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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Statistical 3D 'Atomistic' Simulation of Decanano MOSFETs

A 3D statistical 'atomistic' simulation technique has been developed to study the effect of the random dopant induced parameter fluctuations in aggressively scaled MOSFETs. Efficient implementation of the 'atomistic' simulation approach has been used to investigate the threshold voltage standard deviation and lowering in the case of uniformly doped MOSFETs, and in fluctuation-resistant architectures utilising epitaxial-layers and delta-doping. The effect of the random doping in the polysilicon gate on the threshold voltage fluctuations has also been thoroughly investigated. The influence of a single-charge trapping on the channel conductivity in decanano MOSFETs is studied in the 'atomistic' framework as well. Quantum effects are taken into consideration in our 'atomistic' simulations using the density gradient formalism.

Asenov, Asen↗
DOE OSTI2025

Injection locking and coupling dynamics in superconducting nanowire-based cryogenic oscillators

Oscillators designed to function at cryogenic temperatures play a critical role in superconducting electronics and quantum computing by providing stable, low-noise signals with minimal energy loss. Here, in this work, we present a comprehensive numerical study of injection locking and mutual coupling dynamics in superconducting nanowire (ScNW)-based cryogenic oscillators. Using the design space of a standalone ScNW-based oscillator, we investigate two critical mechanisms that govern frequency synchronization and signal coordination in cryogenic computing architectures: (1) injection locking induced by an external AC signal with a frequency near the oscillator's natural frequency, and (2) the mutual coupling dynamics between two ScNW oscillators under varying coupling strengths. We identify key design parameters—such as shunt resistance, nanowire inductance, and coupling strength—that govern the locking range. Additionally, we examine how the amplitude of the injected signal affects the amplitude of the locked oscillation, offering valuable insights for power-aware oscillator synchronization. Furthermore, we analyze mutual synchronization between coupled ScNW oscillators using capacitive and resistive coupling elements. Our results reveal that the phase difference between oscillators can be controlled by tuning the coupling strength, enabling programmable phase-encoded information processing. These findings could enable building ScNW-based oscillatory neural networks, synchronized cryogenic logic blocks, and on-chip cryogenic resonator arrays.

Artificial neural networks↗
DOE OSTI2022

Operating High-Energy Lithium-Metal Pouch Cells with Reduced Stack Pressure Through a Rational Lithium-Host Design

Transitioning from a liquid electrolyte to an inorganic solid electrolyte offers a potential pathway to enable highly reversible lithium-metal anodes. However, the solid-electrolyte-protected lithium-metal anode suffers from poor interfacial ionic contacts and requires an impractically high stack pressure (>1.0 MPa) to maintain the interfacial contacts. It is demonstrated here that combining a hollow silver/carbon fiber scaffold and an inorganic/organic composite electrolyte enables a highly reversible lithium-metal anode. Since the high surface area of the electrode provides intimate contact and the hollow structure of the electrode relieves the lithium plating-induced stress, the electrode/electrolyte interface remains stable during cycling even under mild stack pressure. This unconventional structural design is validated in practical pouch cells assembled with the 3D lithium host containing a onefold excess of lithium and a high-nickel cathode. At a mild stack pressure of 320 kPa, the pouch cell displays 83% capacity retention for 200 cycles. This work illustrates that combining a hollow electrode architecture and a robust solid electrolyte offers a practical pathway toward rechargeable lithium-metal anodes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structural and quantum chemical basis for OCP-mediated quenching of phycobilisomes

Cyanobacteria use large antenna complexes called phycobilisomes (PBSs) for light harvesting. However, intense light triggers non-photochemical quenching, where the orange carotenoid protein (OCP) binds to PBS, dissipating excess energy as heat. The mechanism of efficiently transferring energy from phycocyanobilins in PBS to canthaxanthin in OCP remains insufficiently understood. Using cryo–electron microscopy, we unveiled the OCP-PBS complex structure at 1.6- to 2.1-angstrom resolution, showcasing its inherent flexibility. Using multiscale quantum chemistry, we disclosed the quenching mechanism. Identifying key protein residues, we clarified how canthaxanthin’s transition dipole moment in its lowest-energy dark state becomes large enough for efficient energy transfer from phycocyanobilins. Our energy transfer model offers a detailed understanding of the atomic determinants of light harvesting regulation and antenna architecture in cyanobacteria.

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

An extended moments model of quantum efficiency for metals and semiconductors

The complexity of photocathode designs and detector materials, and the need to model their performance for short pulse durations, response to high frequency photons, presence of coatings and/or thinness of the absorptive layer, necessitates modifications to three-step and moments models of photoemission that are used in simulation codes. Here, methods to include input from computationally intensive approaches, such as density functional theory to model optical properties and transfer matrix approaches to treat emission from the surface or transport past coatings, by means of parametric models are demonstrated. First, a technique to accurately represent optical behavior so as to model reflectivity and penetration depth is given. Second, modifications to bulk models arising from the usage of thin film architectures, and a means to rapidly calculate them, is provided. Third, a parameterization to model the impact of wells associated with coatings and surface layers on the transmission probably is given. In all cases, the methods are computationally efficient and designed to allow for including input from numerically intensive approaches that would otherwise be unavailable for simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Peptoid-directed assembly of CdSe nanoparticles

The high information content of proteins drives their hierarchical assembly and complex function, including the organization of inorganic nanomaterials. Peptoids offer an organic scaffold very similar to proteins, but with a wider solubility range and easily tunable side chains and functional groups to create a variety of self-assembling architectures with atomic precision. If we could harness this paradigm and understand the factors that govern how they direct nucleation and assembly of inorganic materials to design order within such materials, new dimensions of function and fundamental science would emerge. In this work, peptoid tubes and sheets were explored as platforms to assemble colloidal quantum dots (QDs) and clusters. We have successfully synthesized CdSe QDs with difunctionalized capping ligands containing both carboxylic acid and thiol groups and mixed them with maleimide containing peptoids, to create an assembly of the QDs on the peptoid surface via a covalent linkage. This conjugation was seen to be successful with peptoid tubes, sheets and CdSe QDs and clusters. The particles were seen to have a high preference for the peptoid surface but non-specific interactions with carboxylic acid groups on the peptoids limited control over QD density via maleimide conjugation. Replacing the carboxylic acid groups with methoxy ethers, however, allowed for control over QD density as a function of maleimide concentration. 1 H NMR analysis demonstrated that binding of QDs to peptoids involved a subset of surface ligands bound through the carboxylate functional group, allowing the distal thiol to engage in a covalent linkage to the maleimide. Overall, we have shown the compatibility and control of CdSe-peptoid interactions via a covalent linkage with varying peptoid structures and CdSe particles to create complex hybrid structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Excited-state electronic structure of molecules using many-body Green’s functions: Quasiparticles and electron–hole excitations with VOTCA-XTP

Here, we present the open-source VOTCA-XTP software for the calculation of the excited-state electronic structure of molecules using many-body Green’s function theory in the GW approximation with the Bethe–Salpeter equation (BSE). This work provides a summary of the underlying theory and discusses the details of its implementation based on Gaussian orbitals, including resolution-of-identity techniques and different approaches to the frequency integration of the self-energy or acceleration by offloading compute-intensive matrix operations using graphics processing units in a hybrid OpenMP/Cuda scheme. A distinctive feature of VOTCA–XTP is the capability to couple the calculation of electronic excitations to a classical polarizable environment on an atomistic level in a coupled quantum- and molecular-mechanics (QM/MM) scheme, where a complex morphology can be imported from Molecular Dynamics simulations. The capabilities and limitations of the GW–BSE implementation are illustrated with two examples. First, we study the dependence of optically active electron–hole excitations in a series of diketopyrrolopyrrole-based oligomers on molecular-architecture modifications and the number of repeat units. Second, we use the GW–BSE/MM setup to investigate the effect of polarization on localized and intermolecular charge-transfer excited states in morphologies of low-donor content rubrene–fullerene mixtures. These showcases demonstrate that our implementation currently allows us to treat systems with up to 2500 basis functions on regular shared-memory workstations, providing accurate descriptions of quasiparticle and coupled electron–hole excited states of various characters on an equal footing.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2010

Planar Submillimeter-Wave Mixer Technology with Integrated Antenna

High-performance mixers at terahertz frequencies require good matching between the coupling circuits such as antennas and local oscillators and the diode embedding impedance. With the availability of amplifiers at submillimeter wavelengths and the need to have multi-pixel imagers and cameras, planar mixer architecture is required to have an integrated system. An integrated mixer with planar antenna provides a compact and optimized design at terahertz frequencies. Moreover, it leads to a planar architecture that enables efficient interconnect with submillimeter-wave amplifiers. In this architecture, a planar slot antenna is designed on a thin gallium arsenide (GaAs) membrane in such a way that the beam on either side of the membrane is symmetric and has good beam profile with high coupling efficiency. A coplanar waveguide (CPW) coupled Schottky diode mixer is designed and integrated with the antenna. In this architecture, the local oscillator (LO) is coupled through one side of the antenna and the RF from the other side, without requiring any beam sp litters or diplexers. The intermediate frequency (IF) comes out on a 50-ohm CPW line at the edge of the mixer chip, which can be wire-bonded to external circuits. This unique terahertz mixer has an integrated single planar antenna for coupling both the radio frequency (RF) input and LO injection without any diplexer or beamsplitters. The design utilizes novel planar slot antenna architecture on a 3- mthick GaAs membrane. This work is required to enable future multi-pixel terahertz receivers for astrophysics missions, and lightweight and compact receivers for planetary missions to the outer planets in our solar system. Also, this technology can be used in tera hertz radar imaging applications as well as for testing of quantum cascade lasers (QCLs).

Chattopadhyay, Gautam↗
NASA NTRSDate not supplied

Impact of NASA’s Entry Systems Modeling Project on Planetary Mission Design

Planetary missions continue to grow larger and more complex. Furthermore, the current focus on human exploration of the Moon and Mars, as well as Mars Sample Return(MSR), place increas-ingly stringent requirements on the reliability of the entry, descent, and landing (EDL) system that ensures the safe delivery of payload or crew to their destination. Planetary EDL is an area in which mission designers are critically reliant on modeling and simulation to demonstrate the reliability of the system, as there are no ground facilities that are able to fully test these systems in a flight-relevant environment. NASA’s state-of-the-art modeling and simulation capability must continually evolve to meet the needs of the next generation of planetary EDL. To accomplish this aim, NASA’s Entry Systems Modeling (ESM) Project was formed in 2013and is funded bythe Space Technology Mission Directorate(STMD) and Science Mission Directorate (SMD). ESM is the Agency’s only cross-cutting effort for advancing entry systems modeling and simulation capabilities across a range of technical disciplines and Solar System destinations. ESM is a portfolio project covering a variety of mid-TRL research efforts within four core EDL-related areas of investment: (1) Thermal protection material modeling, (2) Shock layer kinetics and radiation, (3) Aerosciences, and (4) Guidance, navigation, and con-trol. The material modeling group creates detailed material response modelsof thermal protection systems (TPS)from the micro to macro scale, and at the fun-damental and engineering levels. Shock layer kinetics and radiation focuses on radiative heating of space-craft, quantum chemistry and benchmark experiments for validation.Aerosciences is a broad research area that impacts many aspects of entry systems, including parachutes, aerodynamics, and turbulent heating augmentation due to TPS roughness.The guidance, navigation,and control effort under ESM is expanding the capabilities of NASA’s main flight mechanics tool, POST2, for use on high-performance computing architectures and to generalize interoperability with external applications for more detailed end-to-end simula-tion.In addition, several focusedresearch topics have been approvedto augment ESM’s core portfolio. These include efforts for deep post-flight analysis of Mars 2020/MEDLI2 flight data; development ofTPS failure models; improvement of hypersonic wakeflow models; and a recently concluded effort to provide material response models for NuSil-coated PICA heat-shield material. This presentation will discuss each of these investment areas and demonstrate via real mission examples how advances to the state-of-the-art enabled by ESM are directly impacting the missions of today and tomorrow, including InSight, Mars 2020, Mars Sample Return, Orion, and Dragonfly.

Entry Systems Modeling↗
DOE OSTI2021

Learning the ground state of a non-stoquastic quantum Hamiltonian in a rugged neural network landscape

Strongly interacting quantum systems described by non-stoquastic Hamiltonians exhibit rich low-temperature physics. Yet, their study poses a formidable challenge, even for state-of-the-art numerical techniques. Here, we investigate systematically the performance of a class of universal variational wave-functions based on artificial neural networks, by considering the frustrated spin- 1/2 1 / 2 J_1-J_2 J 1 − J 2 Heisenberg model on the square lattice. Focusing on neural network architectures without physics-informed input, we argue in favor of using an ansatz consisting of two decoupled real-valued networks, one for the amplitude and the other for the phase of the variational wavefunction. By introducing concrete mitigation strategies against inherent numerical instabilities in the stochastic reconfiguration algorithm we obtain a variational energy comparable to that reported recently with neural networks that incorporate knowledge about the physical system. Through a detailed analysis of the individual components of the algorithm, we conclude that the rugged nature of the energy landscape constitutes the major obstacle in finding a satisfactory approximation to the ground state wavefunction, and prevents learning the correct sign structure. In particular, we show that in the present setup the neural network expressivity and Monte Carlo sampling are not primary limiting factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Superconducting Detector Arrays for Astrophysics

The next generation of astrophysics instruments will feature an order of magnitude more photon sensors or sensors that have an order of magnitude greater sensitivity. Since detector noise scales with temperature, a number of candidate technologies have been developed that use the intrinsic advantages of detector systems that operate below 1 Kelvin. Many of these systems employ of the superconducting phenomena that occur in metals at these temperatures to build ultrasensitive detectors and low-noise, low-power readout architectures. I will present one such system in use today to meet the needs of the astrophysics community at millimeter and x-ray wavelengths. Our group at NASA in collaboration with Princeton, NIST, Boulder and a number of other groups is building large format arrays of superconducting transition edge sensors (TES) read out with multiplexed superconducting quantum interference devices (SQUID). I will present the high sensitivity we have achieved in multiplexed x-ray sensors with the TES technology and describe the construction of a 1000-sensor TES/SQUID array for microwave measurements. With our collaboration's deployment of a kilopixel TES array for 2 mm radiation at the Atacarna Cosmology Telescope in November 2007, we have first images of the lensed Cosmic Microwave Background at fine angular scales.

Chervenak, James↗
DOE OSTI2020

Systematic Crosstalk Mitigation for Superconducting Qubits via Frequency-Aware Compilation

One of the key challenges in current Noisy Intermediate-Scale Quantum (NISQ) computers is to control a quantum system with high-fidelity quantum gates. There are many reasons a quantum gate can go wrong - for superconducting transmon qubits in particular, one major source of gate error is the unwanted crosstalk between neighboring qubits due to a phenomenon called frequency crowding. We motivate a systematic approach for understanding and mitigating the crosstalk noise when executing near-term quantum programs on superconducting NISQ computers. Here, we present a general software solution to alleviate frequency crowding by systematically tuning qubit frequencies according to input programs, trading parallelism for higher gate fidelity when necessary. The net result is that our work dramatically improves the crosstalk resilience of tunable-qubit, fixed-coupler hardware, matching or surpassing other more complex architectural designs such as tunable-coupler systems. On NISQ benchmarks, we improve worst-case program success rate by 13.3x on average, compared to existing traditional serialization strategies.

Computer architecture↗
DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Driving magnetic domains at the nanoscale by interfacial strain-induced proximity

Here, we investigate the local nanoscale changes of the magnetic anisotropy of a Ni film subject to an inverse magnetostrictive effect by proximity to a V 2 O 3 layer. Using temperature-dependent photoemission electron microscopy (PEEM) combined with X-ray magnetic circular dichroism (XMCD), direct images of the Ni spin alignment across the first-order structural phase transition (SPT) of V 2 O 3 were obtained. We find an abrupt temperature-driven reorientation of the Ni magnetic domains across the SPT, which is associated with a large increase of the coercive field. Moreover, angular dependent ferromagnetic resonance (FMR) shows a remarkable change in the magnetic anisotropy of the Ni film across the SPT of V 2 O 3 . Micromagnetic simulations based on these results are in quantitative agreement with the PEEM data. Direct measurements of the lateral correlation length of the Ni domains from XMCD images show an increase of almost one order of magnitude at the SPT compared to room temperature, as well as a broad spatial distribution of the local transition temperatures, thus corroborating the phase coexistence of Ni anisotropies caused by the V 2 O 3 SPT. We show that the rearrangement of the Ni domains is due to strain induced by the oxide layers’ structural domains across the SPT. Our results illustrate the use of alternative hybrid systems to manipulate magnetic domains at the nanoscale, which allows for engineering of coercive fields for novel data storage architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]

The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).

Warren, Emily↗
DOE OSTI2026

Regulation of Energy and Mass Transport in a Hydrogen-Bonded Framework for Visible-Light-Driven CO2 Reduction in Water

Photoenzymatic reduction of CO2 to formate is a promising strategy for carbon valorization, yet its efficiency is still limited by inefficient energy and mass transport. Here, we design a series of isostructural hydrogen-bonded organic frameworks (HOFs) that establish confinement effects to promote photocatalytic NADH regeneration and the subsequent NADH-dependent enzymatic CO2-to-formate reduction. We demonstrate that spatial confinement within the framework channels localizes exciton migration to nanoscale domains and promotes interfacial dissociation. Additionally, Rh-induced electronic-structure modulation enables ultrafast electron transfer, while the intrinsic hydrogen-bond network furnishes directional proton conduction to NAD+. These synergistic regulations afford a photocatalytic NADH regeneration efficiency of 99.8% with a record apparent quantum efficiency of 32.8%, and drive formate production at a rate of 3020 μmol g-1 h-1 with 100% selectivity─the highest rate reported to date for all light-driven systems in water. The HOF-based catalyst retains 86.3% of its initial activity over five cycles, highlighting its robustness. This work offers mechanistic insight into how microenvironment engineering within HOF architectures regulates energy and mass transport in photoenzymatic catalysis, paving the way for the rational design of advanced hybrid catalytic systems.

Xu, Jiaxing↗