupling based on an energy limit is the key that leads to the local M BH - M * scaling relation. In the future, we plan to extend this methodology to a thousand degrees of the sky using JPAS with an X-ray selection from eROSITA, to obtain an unbiased distribution of BHAR and Eddington ratios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Magnetostrictive Ultrasonic Waveguide Transducer for In-Pile Thermometry

Real-time and reliable temperature measurement on nuclear fuels is crucial for the safe operation of existing pressurized-water reactors and future advanced nuclear reactors. Magnetostrictive materials deform when subjected to a magnetic field or exhibit magnetization variation when stressed. Here, based on these properties, this study prototyped an ultrasonic thermometer (UT) consisting of a magnetostrictive waveguide, a dc coil providing appropriate magnetic biasing, and an ac coil generating an acoustic impulse and detecting the resulting acoustic echoes. By tracking the time of flight between the excitation pulse and the echoes, the UT can potentially detect nuclear fuel cladding temperature from a long distance. In this study, magnetostrictive iron–gallium alloys, or Galfenol, were selected as the waveguide due to their large magnetostriction, superior temperature survivability, excellent radiation resilience, and high mechanical robustness. A multiphysics finite-element model considering electrical, magnetic, and mechanical dynamics in the magnetostrictive UT was then developed. The model exhibited an error of 0.24% in time-of-flight simulation and, therefore, enabled computer-aided design and guided signal processing. Between room temperature and 120 °C, the new Galfenol-based UT exhibits a linear sensitivity of 162.8×10 ₋6 °C ₋1 , which is 51.7% higher than a previous magnetostrictive UT based on iron–cobalt–vanadium alloys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0–1 M) and nitric acid (0.1–10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Nanometre-resolved observation of electrochemical microenvironment formation at the nanoparticle–ligand interface

The dynamic response of surface ligands on nanoparticles (NPs) to external stimuli critically determines the functionality of NP–ligand systems. For example, in electrocatalysis the collective dissociation of ligands on NP surfaces can lead to the creation of an NP/ordered-ligand interlayer, a microenvironment that is highly active and selective for CO 2 -to-CO conversion. However, the lack of in situ characterization techniques with high spatial resolution hampers a comprehensive molecular-level understanding of the mechanism of interlayer formation. Here, in this work, we utilize in situ infrared nanospectroscopy and surface-enhanced Raman spectroscopy, unveiling an electrochemical bias-induced consecutive bond cleavage mechanism of surface ligands leading to formation of the NP/ordered-ligand interlayer. This real-time molecular insight could influence the design of confined localized fields in multiple catalytic systems. Moreover, the demonstrated capability of capturing nanometre-resolved, dynamic molecular-scale events holds promise for the advancement of using controlled local molecular behaviour to achieve desired functionalities across multiple research domains in nanoscience.

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

Tracking Soiling Losses: Assessment, Uncertainty, and Challenges in Mapping

Several models have been presented in the recent years to estimate the magnitude of soiling from environmental parameters. However, these models are often based on data from a single site, or at most a few sites, and only limited data are, as of yet, available on their uncertainty. The present work aims to present a first comparative analysis of soiling estimation models, using measured soiling data from various locations in the USA. The study also investigates the impact that the source of the input data can have on the estimation. The results show that the model selection is only one of the factors that can affect the evaluation. Indeed, the use of satellite-derived or ground-mounted particulate matter data can lead to the generation of different soiling maps, with factors greater than 2x between the modeled losses. The current challenges and the unanswered questions that can bias soiling estimation are discussed. Additionally, potential research directions to improve the quality of soiling modeling are identified.

14 SOLAR ENERGY↗
DOE OSTI2026

Electromagnetic Shower Reconstruction and Identification in FASER's Emulsion Detector for LHC Forward Neutrino Measurements

We present methods for electromagnetic shower reconstruction and identification in the FASERnu emulsion detector using 100 GeV and 200 GeV electron test-beam data from the CERN SPS H4 beamline. The reconstruction employs a clustering-based algorithm without energy-dependent tuning to determine shower axes. A multi-level identification chain comprising track pre-selection, a cut-based selection, and a BDT classifier achieves combined background rejection rates of 99.99% (100 GeV) and 99.94% (200 GeV). The method reaches total reconstruction and identification efficiencies of 58.9% (100 GeV) and 70.8% (200 GeV) evaluated from simulated samples. Energy reconstruction using the total number of reconstructed segments as the calorimetric estimator yields relative biases of +0.6% (100 GeV) and -0.8% (200 GeV), with resolutions of 25.4% and 22.6%, respectively. Systematic uncertainties on the energy reconstruction are dominated by variations in emulsion film detection efficiency, contributing (+10.9%/-8.2%) at 100 GeV and (+10.3%/-6.9%) at 200 GeV. The methodology provides a validated framework for electron neutrino identification with the FASERnu detector at the LHC.

Mammen Abraham, Roshan [UC, Irvine]↗
DOE OSTI2023

Tritium Breeding Ratio Evaluation of Solid Breeder Concepts for the FESS-FNSF

This paper presents a parametric study of the Fusion Energy System Studies-Fusion Nuclear Science Facility’s (FNSF’s) tritium breeding performance for several solid breeder concepts, neutron multiplying materials, and blanket materials, assuming volume fractions based on the most recent FNSF design as a realistically representative fusion facility. In this study, we initially surveyed the tritium breeding ratio (TBR) of several solid breeder concepts by employing a simplified but efficient one-dimensional (1-D) infinite cylinder reduced-order model (ROM). Parametric studies were performed with the ROMs for the full range of breeder-to-multiplier ratios to identify the optimum mixture compositions for each breeder type that would lead to a maximum TBR. These optimized breeder-multiplier combinations were then homogenized with FNSF blanket component materials to estimate their impacts on the TBR. Subsequently, as a validation step for the optimal designs, TBR calculations were performed using a more realistic modified 1-D ROM with inner and outer breeding regions, as well as with a fully detailed 22.5-deg three-dimensional (3-D) sector of the FNSF to assess the impact of geometry details on the TBR. The differences between the two 1-D models were negligible, while the ROMs were able to correctly predict trends and identify the maximum and minimum TBR cases, as well as show consistent biases relative to the results produced by the full 3-D, 22.5-deg sector for specific breeder/multiplier combinations. Solid breeder concepts such as Li 2 O, Li 4 SiO 4 , and Li 8 ZrO 6 outperformed all others in this study in terms of TBR performance when combined with all the neutron multiplier materials selected. Here, an underlying goal of this study was to develop and improve rapid and reliable ROMs to aid designers during parametric optimizations of highly complex and computationally expensive fusion models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

The impact of anisotropic redshift distributions on angular clustering

A leading way to constrain physical theories from cosmological observations is to test their predictions for the angular clustering statistics of matter tracers, a technique that is set to become ever more central with the next generation of large imaging surveys. Interpretation of this clustering requires knowledge of the projection kernel, or the redshift distribution of the sources, and the typical assumption is an isotropic redshift distribution for the objects. However, variations in the kernel are expected across the survey footprint due to photometric variations and residual observational systematic effects. Here, we develop the formalism for anisotropic projection and present several limiting cases that elucidate the key aspects. We quantify the impact of anisotropies in the redshift distribution on a general class of angular two-point statistics. In particular, we identify a mode-coupling effect that can add power to auto-correlations, including galaxy clustering and cosmic shear, and remove it from certain cross-correlations. If the projection anisotropy is primarily at large scales, the mode-coupling depends upon its variance as a function of redshift; furthermore, it is often of similar shape to the signal. In contrast, the cross-correlation of a field whose selection function is anisotropic with another one featuring no such variations — such as CMB lensing — is immune to these effects. We discuss explicitly several special cases of the general formalism including galaxy clustering, galaxy-galaxy lensing, cosmic shear and cross-correlations with CMB lensing, and publicly release a code to compute the biases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Selected Uses of TSUNAMI in Critical Experiment Design and Analysis

Validation in criticality safety is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 and enable investigation of the parameters at which such a critical condition is achieved. For the critical experiments used in a validation to capture the biases of the materials and neutron energy spectra of interest, those materials must be included in the experiment such that they influence k eff or another observable parameter with statistical significance. This paper discusses the use of sensitivity uncertainty (S/U) methods to develop critical experiments for various purposes. S/U techniques are useful for understanding the underlying components of nuclear data which affect the k eff or another parameter of a given configuration. S/U calculations are most commonly used to compare existing experiments to applications of interest; however, S/U techniques can also be used to identify, optimize, or assess features of proposed experiments so that they can better test specific portions of nuclear data or match an application of interest. The S/U techniques discussed here are from the TSUNAMI code system. The two primary codes discussed in this work are TSUNAMI-3D, which implements the KENO criticality code to calculate the sensitivity of k eff to nuclear data, and TSAR, which calculates the sensitivity of a reactivity difference between two configurations based on their TSUNAMI-3D generated sensitivity profiles. The methods used in these tools are discussed in more detail in the SCALE manual. This paper is one of a series on the development and use of TSUNAMI tools. The other papers address development of TSUNAMI methods and a review of TSUNAMI applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2021

Toward quantum Monte Carlo forces on heavier ions: Scaling properties

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here, we benchmark the accuracy and computational cost of QMC forces. The zero-variance zero-bias (ZVZB) force estimator is used in standard variational and diffusion Monte Carlo simulations with mean-field based trial wavefunctions and atomic pseudopotentials. Statistical force uncertainties are obtained with a recently developed regression technique for heavy tailed QMC data [P. Lopez Rios and G. J. Conduit, Phys. Rev. E 99, 063312 (2019)]. By considering selected atoms and dimers with elements ranging from H to Zn (1 ≤ Z eff ≤ 20), we assess the accuracy and the computational cost of ZVZB forces as the effective pseudopotential valence charge, Z eff , increases. We find that the costs of QMC energies and forces approximately follow simple power laws in Zeff. The force uncertainty grows more rapidly, leading to a best case cost scaling relationship of approximately Z e ff 6.5 ( 3 ) for diffusion Monte Carlo. We find that the accessible system size at fixed computational cost scales as Z e ff &#x2212; 2 , insensitive to model assumptions or the use of the “space warp” variance-reduction technique. Our results predict the practical cost of obtaining forces for a range of materials, such as transition metal oxides where QMC forces have yet to be applied, and underscore the importance of further developing force variance-reduction techniques, particularly for atoms with high Z eff .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗