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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Chemical templates of the Central Molecular Zone

Context . The Central Molecular Zone (CMZ) of the Milky Way exhibits extreme conditions, including high gas densities, elevated temperatures, enhanced cosmic-ray ionization rates, and large-scale dynamics. This makes it a perfect laboratory for astrochemical studies. With large-scale molecular surveys revealing increasing chemical and physical complexity in the CMZ, it is essential to develop robust methods to decode the chemical information embedded in this extreme region. Aims . A key step to interpreting the molecular richness found in the CMZ is building chemical templates tailored to its diverse conditions. In particular, understanding how CMZ environments affect shock and protostellar chemistry is crucial. The combined impact of high ionization, elevated temperatures, and dense gas remains insufficiently explored for observable tracers. Methods . For this study, we utilized UCLCHEM , a gas-grain time-dependent chemical model, to link physical conditions with their corresponding molecular signatures and identify key tracers of temperature, density, ionization, and shock activity. To achieve this, we ran a grid of models of shocks and protostellar objects representative of typical CMZ conditions, focusing on 24 species, including complex organic molecules. Results . Shocked and protostellar environments show distinct evolutionary timescales (≲10 4 vs. ≳10 4 years); 300 K emerges as a key temperature threshold for chemical differentiation. We find that cosmic-ray ionization and temperature are the main drivers of chemical trends. HCO + , H 2 CO, and CH 3 SH trace ionization, while HCO, HCO + , CH 3 SH, CH 3 NCO, and HCOOCH 3 show consistent abundance contrasts between shocks and protostellar regions over similar temperature ranges. Conclusions . We characterized the behavior of 24 species in protostellar and shock-related environments. While our models underpredict some complex organics in shocks, they reproduce observed trends for most species, supporting scenarios involving a need for recurring shocks in Galactic Center clouds and enhanced ionization toward Sgr B2(N2). Future work should assess the role of shock recurrence and metallicity in shaping chemistry.

Galaxy: center↗
DOE OSTI2020

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Compact single-shot electro-optic detection system for THz pulses with femtosecond time resolution at MHz repetition rates

Electro-optical detection has proven to be a valuable technique to study temporal profiles of THz pulses with pulse durations down to femtoseconds. As the Coulomb field around a relativistic electron bunch resembles the current profile, electro-optical detection can be exploited for non-invasive bunch length measurements at accelerators. We have developed a very compact and robust electro-optical detection system based on spectral decoding for single-shot longitudinal bunch profile monitoring at the European X-ray Free Electron Laser (XFEL) for electron bunch lengths down to 200 fs (rms). Apart from the GaP crystal and the corresponding laser optics at the electron beamline, all components are housed in 19 in. chassis for rack mount and remote operation inside the accelerator tunnel. An advanced laser synchronization scheme based on radio-frequency down-conversion has been developed for locking a custom-made Yb-fiber laser to the radio-frequency of the European XFEL accelerator. In order to cope with the high bunch repetition rate of the superconducting accelerator, a novel linear array detector has been employed for spectral measurements of the Yb-fiber laser pulses at frame rates of up to 2.26 MHz. In this paper, we describe all sub-systems of the electro-optical detection system as well as the measurement procedure in detail and discuss the first measurement results of longitudinal bunch profiles of around 400 fs (rms) with an arrival-time jitter of 35 fs (rms).

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Featureless adaptive optimization accelerates functional electronic materials design

Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and bandgap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep learning-based quasi-continuum theory for structure of confined fluids

Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfacial structure of fluids. In this work, we develop a deep learning-based quasi-continuum theory (DL-QT) to predict the concentration and potential profiles of a Lennard-Jones (LJ) fluid and water confined in a nanochannel. The deep learning model is built based on a convolutional encoder–decoder network (CED) and is applied for high-dimensional surrogate modeling to relate the fluid properties to the fluid–fluid potential. The CED model is then combined with the interatomic potential-based continuum theory to determine the concentration profiles of a confined LJ fluid and confined water. Further, we show that the DL-QT model exhibits robust predictive performance for a confined LJ fluid under various thermodynamic states and for water confined in a nanochannel of different widths. The DL-QT model seamlessly connects molecular physics at the nanoscale with continuum theory by using a deep learning model.

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

Unsupervised machine learning discovery of structural units and transformation pathways from imaging data

We show that unsupervised machine learning can be used to learn chemical transformation pathways from observational Scanning Transmission Electron Microscopy (STEM) data. To enable this analysis, we assumed the existence of atoms, a discreteness of atomic classes, and the presence of an explicit relationship between the observed STEM contrast and the presence of atomic units. With only these postulates, we developed a machine learning method leveraging a rotationally invariant variational autoencoder (VAE) that can identify the existing molecular fragments observed within a material. The approach encodes the information contained in STEM image sequences using a small number of latent variables, allowing the exploration of chemical transformation pathways by tracing the evolution of atoms in the latent space of the system. The results suggest that atomically resolved STEM data can be used to derive fundamental physical and chemical mechanisms involved, by providing encodings of the observed structures that act as bottom-up equivalents of structural order parameters. The approach also demonstrates the potential of variational (i.e., Bayesian) methods in the physical sciences and will stimulate the development of more sophisticated ways to encode physical constraints in the encoder–decoder architectures and generative physical laws and causal relationships in the latent space of VAEs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Diffractive optical elements for multiplexing structured laser beams

We consider methods for obtaining a multitude of structured laser beams (multiplexing) from an illuminating beam (both structured and unstructured) with the help of diffractive optical elements (DOEs). An approach of ‘intelligent multiplexing’ is proposed to describe and develop the methods. A DOE is calculated that forms a set of five diffraction orders located in a line. An example of focusing a set of doughnut-shaped azimuthally polarised laser beams using a diffraction beam splitter is presented. Efficient multiplexing of first-order vortex beams in a two-dimensional region is implemented by a two-dimensional diffraction grating. An approach is proposed and realised in which the transmission functions of a two-dimensional diffraction beam splitter and the elements forming structured laser beams with specified parameters are combined into the transmission function of one element. Such DOEs can be used in optical communication systems for encoding and decoding data. The possibility of using binary curved fork-shaped gratings for the formation of doughnut-shaped three-dimensional vortex beams, which are detected outside the focal plane, is demonstrated. This approach provides additional advantages for safe data transmission; it can be used in laser processing of materials and in laser manipulation applications. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Elongation factor-Tu can repetitively engage aminoacyl-tRNA within the ribosome during the proofreading stage of tRNA selection

The substrate for ribosomes actively engaged in protein synthesis is a ternary complex of elongation factor Tu (EF-Tu), aminoacyl-tRNA (aa-tRNA), and GTP. EF-Tu plays a critical role in mRNA decoding by increasing the rate and fidelity of aa-tRNA selection at each mRNA codon. Here, using three-color single-molecule fluorescence resonance energy transfer imaging and molecular dynamics simulations, we examine the timing and role of conformational events that mediate the release of aa-tRNA from EF-Tu and EF-Tu from the ribosome after GTP hydrolysis. Our investigations reveal that conformational changes in EF-Tu coordinate the rate-limiting passage of aa-tRNA through the accommodation corridor en route to the peptidyl transferase center of the large ribosomal subunit. Experiments using distinct inhibitors of the accommodation process further show that aa-tRNA must at least partially transit the accommodation corridor for EF-Tu∙GDP to release. aa-tRNAs failing to undergo peptide bond formation at the end of accommodation corridor passage after EF-Tu release can be reengaged by EF-Tu∙GTP from solution, coupled to GTP hydrolysis. These observations suggest that additional rounds of ternary complex formation can occur on the ribosome during proofreading, particularly when peptide bond formation is slow, which may serve to increase both the rate and fidelity of protein synthesis at the expense of GTP hydrolysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Sarecycline interferes with tRNA accommodation and tethers mRNA to the 70S ribosome

Sarecycline is a new narrow-spectrum tetracycline-class antibiotic approved for the treatment of acne vulgaris. Tetracyclines share a common four-ring naphthacene core and inhibit protein synthesis by interacting with the 70S bacterial ribosome. Sarecycline is distinguished chemically from other tetracyclines because it has a 7-[[methoxy(methyl)amino]methyl] group attached at the C7 position of ring D. To investigate the functional role of this C7 moiety, we determined the X-ray crystal structure of sarecycline bound to the Thermus thermophilus 70S ribosome. Our 2.8-Å resolution structure revealed that sarecycline binds at the canonical tetracycline binding site located in the decoding center of the small ribosomal subunit. Importantly, unlike other tetracyclines, the unique C7 extension of sarecycline extends into the messenger RNA (mRNA) channel to form a direct interaction with the A-site codon to possibly interfere with mRNA movement through the channel and/or disrupt A-site codon–anticodon interaction. Based on our biochemical studies, sarecycline appears to be a more potent initiation inhibitor compared to other tetracyclines, possibly due to drug interactions with the mRNA, thereby blocking accommodation of the first aminoacyl transfer RNA (tRNA) into the A site. Overall, our structural and biochemical findings rationalize the role of the unique C7 moiety of sarecycline in antibiotic action.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Anomalous magnetic noise in an imperfectly flat landscape in the topological magnet Dy 2 Ti 2 O 7

Noise generated by motion of charge and spin provides a unique window into materials at the atomic scale. From temperature of resistors to electrons breaking into fractional quasiparticles, “listening” to the noise spectrum is a powerful way to decode underlying dynamics. Here, we use ultrasensitive superconducting quantum interference device (SQUIDs) to probe the puzzling noise in a frustrated magnet, the spin-ice compound Dy 2 Ti 2 O 7 (DTO), revealing cooperative and memory effects. DTO is a topological magnet in three dimensions—characterized by emergent magnetostatics and telltale fractionalized magnetic monopole quasiparticles—whose real-time dynamical properties have been an enigma from the very beginning. We show that DTO exhibits highly anomalous noise spectra, differing significantly from the expected Brownian noise of monopole random walks, in three qualitatively different regimes: equilibrium spin ice, a “frozen” regime extending to ultralow temperatures, and a high-temperature “anomalous” paramagnet. We present several distinct mechanisms that give rise to varied colored noise spectra. In addition, we identify the structure of the local spin-flip dynamics as a crucial ingredient for any modeling. Thus, the dynamics of spin ice reflects the interplay of local dynamics with emergent topological degrees of freedom and a frustration-generated imperfectly flat energy landscape, and as such, it points to intriguing cooperative and memory effects for a broad class of magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

30S subunit recognition and G1405 modification by the aminoglycoside-resistance 16S ribosomal RNA methyltransferase RmtC

Acquired ribosomal RNA (rRNA) methylation has emerged as a significant mechanism of aminoglycoside resistance in pathogenic bacterial infections. Modification of a single nucleotide in the ribosome decoding center by the aminoglycoside-resistance 16S rRNA (m 7 G1405) methyltransferases effectively blocks the action of all 4,6-deoxystreptamine ring-containing aminoglycosides, including the latest generation of drugs. To define the molecular basis of 30S subunit recognition and G1405 modification by these enzymes, we used a S-adenosyl-L-methionine analog to trap the complex in a postcatalytic state to enable determination of a global 3.0 Å cryo-electron microscopy structure of the m 7 G1405 methyltransferase RmtC bound to the mature Escherichia coli 30S ribosomal subunit. This structure, together with functional analyses of RmtC variants, identifies the RmtC N-terminal domain as critical for recognition and docking of the enzyme on a conserved 16S rRNA tertiary surface adjacent to G1405 in 16S rRNA helix 44 (h44). To access the G1405 N7 position for modification, a collection of residues across one surface of RmtC, including a loop that undergoes a disorder-to order transition upon 30S subunit binding, induces significant distortion of h44. This distortion flips G1405 into the enzyme active site where it is positioned for modification by two almost universally conserved RmtC residues. Further, these studies expand our understanding of ribosome recognition by rRNA modification enzymes and present a more complete structural basis for future development of strategies to inhibit m 7 G1405 modification to resensitize bacterial pathogens to aminoglycosides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Engineered mRNA–ribosome fusions for facile biosynthesis of selenoproteins

Ribosomes are often used in synthetic biology as a tool to produce desired proteins with enhanced properties or entirely new functions. However, repurposing ribosomes for producing designer proteins is challenging due to the limited number of engineering solutions available to alter the natural activity of these enzymes. In this study, we advance ribosome engineering by describing a novel strategy based on functional fusions of ribosomal RNA (rRNA) with messenger RNA (mRNA). Specifically, we create an mRNA–ribosome fusion called RiboU, where the 16S rRNA is covalently attached to selenocysteine insertion sequence (SECIS), a regulatory RNA element found in mRNAs encoding selenoproteins. When SECIS sequences are present in natural mRNAs, they instruct ribosomes to decode UGA codons as selenocysteine (Sec, U) codons instead of interpreting them as stop codons. This enables ribosomes to insert Sec into the growing polypeptide chain at the appropriate site. Our work demonstrates that the SECIS sequence maintains its functionality even when inserted into the ribosome structure. As a result, the engineered ribosomes RiboU interpret UAG codons as Sec codons, allowing easy and site-specific insertion of Sec in a protein of interest with no further modification to the natural machinery of protein synthesis. To validate this approach, we use RiboU ribosomes to produce three functional target selenoproteins in Escherichia coli by site-specifically inserting Sec into the proteins’ active sites. Overall, our work demonstrates the feasibility of creating functional mRNA–rRNA fusions as a strategy for ribosome engineering, providing a novel tool for producing Sec-containing proteins in live bacterial cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A 100-Mrad (Si) JFET-based Sensing and Communications System for Extreme Nuclear Instrumentation Environments

Dry cask storage is one of two storage methods approved by the U.S. Nuclear Regulatory Commission for spent fuel after removal from reactor cores. Dry casks consist of a stainless steel canister enclosed in a concrete overpack to contain the hazardous radioactive spent fuel rods and provide radiation shielding. Monitoring spent fuel storage casks is desired to ensure the safe containment of the enclosed spent fuel, but is very difficult due to the related harsh temperature and radiation environment. The sensors and associated electronics to monitor temperature, pressure, and/or radiation need to survive high temperatures and radiation doses for extended time periods. For this reason, there is a severe need for radiation-hardened electrical systems that survive well beyond the existing capabilities of commercially available radiation-rated electronic components, which have primarily been developed for space applications. Junction-gate field-effect transistor (JFET) devices are inherently radiation hardened [exceeding 100 Mrad (Si)]. Additionally, when JFETs are used as building blocks for sensing and communication electronics (i.e., oscillators, amplifiers, filters, and mixers), inherently radiation-hardened circuits can be achieved. To this end, JFET-based radiation-hardened electronics interfacing with cask-embedded sensors capable of driving modulated sensor signals through a stainless steel barrier were designed and tested at a dose rate of approximately 500 krad/h (Si) to beyond a 200-Mrad (Si) total ionizing dose. After 200 Mrad (Si), the sensor and communication circuit signals were correctly decoded at the receiver despite oscillator drift. The results from this experiment demonstrate the potential for creating more complex radiation-hardened JFET-based electrical systems for nuclear environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

ML-Based Pebble Power Reconstruction for Pebble Bed Reactor Analysis

Pebble power reconstruction has been explored to complement the conventional homogenized modeling approach in pebble bed reactor (PBR) analysis, as detailed heterogeneous geometry calculations are computationally expensive. The random distribution of pebble fuels within the core challenges the application of conventional pin power reconstruction methods. To address this, we introduce a machine learning approach based on the transformer model, composed of encoder and decoder layers, to estimate the flux and power form functions for reconstructing individual pebble neutron fluxes and powers. The homogeneous neutron flux distribution within each spectral zone (SZ) is obtained from finite element solutions of global diffusion or transport calculations. Verification tests demonstrate that the trained transformer model accurately predicts power form functions over a range of conditions, including variations in pebble enrichment, location, type, SZ size, and burnup. In particular, verification using a three-dimensional PBR benchmark with burned pebbles shows good agreement in heterogeneous pebble power distributions between Griffin and Serpent. These results highlight the potential of applying conventional pin power reconstruction approaches to PBR cores with randomly distributed pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Imaging nuclei by smashing them at high energies: how are their shapes revealed after destruction?

High-energy nuclear collisions have recently emerged as a promising ‘imaging-by-smashing’ approach to reveal the intrinsic shapes of atomic nuclei. Here, I outline a conceptual framework for this technique, explaining how nuclear shapes are encoded during quark–gluon plasma (QGP) formation and evolution, and how they can be decoded from final-state particle distributions. Furthermore, I highlight the method’s potential to advance our understanding of both nuclear structure and QGP physics.

imaging by smashing↗
DOE OSTI2021

Data transmission by quantum matter wave modulation

Abstract Classical communication schemes exploiting wave modulation are the basis of our information era. Quantum information techniques with photons enable future secure data transfer in the dawn of decoding quantum computers. Here we demonstrate that also matter waves can be applied for secure data transfer. Our technique allows the transmission of a message by a quantum modulation of coherent electrons in a biprism interferometer. The data is encoded in the superposition state by a Wien filter introducing a longitudinal shift between separated matter wave packets. The transmission receiver is a delay line detector performing a dynamic contrast analysis of the fringe pattern. Our method relies on the Aharonov–Bohm effect but does not shift the phase. It is demonstrated that an eavesdropping attack will terminate the data transfer by disturbing the quantum state and introducing decoherence. Furthermore, we discuss the security limitations of the scheme due to the multi-particle aspect and propose the implementation of a key distribution protocol that can prevent active eavesdropping.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Abstract Objective. Optically pumped magnetometers (OPMs) are emerging as a near-room-temperature alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). In contrast to SQUIDs, OPMs can be placed in a close proximity to subject’s scalp potentially increasing the signal-to-noise ratio and spatial resolution of MEG. However, experimental demonstrations of these suggested benefits are still scarce. Here, to compare a 24-channel OPM-MEG system to a commercial whole-head SQUID system in a data-driven way, we quantified their performance in classifying single-trial evoked responses. Approach. We measured evoked responses to three auditory tones in six participants using both OPM- and SQUID-MEG systems. We performed pairwise temporal classification of the single-trial responses with linear discriminant analysis as well as multiclass classification with both EEGNet convolutional neural network and xDAWN decoding. Main results. OPMs provided higher classification accuracies than SQUIDs having a similar coverage of the left hemisphere of the participant. However, the SQUID sensors covering the whole helmet had classification scores larger than those of OPMs for two of the tone pairs, demonstrating the benefits of a whole-head measurement. Significance. The results demonstrate that the current OPM-MEG system provides high-quality data about the brain with room for improvement for high bandwidth non-invasive brain–computer interfacing.

Iivanainen, Joonas (ORCID:0000000160344604)↗
DOE OSTI2022

Event driven readout architecture with non-priority arbitration for radiation detectors

A novel event driven readout architecture, EDWARD (Event Driven with Access and 8 Reset Decoder) architecture, for highly granular pixel detectors is presented. It incorporates, inter alia, an asynchronous arbitration tree based on Seitz' arbiters, removing the need for an imposed prioritization scheme. It also provides protection against glitches during readout. The system allows not only reading pixel activities, but also retrieving additional data, both analog and digital, from the pixels. A novel in-channel logic allows the entire readout process to be split into consecutive phases for additional flexibility. All operations are controlled by only one edge of the clock signal, seen as an acknowledge token, so there is no dead time between readouts.

47 OTHER INSTRUMENTATION↗