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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Correlating structural changes in thermoresponsive hydrogels to the optical response of embedded plasmonic nanoparticles

Stimuli-responsive microgels, composed of small beads with soft, deformable polymer networks swollen through a combination of synthetic control over the polymer and its interaction with water, form a versatile platform for development of multifunctional and biocompatible sensors. The interfacial structural variation of such materials at a nanometer length scale is essential to their function, but not yet fully comprehended. Here, we take advantage of the plasmonic response of a gold nanorod embedded in a thermoresponsive microgel (AuNR@PNIPMAm) to monitor structural changes in the hydrogel directly near the nanorod surface. By direct comparison of the plasmon response against measurements of the hydrogel structure from dynamic light scattering and nuclear magnetic resonance, we find that the microgel shell of batch-polymerized AuNR@PNIPMAm exhibits a heterogeneous volume phase transition reflected by different onset temperatures for changes in the hydrodyanmic radius (R H ) and plasmon resonance, respectively. The new approach of contrasting plasmonic response (a measure of local surface hydrogel structure) with R H and relaxation times paves a new path to gain valuable insight for the design of plasmonic sensors based on stimuli-responsive hydrogels.

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

ZTF-SEDm Type Ia supernova sample for Twins Embedding spectrophotometric standardization

Aims. This paper has two aims: the first aim is to build a large homogeneous spectrophotometric sample of Type Ia supernovae (SNe Ia) from the second data release of the Zwicky Transient Facility (ZTF DR2). We used the spectrum sample from the low-resolution ( R ∼ 100) SEDmachine (SEDm) Integral Field Spectrograph (IFS) that gathered 3069 spectra. This is one of the largest samples of such collections that can attempt to reproduce the Twins Embedding (TE) spectrophotometric standardization method. This is our second objective. The method was developed based on high-quality spectra from 200 SNe Ia of the Nearby Supernova factory (SNfactory) and led to an exceptionally low value of 0.073 mag for the intrinsic scatter. Methods. As the SEDm is not designed as a spectrophotometric instrument, we first improved the flux-calibration accuracy of the SN Ia spectrum sample using the ZTF photometric data, which were calibrated at the percent level. We corrected the spectra for second-order polynomials, fitted by comparing the synthetic photometry in the ZTF g , r , i filters with the light-curve (LC) data. We then applied the three steps of the TE parameterization to a subset of 783 ZTF SN spectra near maximum light while comparing results from SNfactory and ZTF. We finally analyzed the standardization methods based on the TE parameters. Results. The precision of the phase-correction model, which is the first step of the TE, is estimated at 0.01 mag in g band based on ZTF data. Despite the challenge posed by the spectrum-extraction pipeline associated with the SEDm (flux calibration, leftover host signal, low signal-to-noise ratio, and low resolution), we applied a first standardization in color based on the second step of the TE, called read between the lines (RBTL), to the ZTF sample. We reached a Hubble residual scatter of 0.153 mag, all in normalized median absolute deviation, which is to be compared to the ∼0.11 mag obtained with the SNfactory data. The SALT color and stretch standardization reaches a scatter of 0.164 mag for the same ZTF SN Ia sample, and its host steps are ∼0.1 mag and zero for RBTL. When considering the scatter due to the redshift error and flux calibration error, we estimated a RBTL scatter of ∼0.129 mag for this ZTF sample as an upper limit because we identified an additional contribution from a systematic error in color. We tested the standardization based on the nonlinear TE parameters, and, as expected from the low spectrum quality, it did not improve the overall dispersion. Conclusions. We release 1897 flux calibrated spectra of 1607 SNe Ia with an estimated photometric accuracy of 0.07 mag. We further demonstrate that some amount of spectrophotometric SN Ia standardization can be done with limited-quality spectra. The RBTL standardization is more efficient than that of SALT with one parameter less, and the resulting host steps are consistent with zero. This makes it less prone to astrophysical bias. For future spectroscopic surveys, targeting the extraction pipeline for a thorough flux calibration and good signal-to-noise ratio would enable us to compute the full TE standardization, which would further reduce the scatter in the distance estimate.

Ganot, C↗
DOE OSTI2024

High pressure melt line of nickel using a generalized embedded atomic method potential

As the second most abundant metal in the Earth's core, nickel plays an important role in determining the structure and temperature of the Earth's core. Yet, the melt line of Ni at pressures corresponding to the Earth's core has not been explored in the literature. Many previous experimental and simulation efforts have reported the melting point of Ni at pressures below 100 GPa, but there exist large discrepancies, most of which have persisted due to various experimental and simulation bottlenecks in handling extreme pressure and temperature conditions. We adopted the generalized embedded atom method, which overcomes the limitations of existing interatomic potentials, to probe phase stability and phase boundaries of Ni at pressures between 50 and 500 GPa. Further, the potential was validated by comparing the cold curves, phonon dispersion curves, and enthalpies of fusion with ab initio density functional theory calculations. Our analysis shows that face centered cubic (FCC) is stable, and the hexagonal close packed (HCP) and body centered cubic (BCC) phases are metastable close to the melt line. Melting temperatures at different pressures were obtained from two-phase co-existence simulations and take the following functional form: $T$ m = $1969.23+19.15P-0.012P$ 2 . In contrast to iron, differences between the melting points of the stable and metastable phases of Ni are less than 250 K at 300 GPa, and the difference in melting points of the metastable BCC and HCP phases changes sign at 500 GPa, which implies that the phase transition mechanisms during solidification can be very complex.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating and contrasting the mechanisms for Mg and Ca sulfate ion-pair formation with multi-level embedded quantum mechanics/molecular dynamics simulations

Here, solutions and minerals containing sulfate (SO 4 2- ), and Ca 2+ and Mg 2+ cations, are ubiquitous throughout the lithosphere and are significant components of seawater, thus presenting a prototypical system for the study of strong electrolytes and crystal nucleation mechanisms. However, despite their relative abundance, key questions remain unanswered about the most fundamental atomic-level steps of their mineralization pathways and aqueous dynamics. Here, we carry out enhanced sampling multi-level molecular dynamics (MD) embedded correlated wavefunction theory simulations to elucidate ion-pairing mechanisms for Mg–SO 4 and Ca–SO 4 in concentrated aqueous solution, accurately capturing effects arising from both structural dynamics and electron exchange–correlation. We predict contact-ion-pair formation to be barrierless and highly exoergic for Ca–SO 4 , in agreement with its minimal solubility, whereas for Mg–SO 4 , solvent-shared and contact ion pairs have similar free energies, qualitatively consistent with its higher solubility. Finally, we demonstrate that brief high-temperature pre-equilibration may be utilized to accelerate convergence of free energies in blue-moon-ensemble enhanced-sampling MD.

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

Metal–bicarbonate ion pairing in alkaline aqueous solutions from multilevel embedded correlated wavefunction theory and molecular dynamics

In this work, we examine ion-pairing mechanisms of bicarbonates in alkaline aqueous solutions with the divalent metal ions most abundantly present in seawater, namely, Ca 2+ and Mg 2+ . We employ a rare-event enhanced sampling approach within first-principles molecular dynamics to explore regions of phase space spanning solvent-shared to contact ion pairs. Second-order Møller–Plesset perturbation theory (MP2) corrections are subsequently applied in an embedding framework (EMB) to refine the electronic structure of stationary states and associated reaction barriers along the free-energy profiles while retaining the extended solvent effects at the density functional theory (DFT) level. Ca 2+ –HCO 3 − was previously hypothesized to exist in a solvent-shared ion pair (SSHIP) by DFT studies with an endergonic contact ion pair (CIP) formation; however, our EMB-MP2 refinement of the DFT ion-pairing pathways reveals that Ca 2+ and HCO 3 − form a virtually barrier-free CIP in alkaline solutions, with even more energetic ease than the widely studied Ca–CO 3 ion pair. We find qualitative agreement between DFT and EMB-MP2 for Mg 2+ —unlike Ca 2+ , Mg 2+ refuses to shed its strong hydration shell, thereby preferring a SSHIP state with a significant activation barrier to crossover to the CIP forms—a trait reminiscent of ion pairing in Mg–CO 3 and closely related to the kinetic limitations underlying the famous subject of the dolomite problem. Our study highlights the importance of improved electronic structure descriptions of liquids, modeled as a condensed phase of matter lacking in long-range crystalline order. It also strongly suggests that Ca 2+ –HCO 3 − CIPs are likely precursors involved in prenucleation of CaCO 3 mineral formation in seawater.

Sharma, Vidushi [Princeton Plasma Physics Laborato↗
DOE OSTI2022

Charting C–C coupling pathways in electrochemical CO 2 reduction on Cu(111) using embedded correlated wavefunction theory

The electrochemical CO 2 reduction reaction (CO 2 RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C 2+ ) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO 2 RR electrocatalysts is mechanistic analysis of the best metal catalyst thus far identified, namely, copper (Cu), via quantum mechanical computations to complement experiments. Here, we apply embedded correlated wavefunction (ECW) theory, which regionally corrects the electron exchange-correlation error in density functional theory (DFT) approximations, to examine multiple C–C coupling steps involving adsorbed CO (*CO) and its hydrogenated derivatives on the most ubiquitous facet, Cu(111). We predict that two adsorbed hydrogenated CO species, either *COH or *CHO, are necessary precursors for C–C bond formation. The three kinetically feasible pathways involving these species yield all three possible products: *COH–CHO, *COH–*COH, and *OCH–*OCH. The most kinetically favorable path forms *COH–CHO. In contrast, standard DFT approximations arrive at qualitatively different conclusions, namely, that only *CO and *COH will prevail on the surface and their C–C coupling paths produce only *COH–*COH and *CO–*CO, with a preference for the first product. This work demonstrates the importance of applying qualitatively and quantitatively accurate quantum mechanical method to simulate electrochemistry in order ultimately to shed light on ways to enhance selectivity toward C 2+ product formation via CO 2 RR electrocatalysts.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Atomistic simulation of brittle-to-ductile transition in silicon carbide embedded with nano-sized helium bubbles

In this study, the tensile response of cubic silicon carbide (SiC) bulk containing cavities (voids and He bubbles) has been investigated using molecular dynamic simulations. The formation of cavities in SiC leads to a significant degradation in the mechanical properties of SiC with more influence on material fracture than initial elastic deformation. The brittle-to-ductile transition occurs in cavity-embedded SiC as the pressure in He bubbles increases. This is associated with the deformation mechanism that bond breaking at a low He bubble pressure transfers to extensive dislocation activities at a higher He bubble pressure. The cavities can effectively concentrate stress around them in the direction perpendicular to the tension, which leads to preferred cracking in the region with a higher tensile stress. The failure mechanism as revealed by this study improves understanding of property degradation in SiC that may be useful for applications of SiC in advanced nuclear energy systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Study of carbon nanotube embedded honey as a resistive switching material

In this paper, natural organic honey embedded with carbon nanotubes (CNTs) was studied as a resistive switching material for biodegradable nonvolatile memory in emerging neuromorphic systems. CNTs were dispersed in a honey-water solution with the concentration of 0.2 wt% CNT and 30 wt% honey. The final honey-CNT-water mixture was spin-coated and dried into a thin film sandwiched in between Cu bottom electrode and Al top electrode to form a honey-CNT based resistive switching memory (RSM). Surface morphology, electrical characteristics and current conduction mechanism were investigated. The results show that although CNTs formed agglomerations in the dried honey-CNT film, both switching speed and the stability in SET and RESET process of honey-CNT RSM were improved. The mechanism of current conduction in CNT is governed by Ohm’s law in low-resistance state and the low-voltage range in high-resistance state, but transits to the space charge limited conduction at high voltages approaching the SET voltage.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Design and implementation of the AMIGA embedded system for data acquisition

The Auger Muon Infill Ground Array (AMIGA) is part of the AugerPrime upgrade of the Pierre Auger Observatory. It consists of particle counters buried 2.3 m underground next to the water-Cherenkov stations that form the 23.5 km 2 large infilled array. The reduced distance between detectors in this denser area allows the lowering of the energy threshold for primary cosmic ray reconstruction down to about 1017 eV. At the depth of 2.3 m the electromagnetic component of cosmic ray showers is almost entirely absorbed so that the buried scintillators provide an independent and direct measurement of the air showers muon content. This work describes the design and implementation of the AMIGA embedded system, which provides centralized control, data acquisition and environment monitoring to its detectors. The presented system was firstly tested in the engineering array phase ended in 2017, and lately selected as the final design to be installed in all new detectors of the production phase. The system was proven to be robust and reliable and has worked in a stable manner since its first deployment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Embedded FPGA developments in 130 nm and 28 nm CMOS for machine learning in particle detector readout

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Embedded EPICS server for PowerPMAC motion controllers

An embedded server layer of Experimental Physics and Industrial Control System (EPICS) for PowerPMAC motion controllers has been developed and deployed at two undulator beamlines of the National Institute of General Medical Sciences and the National Cancer Institute (GM/CA) Structural Biology Facility at the Advanced Photon Source (APS). This compact, open source solution makes the power and versatility of PowerPMAC motion controls directly accessible to distributed EPICS clients. At GM/CA the system controls about 200 servo and stepper motors — both encoded and unencoded — and multiple digital and analog I/O accessories. The server stack comprises two sublayers: a lower-level driver and database that communicates directly with PowerPMAC, and a facility-specific soft sublayer built on top. The paper describes installing EPICS on PowerPMAC, the implementation of both layers and client examples, including on-the-fly scanning.

EPICS↗
DOE OSTI2025

SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing

MOTIVATION: High-throughput sequencing (HTS) is a modern sequencing technology used to profile microbiomes by sequencing thousands of short genomic fragments from the microorganisms within a given sample. This technology presents a unique opportunity for artificial intelligence to comprehend the underlying functional relationships of microbial communities. However, due to the unstructured nature of HTS data, nearly all computational models are limited to processing DNA sequences individually. This limitation causes them to miss out on key interactions between microorganisms, significantly hindering our understanding of how these interactions influence the microbial communities as a whole. Furthermore, most computational methods rely on post-processing of samples which could inadvertently introduce unintentional protocol-specific bias. RESULTS: Addressing these concerns, we present SetBERT, a robust pre-training methodology for creating generalized deep learning models for processing HTS data to produce contextualized embeddings and be fine-tuned for downstream tasks with explainable predictions. By leveraging sequence interactions, we show that SetBERT significantly outperforms other models in taxonomic classification with genus-level classification accuracy of 95%. Furthermore, we demonstrate that SetBERT is able to accurately explain its predictions autonomously by confirming the biological-relevance of taxa identified by the model. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/DLii-Research/setbert. SetBERT may be used through the q2-deepdna QIIME 2 plugin whose source code is available at https://github.com/DLii-Research/q2-deepdna.

Ludwig, David W↗
DOE OSTI2024

Increasing aggregate size reduces single-cell organic carbon incorporation by hydrogel-embedded wetland microbes

Abstract Microbial degradation of organic carbon in sediments is impacted by the availability of oxygen and substrates for growth. To better understand how particle size and redox zonation impact microbial organic carbon incorporation, techniques that maintain spatial information are necessary to quantify elemental cycling at the microscale. In this study, we produced hydrogel microspheres of various diameters (100, 250, and 500 μm) and inoculated them with an aerobic heterotrophic bacterium isolated from a freshwater wetland (Flavobacterium sp.), and in a second experiment with a microbial community from an urban lacustrine wetland. The hydrogel-embedded microbial populations were incubated with 13C-labeled substrates to quantify organic carbon incorporation into biomass via nanoSIMS. Additionally, luminescent nanosensors enabled spatially explicit measurements of oxygen concentrations inside the microspheres. The experimental data were then incorporated into a reactive-transport model to project long-term steady-state conditions. Smaller (100 μm) particles exhibited the highest microbial cell-specific growth per volume, but also showed higher absolute activity near the surface compared to the larger particles (250 and 500 μm). The experimental results and computational models demonstrate that organic carbon availability was not high enough to allow steep oxygen gradients and as a result, all particle sizes remained well-oxygenated. Our study provides a foundational framework for future studies investigating spatially dependent microbial activity in aggregates using isotopically labeled substrates to quantify growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

An finite element analysis surrogate model with boundary oriented graph embedding approach for rapid design

Abstract In this work, we present a boundary oriented graph embedding (BOGE) approach for the graph neural network to assist in rapid design and digital prototyping. The cantilever beam problem has been solved as an example to validate its potential of providing physical field results and optimized designs using only 10 ms. Providing shortcuts for both boundary elements and local neighbor elements, the BOGE approach can embed unstructured mesh elements into the graph and performs an efficient regression on large-scale triangular-mesh-based finite element analysis (FEA) results, which cannot be realized by other machine-learning-based surrogate methods. It has the potential to serve as a surrogate model for other boundary value problems. Focusing on the cantilever beam problem, the BOGE approach with 3-layer DeepGCN model achieves the regression with mean square error (MSE) of 0.011 706 (2.41% mean absolute percentage error) for stress field prediction and 0.002 735 MSE (with 1.58% elements having error larger than 0.01) for topological optimization. The overall concept of the BOGE approach paves the way for a general and efficient deep-learning-based FEA simulator that will benefit both industry and Computer Aided Design (CAD) design-related areas.

42 ENGINEERING↗
DOE OSTI2022

Differences in chemical evolution between isolated and embedded prestellar cores

Models of prestellar cores often assume that the cores are isolated from their environment – material outside the core boundary plays no role in the subsequent evolution. This is unlikely to be the case in reality, where cores are located within hierarchically substructured molecular clouds. Here, we investigate the dynamical and chemical evolution of prestellar cores, modelled as Bonnor–Ebert spheres, and show that the density of the ambient medium has a large impact on the resulting chemical properties of the cores. Models embedded in high-density, low-temperature surroundings have greatly enhanced abundances of several molecules, such as CO and CS, compared to models with more diffuse surroundings, corresponding to relatively isolated cores. The predicted intensities and profile shapes of molecular lines are also affected. The density of the ambient medium has a stronger effect on the chemical evolution than whether the cores are initially in or out of equilibrium. This suggests that the impact of environment cannot be neglected when modelling chemistry in prestellar cores; the results of these models are highly sensitive to the assumptions made about the core surroundings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Structure of a 28.5 kDa duplex-embedded G-quadruplex system resolved to 7.4 Å resolution with cryo-EM

Genomic regions with high guanine content can fold into non-B form DNA four-stranded structures known as G-quadruplexes (G4s). Extensive in vivo investigations have revealed that promoter G4s are transcriptional regulators. Little structural information exists for these G4s embedded within duplexes, their presumed genomic environment. Here, we report the 7.4 Å resolution structure and dynamics of a 28.5 kDa duplex-G4-duplex (DGD) model system using cryo-EM, molecular dynamics, and small-angle X-ray scattering (SAXS) studies. The DGD cryo-EM refined model features a 53° bend induced by a stacked duplex-G4 interaction at the 5’ G-tetrad interface with a persistently unstacked 3’ duplex. The surrogate complement poly dT loop preferably stacks onto the 3’ G-tetrad interface resulting in occlusion of both 5’ and 3’ tetrad interfaces. Structural analysis shows that the DGD model is quantifiably more druggable than the monomeric G4 structure alone and represents a new structural drug target. Our results illustrate how the integration of cryo-EM, MD, and SAXS can reveal complementary detailed static and dynamic structural information on DNA G4 systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Composite quarks and leptons with embedded QCD

We construct a model of quark and lepton compositeness based on an 𝑆⁢𝑈⁡(15) gauge interaction that confines chiral preons, which are also charged under the weakly coupled 𝑆⁢𝑈⁢(4) PS ×𝑆⁢𝑈⁢(2) 𝐿 ×𝑆⁢𝑈⁢(2) 𝑅 gauge group. The breaking of the latter, down to the Standard Model group, is achieved by scalar 𝑆⁢𝑈⁡(15) bound states at a scale in the 30–100 TeV range. The embedding of the QCD gauge group in 𝑆⁢𝑈⁢(4) PS slows down the running of 𝛼 𝑠 in the UV. We estimate the effects of the strongly coupled 𝑆⁢𝑈⁡(15) dynamics on the running of the 𝑆⁢𝑈⁢(4) PS ×𝑆⁢𝑈⁢(2) 𝐿 ×𝑆⁢𝑈⁢(2) 𝑅 gauge couplings, which likely remain perturbative beyond the compositeness scale of about 10 3 –10 4 TeV, and even above a unification scale. A composite vectorlike lepton doublet acquires a mass in the TeV range probed at future colliders, and an extended Higgs sector arises from six-preon bound states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗