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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Abstract Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Study of graphene p-n junctions formed by the electrostatic modification of the SiO2 substrate

Abstract We study the transport properties of mm-scale CVD graphene p-n junctions, which are formed in a single gated graphene field effect transistor configuration. Here, an electrical-stressing-voltage technique served to modify the electrostatic potential in the SiO 2 /Si substrate and create the p-n junction. We examine the transport characteristics about the Dirac points that are localized in the perturbed and unperturbed regions in the graphene channel and note the quantitative differences in the Hall effect between the perturbed and unperturbed regions. The results also show that the longitudinal resistance is highly sensitive to the external magnetic field when the Hall bar device operates as a p-n junction.

Science & Technology - Other Topics↗
DOE OSTI2024

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A single-photon lidar observes atmospheric clouds at decimeter scales: resolving droplet activation within cloud base

Abstract Clouds, crucial for understanding climate, begin with droplet formation from aerosols, but observations of this fleeting activation step are lacking in the atmosphere. Here we use a time-gated time-correlated single-photon counting lidar to observe cloud base structures at decimeter scales. Results show that the air–cloud interface is not a perfect boundary but rather a transition zone where the transformation of aerosol particles into cloud droplets occurs. The observed distributions of first-arriving photons within the transition zone reflect vertical development of a cloud, including droplet activation and condensational growth. Further, the highly resolved vertical profile of backscattered photons above the cloud base enables remote estimation of droplet concentration, an elusive but critical property to understanding aerosol–cloud interactions. Our results show the feasibility of remotely monitoring cloud properties at submeter scales, thus providing much-needed insights into the impacts of atmospheric pollution on clouds and aerosol-cloud interactions that influence climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Tuning transport across MoS2/graphene interfaces via as-grown lateral heterostructures

An unexploited property of graphene-based heterojunctions is the tunable doping of the junction via electrostatic gating. This unique property may be key in advancing electronic transport across interfaces with semiconductors. Here, we engineer transport in semiconducting TMDs by constructing a lateral heterostructure with epitaxial graphene and tuning its intrinsic doping to form a p–n junction between the graphene and the semiconducting TMDs. Graphene grown on SiC (epitaxial graphene) is intrinsically doped via substrate polarization without the introduction of an external dopant, thus enabling a platform for pristine heterostructures with a target band alignment. We demonstrate an electrostatically tunable graphene/MoS 2 p–n junction with >20× reduction and >10× increased tunability in contact resistance (R c ) compared with metal/TMD junctions, attributed to band alignment engineering and the tunable density of states in graphene. This unique concept provides improved control over transport across 2D p–n junctions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thiol-based defect healing of WSe 2 and WS 2

Recent research on two-dimensional (2D) transition metal dichalcogenides (TMDCs) has led to remarkable discoveries of fundamental phenomena and to device applications with technological potential. Large-scale TMDCs grown by chemical vapor deposition (CVD) are now available at continuously improving quality, but native defects and natural degradation in these materials still present significant challenges. Spectral hysteresis in gate-biased photoluminescence (PL) measurements of WSe 2 further revealed long-term trapping issues of charge carriers in intrinsic defect states. To address these issues, we apply here a two-step treatment with organic molecules, demonstrating the “healing” of native defects in CVD-grown WSe 2 and WS 2 by substituting atomic sulfur into chalcogen vacancies. We uncover that the adsorption of thiols provides only partial defect passivation, even for high adsorption quality, and that thiol adsorption is fundamentally limited in eliminating charge traps. However, as soon as the molecular backbone is trimmed and atomic sulfur is released to the crystal, both bonds of the sulfur are recruited to passivate the divalent defect and the semiconductor quality improves drastically. Time-dependent X-ray photoelectron spectroscopy (XPS) is applied here together with other methods for the characterization of defects, their healing, leading energies and occupation. First-principles calculations support a unified picture of the electronic passivation of sulfur-healed WSe 2 and WS 2 . This work provides a simple and efficient method for improving the quality of 2D semiconductors and has the potential to impact device performance even after natural degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Strain-insensitive intrinsically stretchable transistors and circuits

An all-elastomer strain engineering approach, which uses patterned elastomer layers with tunable stiffnesses, can be used to create intrinsically stretchable transistor arrays with a device density of 340 transistors cm -2 and strain insensitivity of less than 5% performance variation when stretched to 100% strain. Intrinsically stretchable electronics can form intimate interfaces with the human body, creating devices that could be used to monitor physiological signals without constraining movement. However, mechanical strain invariably leads to the degradation of the electronic properties of the devices. Here we show that strain-insensitive intrinsically stretchable transistor arrays can be created using an all-elastomer strain engineering approach, in which the patterned elastomer layers with tunable stiffnesses are incorporated into the transistor structure. By varying the cross-linking density of the elastomers, areas of increased local stiffness are introduced, reducing strain on the active regions of the devices. This approach can be readily incorporated into existing fabrication processes, and we use it to create arrays with a device density of 340 transistors cm -2 and a strain insensitivity of less than 5% performance variation when stretched to 100% strain. We also show that it can be used to fabricate strain-insensitive circuit elements, including NOR gates, ring oscillators and high-gain amplifiers for the stable monitoring of electrophysiological signals.

42 ENGINEERING↗
DOE OSTI2024

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds’ intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Relaxation of stationary states on a quantum computer yields a unique spectroscopic fingerprint of the computer’s noise

Abstract Quantum computing has the potential to revolutionize computing, but its significant sensitivity to noise requires sophisticated error correction and mitigation. Traditionally, noise on the quantum device is characterized directly through qubit and gate measurements, but this approach has drawbacks in that it does not adequately capture the effect of noise on realistic multi-qubit applications. In this paper, we simulate the relaxation of stationary quantum states on a quantum computer to obtain a unique spectroscopic fingerprint of the computer’s noise. In contrast to traditional approaches, we obtain the frequency profile of the noise as it is experienced by the simulated stationary quantum states. Data from multiple superconducting-qubit IBM processors show that noise generates a bath within the simulation that exhibits both colored noise and non-Markovian behavior. Our results provide a direction for noise mitigation but also suggest how to use noise for quantum simulations of open systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The unitary dependence theory for characterizing quantum circuits and states

Abstract Most existing quantum algorithms are discovered accidentally or adapted from classical algorithms, and there is the need for a systematic theory to understand and design quantum circuits. Here we develop a unitary dependence theory to characterize the behaviors of quantum circuits and states in terms of how quantum gates manipulate qubits and determine their measurement probabilities. Compared to the conventional entanglement description of quantum circuits and states, the unitary dependence picture offers more practical information on the measurement and manipulation of qubits, easier generalization to many-qubit systems, and better robustness upon partitioning of the system. The unitary dependence theory can be applied to systematically understand existing quantum circuits and design new quantum algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mapping of the mechanical response in Si/SiGe nanosheet device geometries

Abstract The performance of next-generation, nanoelectronic devices relies on a precise understanding of strain within the constituent materials. However, the increased flexibility inherent to these three-dimensional device geometries necessitates direct measurement of their deformation. Here we report synchrotron x-ray diffraction-based non-destructive nanoscale mapping of Si/SiGe nanosheets for gate-all-around structures. We identified two competing mechanisms at different length scales contributing to the deformation. One is consistent with the in-plane elastic relaxation due to the Ge lattice mismatch with the surrounding Si. The second is associated with the out-of-plane layering of the Si and SiGe regions at a length scale of film thickness. Complementary mechanical modeling corroborated the qualitative aspects of the deformation profiles observed across a variety of nanosheet sample widths. However, greater deformation is observed in the SiGe layers of the nanosheets than the predicted distributions. These insights could play a role in predicting carrier mobilities of future devices.

Murray, Conal E. (ORCID:0000000199014290)↗
DOE OSTI2023

Ultrathin quasi-2D amorphous carbon dielectric prepared from solution precursor for nanoelectronics

Abstract Materials keeping thickness in atomic scale but extending primarily in lateral dimensions offer properties attractive for many emerging applications. However, compared to crystalline counterparts, synthesis of atomically thin films in the highly disordered amorphous form, which avoids nonuniformity and defects associated with grain boundaries, is challenging due to their metastable nature. Here we present a scalable and solution-based strategy to prepare large-area, freestanding quasi-2D amorphous carbon nanomembranes with predominant sp 2 bonding and thickness down to 1–2 atomic layers, from coal-derived carbon dots as precursors. These atomically thin amorphous carbon films are mechanically strong with modulus of 400 ± 100 GPa and demonstrate robust dielectric properties with high dielectric strength above 20 MV cm −1 and low leakage current density below 10 −4 A cm −2 through a scaled thickness of three-atomic layers. They can be implemented as solution-deposited ultrathin gate dielectrics in transistors or ion-transport media in memristors, enabling exceptional device performance and spatiotemporal uniformity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Selective electrified polyethylene upcycling by pore-modulated pyrolysis

Plastic waste is a increasing problem, accumulating in landfills and the environment. Pyrolysis is a promising and industrially relevant approach for transforming plastic waste into value-added chemicals. However, the selectivity and yield of traditional plastic pyrolysis are poor, with products featuring broad molar mass distributions. Here we report a highly selective, energy-efficient and catalyst-free pyrolysis method that can upcycle plastic into value-added chemicals via pore-modulated pyrolysis. Using a Joule-heated carbon column, we demonstrate the pivotal role of the reactor’s graded porous structure in decreasing the polydispersity of the reaction intermediates, enabling high product selectivity and yield. The decreasing pore size of the reactor modulates the mass transport in an apparent gating effect—preventing high-molar-mass species from exiting the reactor before sufficient pyrolysis has occurred. Using polyethylene as a model reactant, we demonstrate a high yield of 65.9 ± 5.2% and up to 80.8% selectivity toward value-added aviation fuel precursor (C8–C18 hydrocarbons) without the use of any catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

High broadband photoconductivity of few-layered MoS 2 field-effect transistors measured using multi-terminal methods: effects of contact resistance

Among the layered two dimensional semiconductors, molybdenum disulfide (MoS 2 ) is considered to be an excellent candidate for applications in optoelectronics and integrated circuits due to its layer-dependent tunable bandgap in the visible region, high ON/OFF current ratio in field-effect transistors (FET) and strong light–matter interaction properties. In this study, using multi-terminal measurements, we report high broadband photocurrent response ( R ) and external quantum efficiency (EQE) of few-atomic layered MoS 2 phototransistors fabricated on a SiO 2 dielectric substrate and encapsulated with a thin transparent polymer film of Cytop. The photocurrent response was measured using a white light source as well as a monochromatic light of wavelength λ = 400 nm–900 nm. We measured responsivity using a 2-terminal configuration as high as R = 1 × 10 3 A W -1 under white light illumination with an optical power P opt = 0.02 nW. The R value increased to 3.5 × 10 3 A W -1 when measured using a 4-terminal configuration. Using monochromatic light on the same device, the measured values of R were 10 3 and 6 × 10 3 A W -1 under illumination of λ = 400 nm when measured using 2- and 4-terminal methods, respectively. The highest EQE values obtained using λ = 400 nm were 10 5 % and 10 6 % measured using 2- and 4-terminal configurations, respectively. The wavelength dependent responsivity decreased from 400 nm to the near-IR region at 900 nm. The observed photoresponse, photocurrent–dark current ratio (PDCR), detectivity as a function of applied gate voltage, optical power, contact resistances and wavelength were measured and are discussed in detail. The observed responsivity is also thoroughly studied as a function of contact resistance of the device.

36 MATERIALS SCIENCE↗
DOE OSTI2020

All-atom molecular dynamics simulations of weak polyionic brushes: influence of charge density on the properties of polyelectrolyte chains, brush-supported counterions, and water molecules

All atom molecular dynamics (MD) simulations of planar Na+-counterion-neutralized polyacrylic acid (PAA) brushes are performed for varying degrees of ionization (and thereby varying charge density) and varying grafting density. Variation in the PE charge density (or degree of ionization) and grafting density leads to massive changes of the properties of the PE molecules (quantified by the changes in the height and the mobility of the PE brushes) as well as the local arrangement and distribution of the brush-supported counterions and water molecules within the brushes. The effect on the counterions is manifested by the corresponding variation of the counterion mobility, counterion concentration, extent of counterion binding to the charged site of the PE brushes, water-in-salt-like structure formation, and counterion-water–oxygen radial distribution function within the PE brushes. On the other hand, the effect on water molecules is manifested by the corresponding variation of water–oxygen–water–oxygen RDF, local water density, water–water and water–PE functional group hydrogen bond networks, static dielectric constant of water molecules, orientational tetrahedral order parameter, and water mobility. Enforcing such varying degree of ionization of weak polyelectrolytes is possible by changing the pH of the surrounding medium. Thus, our results provide insights into the changes in microstructure (at the atomistic level) of weak polyionic brushes at varying pH. Finally, we anticipate that this knowledge will prove to be vital for the efficient design of several nano-scale systems employing PE brushes such as nanomechanical gates, current rectifiers, etc.

42 ENGINEERING↗
DOE OSTI2021

Accessing the triplet manifold of naphthalene benzimidazole–phenanthroline in rhenium(i) bichromophores

In this work, the steady-state and ultrafast to supra-nanosecond excited state dynamics of fac-[Re(NBI-phen)(CO) 3 (L)](PF 6 ) (NBI-phen = 16H-benzo[4',5']isoquinolino[2',1':1,2]imidazo[4,5-f][1,10]phenanthrolin-16-one) as well as their respective models of the general molecular formula [Re(phen)(CO) 3 (L)](PF 6 ) (L = PPh 3 and CH 3 CN) has been investigated using transient absorption and time-gated photoluminescence spectroscopy. The NBI-phen containing molecules exhibited enhanced visible light absorption with respect to their models and a rapid formation (<6 ns) of the triplet ligand-centred (LC) excited state of the organic ligand, NBI-phen. These triplet states exhibit an extended excited state lifetime that enable the energized molecules to readily engage in triplet–triplet annihilation photochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗