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All sourcesNASA NTRSDOE OSTI
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 OSTI2026

Ultrafast x-ray imaging of coherently controlled molecular dynamics in real space and time

Coherent control aims to manipulate chemical processes on the latent length and timescales of atoms and bonds, scales that are intrinsic to molecular dynamics but not directly resolved by most experimental probes. As a result, existing coherent-control experiments, which overwhelmingly rely on spectroscopic observables, leave a crucial blind spot: the direct, real-space recovery of all atomic and molecular rearrangements in response to coherently controlled excitations. Here, we overcome this limitation by integrating a Tannor-Kosloff-Rice pump-control-probe scheme with ultrafast X-ray scattering to capture snapshots of the wavepacket motion in a benchmark molecular system. We demonstrate this by photoexciting diatomic iodine vapor with a visible pump pulse, selectively steering the wavepacket toward ground-state recombination or dissociative pathways with a time-delayed near-IR control pulse, and recording the dynamics with angstrom and femtosecond precision with an ultrashort hard X-ray probe pulse. By comparing these structural observations with numerical solutions of the time-dependent Schrödinger equation, we reveal how coherent control actively reshapes the molecular charge density distribution. Our results pave the way for leveraging structural feedback as a control handle and provide a fundamental microscopic visualization of quantum decoherence and energy redistribution at the atomic level.

Hopper, Thomas R. [SLAC National Accelerator Labor↗
DOE OSTI2025

Hyperselective carbon membranes for precise high-temperature H 2 and CO 2 separation

More than 90% of the world’s hydrogen (H 2 ) is produced from fossil fuel sources, which requires energy-intensive separation and purification to produce high-purity H 2 fuel and to capture the carbon dioxide (CO 2 ) by-product. While membranes can decarbonize H 2 /CO 2 separation, their moderate H 2 /CO 2 selectivity requires secondary H 2 purification by pressure swing adsorption. Here, we report hyperselective carbon molecular sieve hollow fiber membranes showing H 2 /CO 2 selectivity exceeding 7000 under mixture permeation at 150°C, which is almost 30 times higher than the most selective nonmetallic membrane reported in the literature. The membrane is able to maintain an ultrahigh H 2 /CO 2 selectivity over 1400 under mixture permeation at 400°C. Pore structure characterization suggests that highly refined ultramicropores are responsible for effectively discriminating the closely sized H 2 and CO 2 molecules in the hyperselective carbon molecular sieve membrane. Modeling shows that the unprecedented H 2 /CO 2 selectivity will potentially allow one-step enrichment of fuel-grade H 2 from shifted syngas for decarbonized H 2 production.

Science & Technology - Other Topics↗
DOE OSTI2026

Temperature Inversions below 1 km from a V-Band Scanning Radiometer at the North Slope of Alaska

A single-channel (56.7 GHz) scanning radiometer was deployed in August 2022 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska site near Utqiaġvik. The radiometer is designed to provide temperature profiles between 0 and 1 km every 5 min. Averaging kernels show that this single-channel radiometer, taking observations at 10 discrete elevation angles, yields approximately the same information as a seven-channel V-band radiometer scanning three elevation angles. The instrument is able to reproduce the occurrence of temperature inversions between the surface and 1 km and their strength showing a correlation of 0.85, bias of −0.6 K, and slope of 1.04 with respect to radiosondes. Uncertainty in the inversion base height varies from 50 m near the surface to ∼300 m above 0.4 km when compared with radiosondes. Conversely, the inversion top height is overestimated and has higher uncertainty due to the degrading effects of the averaging kernels on the vertical resolution of the retrievals. Thanks to the high temporal resolution of the retrievals, the diurnal cycle of boundary layer temperature was evaluated showing that the radiometer can capture some aspects of the boundary layer thermal structure. The present analysis provides an overview of the capabilities of this simple observing configuration for selected applications.

Atmospheric profilers↗
DOE OSTI2024

Computational Modeling of CO2 Capture By Novel PIM-RU in a Fluidized Bed Riser

The interest in carbon capture, storage, and utilization (CCUS) has increased significantly in the past few decades as it can help mitigate the threat of global warming caused by substantial increase in CO2 emissions due to anthropogenic activities. Although several CO2 capture technologies have been developed, porous solid sorbents, which adsorb CO2 by physisorption, are considered promising candidates for post-combustion CO2 capture because of the easier recovery of adsorbed CO2 and high material stability. Some prominent types of porous solid sorbents are metal-organic frameworks (MOFs), Zeolite, mesoporous silica, and polymer-based sorbents (e.g., polymers with intrinsic microporosity or PIM). Oak Ridge National Laboratory (ORNL) recently developed a novel PIM-based sorbent, referred to here as PIM-RU. The main objective of this work is to investigate the CO2 capture performance of this sorbent using computational fluid dynamics (CFD). While process configuration and reactor design are open questions, a fluidized bed riser was selected as the contactor type for this study.

Aziz, Hossain↗
NASA NTRS1993

Single and double charge transfer of He(2+) ions with molecules at near-thermal energies

Rate coefficients were measured for charge-transfer reactions of He(2+) ions with H2, N2, O2, CO, CO2, and H2O. The experiments were carried out using a selected-ion drift-tube mass spectrometer. Total rate coefficients are found to be very large and are generally close to the limiting Langevin capture rate coefficients or the corresponding ADO-model (Su and Bowers, 1973) coefficients. The product-ion spectra indicate that both single and double charge transfer and possibly transfer ionization occur in these reactions.

Tosh, R. E.↗
NASA NTRS2003

Overview of the Design, Development, and Application of Nickel-hydrogen Batteries

This document provides an overview of the design, development, and application of nickel-hydrogen (Ni-H2) battery technology for aerospace applications. It complements and updates the information presented in NASA RP-1314, NASA Handbook for Nickel- Hydrogen Batteries, published in 1993. Since that time, nickel-hydrogen batteries have become widely accepted for aerospace energy storage requirements and much more has been learned. The intent of this document is to capture some of that additional knowledge. This document addresses various aspects of nickel-hydrogen technology including the electrochemical reactions, cell component design, and selection considerations; overall cell and battery design considerations; charge control considerations; and manufacturing issues that have surfaced over the years that nickel-hydrogen battery technology has been the major energy storage technology for geosynchronous and low-Earth-orbiting satellites.

Thaller, Lawrence H.↗
NASA NTRS2004

Characterizing the effects of droplines on target acquisition performance on a 3-D perspective display

The present study investigated the effects of droplines on target acquisition performance on a 3-D perspective display in which participants were required to move a cursor into a target cube as quickly as possible. Participants' performance and coordination strategies were characterized using both Fitts' law and acquisition patterns of the 3 viewer-centered target display dimensions (azimuth, elevation, and range). Participants' movement trajectories were recorded and used to determine movement times for acquisitions of the entire target and of each of its display dimensions. The goodness of fit of the data to a modified Fitts function varied widely among participants, and the presence of droplines did not have observable impacts on the goodness of fit. However, droplines helped participants navigate via straighter paths and particularly benefited range dimension acquisition. A general preference for visually overlapping the target with the cursor prior to capturing the target was found. Potential applications of this research include the design of interactive 3-D perspective displays in which fast and accurate selection and manipulation of content residing at multiple ranges may be a challenge.

Time and Motion Studies↗
NASA NTRS2015

Analytic Thermoelectric Couple Modeling: Variable Material Properties and Transient Operation

To gain a deeper understanding of the operation of a thermoelectric couple a set of analytic solutions have been derived for a variable material property couple and a transient couple. Using an analytic approach, as opposed to commonly used numerical techniques, results in a set of useful design guidelines. These guidelines can serve as useful starting conditions for further numerical studies, or can serve as design rules for lab built couples. The analytic modeling considers two cases and accounts for 1) material properties which vary with temperature and 2) transient operation of a couple. The variable material property case was handled by means of an asymptotic expansion, which allows for insight into the influence of temperature dependence on different material properties. The variable property work demonstrated the important fact that materials with identical average Figure of Merits can lead to different conversion efficiencies due to temperature dependence of the properties. The transient couple was investigated through a Greens function approach; several transient boundary conditions were investigated. The transient work introduces several new design considerations which are not captured by the classic steady state analysis. The work helps to assist in designing couples for optimal performance, and also helps assist in material selection.

Seebeck Effect↗
NASA NTRS2017

Lucy: Navigating a Jupiter Trojan Tour

In January 2017, NASA selected the Lucy mission to explore six Jupiter Trojan asteroids. These six bodies, remnants of the primordial material that formed the outer planets, were captured in the Sun-Jupiter L4 and L5 Lagrangian regions early in the solar system formation. These particular bodies were chosen because of their diverse spectral properties and the chance to observe up close for the first time two orbiting approximately equal mass binaries, Patroclus and Menoetius. KinetX, Inc. is the primary navigation supplier for the Lucy mission. This paper describes preliminary navigation analyses of the approach phase for each Trojan encounter.

trajectory design↗
NASA NTRSDate not supplied

Mitigating the Impacts of Measurement Error in the Quesst Mission Community Noise Study

Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.

measurement error↗
DOE OSTI2026

Water as a gas separation membrane

Efficient gas separation membranes are essential for carbon capture, biogas upgrading, and hydrogen purification. Inspired by how plants absorb CO 2 through water, we present a membrane platform that uses liquid water as the selective layer. Hydrophilic sub-100-nm pores stabilize water through strong capillary forces, enabling operation at feed pressures above 72 bar under dry and humid conditions. Selectivity is governed by gas solubility in water, while permeance is tuned by adjusting the water layer thickness. Reducing this thickness below 200 nm yields CO 2 permeances up to 11,600 gas permeation units with CO 2 :N 2 , CO 2 :CH 4 , and CO 2 :H 2 selectivities of 40, 26, and 31, respectively, surpassing the performance of state-of-the-art membranes. Operation is sustained for over a week without water loss, and performance scales using commercially available porous polymer supports under mixed-gas crossflow conditions. Water’s dissolution-based transport avoids saturation and reaction-rate limits, enabling a robust, high-performance, and environmentally benign gas separation platform.

08 HYDROGEN↗
NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗
NASA NTRS2011

Introduction of structural affinity handles as a tool in selective nucleic acid separations

The method is used for separating nucleic acids and other similar constructs. It involves selective introduction, enhancement, or stabilization of affinity handles such as single-strandedness in the undesired (or desired) nucleic acids as compared to the usual structure (e.g., double-strandedness) of the desired (or undesired) nucleic acids. The undesired (or desired) nucleic acids are separated from the desired (or undesired) nucleic acids due to capture by methods including but not limited to immobilized metal affinity chromatography, immobilized single-stranded DNA binding (SSB) protein, and immobilized oligonucleotides. The invention is useful to: remove contaminating genomic DNA from plasmid DNA; remove genomic DNA from plasmids, BACs, and similar constructs; selectively separate oligonucleotides and similar DNA fragments from their partner strands; purification of aptamers, (deoxy)-ribozymes and other highly structured nucleic acids; Separation of restriction fragments without using agarose gels; manufacture recombinant Taq polymerase or similar products that are sensitive to host genomic DNA contamination; and other applications.

Willson, III, Richard Coale↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Spin-selective photocatalysis and quantum transport using ab initio density-matrix dynamics

The overarching goal of this research program is to quantitatively predict out-of-equilibrium quantum dynamics and transport with electrons and spin degrees of freedom coupled to phonons, photons, defects and liquid environments, specifically targeting spin-selective chemistry. Spin polarized carriers, which can be generated at room temperature by circularly-polarized light, provide unique opportunities for creating new reaction pathways and increasing selectivity towards specific pathways. If realized, this can substantially increase the level of reaction control possible in the field of heterogeneous catalysis. Spin, a quantum mechanical entity without a classical counterpart, requires quantum dynamics. Capturing both coherent and incoherent dynamics and accurate correlation of spins, electrons and phonon environments are essential to quantitative description of generation, relaxation and transport, as well as chemical reaction of spin-polarized carriers in molecules and materials promising for spin-photocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K

Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.

42 ENGINEERING↗
DOE OSTI2020

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗