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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated their unique values in content generation. This paper aims to explore the innovative integration of GenAI techniques and urban digital twins to address challenges in the planning and management of built environments with focuses on various urban sub-systems, such as transportation, energy, water, and building and infrastructure. The survey starts with the introduction of cutting-edge generative AI models, such as the Generative Adversarial Networks (GAN), Variational Autoencoders (VAEs), Generative Pre-trained Transformer (GPT), followed by a scoping review of the existing urban science applications that leverage the intelligent and autonomous capability of these techniques to facilitate the research, operations, and management of critical urban subsystems, as well as the holistic planning and design of the built environment. Based on the review, we discuss potential opportunities and technical strategies that integrate GenAI models into the next-generation urban digital twins for more intelligent, scalable, and automated smart city development and management.

3D city modeling↗
DOE OSTI2024

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Reimagining metal-organic framework discovery: Integrating experiment, computation, and artificial intelligence

The traditional development of novel metal–organic frameworks (MOFs) is often hindered by challenges such as synthetic accessibility and time- and resource-intensive experimentation. High-throughput, automated experimental and computational techniques have enabled rapid chemical space exploration and theoretical MOF design. When combined with artificial intelligence (AI), these methods can be used to lead autonomous laboratories to new frontiers for MOF discovery, where these materials can be designed for a specific application, efficiently synthesized, characterized, and evaluated. Here, this perspective highlights the role of AI in advancing automated MOF synthesis and characterization, computational MOF design and screening, and the integration of these approaches within autonomous workflows to ultimately enable the MOF laboratories of the future.

Gaidimas, Madeleine A. [Northwestern University, E↗
DOE OSTI2019

Na 4 MnV(PO 4 ) 3 -rGO as Advanced cathode for aqueous and non-aqueous sodium ion batteries

NASICON-type Na 4 MnV(PO 4 ) 3 with reduced graphene oxide (rGO) has been synthesized by the simple sol-gel reaction and characterized by different analytical techniques. The resulted material has been explored as a cathode material for rechargeable non-aqueous and aqueous sodium-ion batteries. In non-aqueous electrolytes, the as-synthesized Na 4 MnV(PO 4 ) 3 -rGO composite shows stable discharge capacity of 86 mAh g -1 at 0.1 C and 68 mAh g -1 at 0.2 C after 100 cycles in half-cell and full-cell configurations, respectively. In aqueous electrolytes, it delivers an initial discharge capacity of 92 mAh g -1 at 1 C rate in half-cells and 97 mAh g -1 at 10 C rate in full-cells having NaTi 2 (PO 4 ) 3 -MWCNT as the anode. Stable cycleability and high rate capabilities of Na 4 MnV(PO 4 ) 3 -rGO composite can be attributed to the very strong and sustainable conductive percolation networks for both electrons and Na + ions. The obtained results reveal that the aqueous electrolyte cell has a huge scope for gird level energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2022

Inactivation of multiple human pathogens by Fathhome's dry sanitizer device: Rapid and eco-friendly ozone-based disinfection

SARS-CoV-2 spread rapidly, causing millions of deaths across the globe. As a result, demand for medical supplies and personal protective equipment (PPE) surged and supplies dwindled. Separate entirely, hospital-acquired infections have become commonplace and challenging to treat. To explore the potential of novel sterilization techniques, this study evaluated the disinfection efficacy of Fathhome's ozone-based, dry-sanitizing device by dose and time response. Inactivation of human pathogens was tested on non-porous (plastic) surfaces. 95.42-100% inactivation was observed across all types of vegetative microorganisms and 27.36% inactivation of bacterial endospores tested, with no residual ozone detectable after completion. These results strongly support the hypothesis that Fathhome's commercial implementation of gas-based disinfection is suitable for rapid decontamination of a wide variety of pathogens on PPE and other industrially relevant materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Optimum lithium loading of a liquid scintillator for neutron and neutrino detection

Neutral particle detection in high-background environments is greatly aided by the ability to easily load 6 Li into liquid scintillators. In this work, we describe a readily available and inexpensive liquid scintillation cocktail stably loaded with a Li mass fraction up to 1%. Compositions that give thermodynamically stable microemulsions (reverse-micellar systems) were explored, using a Compton spectrum quenching technique to distinguish these from unstable emulsions. Scintillation light yield and transmittance were characterized. Pulse shape discrimination (PSD) was measured using a 252 Cf source, showing that electron-like and proton-like recoil events are well-resolved even for Li loading up to 1%, providing a means of background suppression in neutron/neutrino detectors. While samples in this work were prepared with nat Li (7.59% 6 Li), the neutron capture peak was clearly visible in the PSD spectrum; this implies that while extremely high capture efficiency could be achieved with 6 Li-enriched material, a very inexpensive neutron-sensitive detector can be prepared with nat Li.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Pressure–Temperature–Magnetic Field Phase Diagram of Multiferroic (NH 4 ) 2 FeCl 5 ·H 2 O

We combined synchrotron-based infrared absorbance and Raman scattering spectroscopies with diamond anvil cell techniques and a symmetry analysis to explore the properties of multiferroic (NH 4 ) 2 FeCl 5 ·H 2 O under extreme pressure–temperature conditions. Compression-induced splitting of the Fe–Cl stretching, Cl–Fe–Cl and Cl–Fe–O bending, and NH 4 + librational modes defines two structural phase transitions, and a group–subgroup analysis reveals space group sequences that vary depending upon proximity to the unexpectedly wide order–disorder transition. Here, we bring these findings together with prior high-field work to develop the pressure–temperature–magnetic field phase diagram uncovering competing polar, chiral, and magnetic phases in this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Impacts of Oxo Interactions on Np(V) Crown Ether Complexes

Intermolecular interactions between the oxo group of an actinyl cation and other metal cations (i.e., cation–cation interactions) are dependent on the strength of the actinyl bond. These cation–cation interactions are prominently observed for the neptunyl cation [Np(V)O 2] + and are sufficiently stable enough to explore using a variety of chemical techniques. Here, we investigate these intermolecular interactions in the neptunyl 18-crown-6 system, because this macrocyclic ligand provides both stable coordination and the proper sterics to engage the oxo group in bonding with both low-valent metal cations and neighboring neptunyl units. We report the structural and spectroscopic characterization of five neptunyl, [Np(V,VI)O 2 ] +,2+ , compounds: Np1a ([NpO 2 (18-crown-6)]ClO 4 ), Np1b ([NpO 2 (18-crown-6)]AuCl 4 ), Na–Np ([Np(V)O 2 (18-crown-6)(Na(H 2 O)(18-crown-6)][Np(VI)O 2 Cl 4 ], Np–Np ([NpO 2 (18-crown-6)](NpO 2 Cl 2 NO 3 )], and Np–Cl (NpO 2 Cl(H 2 O) 1.75 ). Each of these compounds were prepared from the ambient reactions of Np(V) in HX (where X = Cl, NO 3 ) with the 18-crown-6 ether molecule. Structural information obtained from single-crystal X-ray diffraction data was paired with solid-state and solution Raman spectroscopy to provide information on the interaction of the neptunyl oxo atom with neighboring cations. Neptunyl (Np=O) bond lengths are not perturbed upon interaction with the Na + cation (Na–Np), but elongation is observed upon formation of a neptunyl–neptunyl interaction (Np–Np). This is also the first structurally characterized isolated, molecular complex that contains a simple T-shaped neptunyl–neptunyl interaction. Raman spectroscopy indicates little perturbation to the neptunyl bond until the formation of the neptunyl–neptunyl motif, which also results in activation of the ν 3 asymmetric stretch. Additional spectroscopic studies indicated that the neptunyl 18-crown-6 inclusion complexes form in solution and persist in the presence of other low-valence cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Formation of Larger Solvation Shells in a LiFSI Salt Solution for Enhanced Li + Transport

Electrodes and electrolytes in Li-ion batteries (LIBs) are crucial for their electrochemical performance, and fabricating these materials to achieve the desired properties for improved efficiency is challenging. A recent study published in Nature ( Nature 2024, 627, 101−107) outlined guidelines for designing an electrolyte using fluoroacetonitrile (FACN), a small-molecule solvent with low solvation energy. This characteristic enables the formation of an anion-rich inorganic interphase in a 1.3 M lithium bis(fluorosulfonyl)imide (LiFSI) solution, facilitating higher ionic conductivity, even at low temperatures. The formation of a ligand channel was postulated and demonstrated in the simulation due to the attraction of small solvent molecules from the secondary solvation shell to the Li + ion in the primary solvation shell, thereby enhancing Li + transport. While that study primarily focused on Li + ion behavior in LIBs, the behavior of FACN in solutions with different lithium salts and what makes LiFSI in FACN outperform other systems remain to be explored. In conclusion, using an experimental technique sensitive to FACN molecules, here we directly observe formation of larger solvation shells in a LiFSI solution compared to the Li salts with different anions, consistent with the postulated ligand-channel-mechanism and potentially paving the way to achieving enhanced ionic conductivity and energy density during LIB operation.

Batteries↗
DOE OSTI2014

Shedding Light on the Photochemistry of Coinage-Metal Phosphorescent Materials: A Time-Resolved Laue Diffraction Study of an Ag I -Cu I Tetranuclear Complex

The triplet excited state of a new crystalline form of a tetranuclear coordination d 10 –d 10 -type complex, Ag 2 Cu 2 L 4 (L = 2-diphenylphosphino-3-methylindole ligand), containing Ag I and Cu I metal centers has been explored using the Laue pump–probe technique with ≈80 ps time resolution. The relatively short lifetime of 1 μs is accompanied by significant photoinduced structural changes, as large as the Ag1···Cu2 distance shortening by 0.59(3) Å. The results show a pronounced strengthening of the argentophilic interactions and formation of new Ag···Cu bonds on excitation. Theoretical calculations indicate that the structural changes are due to a ligand-to-metal charge transfer (LMCT) strengthening the Ag···Ag interaction, mainly occurring from the methylindole ligands to the silver metal centers. QM/MM optimizations of the ground and excited states of the complex support the experimental results. Comparison with isolated molecule optimizations demonstrates the restricting effect of the crystalline matrix on photoinduced distortions. The work represents the first time-resolved Laue diffraction study of a heteronuclear coordination complex and provides new information on the nature of photoresponse of coinage metal complexes, which have been the subject of extensive studies.

Jarzembska, Katarzyna N.↗
DOE OSTI2015

Probing local bias-induced transitions using photothermal excitation contact resonance atomic force microscopy and voltage spectroscopy

In this paper, nanomechanical properties are closely related to the states of matter, including chemical composition, crystal structure, mesoscopic domain configuration, etc. Investigation of these properties at the nanoscale requires not only static imaging methods, e.g., contact resonance atomic force microscopy (CR-AFM), but also spectroscopic methods capable of revealing their dependence on various external stimuli. Here we demonstrate the voltage spectroscopy of CR-AFM, which was realized by combining photothermal excitation (as opposed to the conventional piezoacoustic excitation method) with the band excitation technique. We applied this spectroscopy to explore local bias-induced phenomena ranging from purely physical to surface electromechanical and electrochemical processes. Our measurements show that the changes in the surface properties associated with these bias-induced transitions can be accurately assessed in a fast and dynamic manner, using resonance frequency as a signature. Finally, with many of the advantages offered by photothermal excitation, contact resonance voltage spectroscopy not only is expected to find applications in a broader field of nanoscience but also will provide a basis for future development of other nanoscale elastic spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Big Data Seismology

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Currently, Big Data Seismology is an emergent revolution involving the use of large, data-dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data-dense sensor systems, improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long-duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up-to-speed with how the Big Data revolution is advancing the field of seismology.

58 GEOSCIENCES↗
DOE OSTI2018

High-performance and scalable on-chip digital Fourier transform spectroscopy

Abstract On-chip spectrometers have the potential to offer dramatic size, weight, and power advantages over conventional benchtop instruments for many applications such as spectroscopic sensing, optical network performance monitoring, hyperspectral imaging, and radio-frequency spectrum analysis. Existing on-chip spectrometer designs, however, are limited in spectral channel count and signal-to-noise ratio. Here we demonstrate a transformative on-chip digital Fourier transform spectrometer that acquires high-resolution spectra via time-domain modulation of a reconfigurable Mach-Zehnder interferometer. The device, fabricated and packaged using industry-standard silicon photonics technology, claims the multiplex advantage to dramatically boost the signal-to-noise ratio and unprecedented scalability capable of addressing exponentially increasing numbers of spectral channels. We further explore and implement machine learning regularization techniques to spectrum reconstruction. Using an ‘elastic-D 1 ’ regularized regression method that we develop, we achieved significant noise suppression for both broad (>600 GHz) and narrow (<25 GHz) spectral features, as well as spectral resolution enhancement beyond the classical Rayleigh criterion.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Imaging shapes of atomic nuclei in high-energy nuclear collisions

Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes, traditionally explored using non-invasive spectroscopic techniques at low energies. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Detecting defects that reduce breakdown voltage using machine learning and optical profilometry

Abstract Semiconductor wafer manufacturing relies on the precise control of various performance metrics to ensure the quality and reliability of integrated circuits. In particular, GaN has properties that are advantageous for high voltage and high frequency power devices; however, defects in the substrate growth and manufacturing are preventing vertical devices from performing optimally. This paper explores the application of machine learning techniques utilizing data obtained from optical profilometry as input variables to predict the probability of a wafer meeting performance metrics, specifically the breakdown voltage (V bk ). By incorporating machine learning techniques, it is possible to reliably predict performance metrics that cause devices to fail at low voltage. For diodes that fail at a higher (but still below theoretical) breakdown voltage, alternative inspection methods or a combination of several experimental techniques may be necessary.

42 ENGINEERING↗
DOE OSTI2014

A new time-frequency method to reveal quantum dynamics of atomic hydrogen in intense laser pulses: Synchrosqueezing transform

This study introduces a new adaptive time-frequency (TF) analysis technique, the synchrosqueezing transform (SST), to explore the dynamics of a laser-driven hydrogen atom at an ab initio level, upon which we have demonstrated its versatility as a new viable venue for further exploring quantum dynamics. For a signal composed of oscillatory components which can be characterized by instantaneous frequency, the SST enables rendering the decomposed signal based on the phase information inherited in the linear TF representation with mathematical support. Compared with the classical type of TF methods, the SST clearly depicts several intrinsic quantum dynamical processes such as selection rules, AC Stark effects, and high harmonic generation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Photovoltaic conversion of visible spectrum by GaP capped InP quantum dots grown on Si (100) by metalorganic chemical vapor deposition

Growth of GaP capped strained InP quantum dots was carried out by metal organic chemical vapor deposition technique on Si (100) substrates to explore an alternative material system for photovoltaic conversion. Studies on reflectance spectroscopy show higher absorption of visible photons compared to scattering. Smooth and defect free interface provides low dark current with high rectification ratio. A solar cell made of five periods of quantum dots is found to provide a conversion efficiency of 4.18% with an open circuit voltage and short circuit current density of 0.52 V and 13.64 mA/cm{sup 2}, respectively, under AM 1.5 solar radiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗