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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantum capacities of transducers

Abstract High-performance quantum transducers, which faithfully convert quantum information between disparate physical carriers, are essential in quantum science and technology. Different figures of merit, including efficiency, bandwidth, and added noise, are typically used to characterize the transducers’ ability to transfer quantum information. Here we utilize quantum capacity, the highest achievable qubit communication rate through a channel, to define a single metric that unifies various criteria of a desirable transducer. Using the continuous-time quantum capacities of bosonic pure-loss channels as benchmarks, we investigate the optimal designs of generic quantum transduction schemes implemented by transmitting external signals through a coupled bosonic chain. With physical constraints on the maximal coupling rate $${g}_{\max }$$ g max , the highest continuous-time quantum capacity $${Q}^{\max }\approx 31.4{g}_{\max }$$ Q max ≈ 31.4 g max is achieved by transducers with a maximally flat conversion frequency response, analogous to Butterworth electric filters. We further investigate the effect of thermal noise on the performance of transducers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Electrochemical direct air capture of CO 2 using neutral red as reversible redox-active material

Direct air capture of carbon dioxide is a viable option for the mitigation of CO 2 emissions and their impact on global climate change. Conventional processes for carbon capture from ambient air require 230 to 800 kJ thermal per mole of CO 2 , which accounts for most of the total cost of capture. Here, we demonstrate electrochemical direct air capture using neutral red as a redox-active material in an aqueous solution enabled by the inclusion of nicotinamide as a hydrotropic solubilizing agent. The electrochemical system demonstrates a high electron utilization of 0.71 in a continuous flow cell with an estimated minimum work of 35 kJ e per mole of CO 2 from 15% CO 2 . Further exploration using ambient air (410 ppm CO 2 in the presence of 20% oxygen) as a feed gas shows electron utilization of 0.38 in a continuous flow cell to provide an estimated minimum work of 65 kJ e per mole of CO 2 .

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

Quantifying disorder one atom at a time using an interpretable graph neural network paradigm

Abstract Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric for local disorder, called SODAS. This metric encodes the diversity of the local atomic configurations as a continuous spectrum between the solid and liquid phases, quantified against a distribution of thermal perturbations. We apply this methodology to four prototypical examples with varying levels of disorder: (1) grain boundaries, (2) solid-liquid interfaces, (3) polycrystalline microstructures, and (4) tensile failure/fracture. We also compare SODAS to several commonly used methods. Using elemental aluminum as a case study, we show how our paradigm can track the spatio-temporal evolution of interfaces, incorporating a mathematically defined description of the spatial boundary between order and disorder. We further show how to extract physics-preserved gradients from our continuous disorder fields, which may be used to understand and predict materials performance and failure. Overall, our framework provides a simple and generalizable pathway to quantify the relationship between complex local atomic structure and coarse-grained materials phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nondestructive flash cathode recycling

Effective recycling of end-of-life Li-ion batteries (LIBs) is essential due to continuous accumulation of battery waste and gradual depletion of battery metal resources. The present closed-loop solutions include destructive conversion to metal compounds, by destroying the entire three-dimensional morphology of the cathode through continuous thermal treatment or harsh wet extraction methods, and direct regeneration by lithium replenishment. Here, we report a solvent- and water-free flash Joule heating (FJH) method combined with magnetic separation to restore fresh cathodes from waste cathodes, followed by solid-state relithiation. The entire process is called flash recycling. This FJH method exhibits the merits of milliseconds of duration and high battery metal recovery yields of ~98%. After FJH, the cathodes reveal intact core structures with hierarchical features, implying the feasibility of their reconstituting into new cathodes. Relithiated cathodes are further used in LIBs, and show good electrochemical performance, comparable to new commercial counterparts. Life-cycle-analysis highlights that flash recycling has higher environmental and economic benefits over traditional destructive recycling processes.

25 ENERGY STORAGE↗
DOE OSTI2024

Confinement of excited states in two-dimensional, in-plane, quantum heterostructures

Two-dimensional (2D) semiconductors are promising candidates for optoelectronic application and quantum information processes due to their inherent out-of-plane 2D confinement. In addition, they offer the possibility of achieving low-dimensional in-plane exciton confinement, similar to zero-dimensional quantum dots, with intriguing optical and electronic properties via strain or composition engineering. However, realizing such laterally confined 2D monolayers and systematically controlling size-dependent optical properties remain significant challenges. Here, we report the observation of lateral confinement of excitons in epitaxially grown in-plane MoSe 2 quantum dots (~15-60 nm wide) inside a continuous matrix of WSe 2 monolayer film via a sequential epitaxial growth process. Various optical spectroscopy techniques reveal the size-dependent exciton confinement in the MoSe 2 monolayer quantum dots with exciton blue shift (12-40 meV) at a low temperature as compared to continuous monolayer MoSe 2 . Finally, single-photon emission (g 2 (0) ~ 0.4) was also observed from the smallest dots at 1.6 K. Our study opens the door to compositionally engineered, tunable, in-plane quantum light sources in 2D semiconductors.

42 ENGINEERING↗
DOE OSTI2024

Autonomous stabilization with programmable stabilized state

Reservoir engineering is a powerful technique to autonomously stabilize a quantum state. Traditional schemes involving multi-body states typically function for discrete entangled states. In this work, we enhance the stabilization capability to a continuous manifold of states with programmable stabilized state selection using multiple continuous tuning parameters. We experimentally achieve 84.6% and 82.5% stabilization fidelity for the odd and even-parity Bell states as two special points in the manifold. We also perform fast dissipative switching between these opposite parity states within 1.8 μs and 0.9 μs by sequentially applying different stabilization drives. Our result is a precursor for new reservoir engineering-based error correction schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Automatic speech recognition predicts contemporaneous earthquake fault displacement

Abstract Significant progress has been made in probing the state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec-2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kīlauea volcano on the island of Hawai’i. We pre-train the Wav2Vec-2.0 model using caldera seismic waveforms and augment the model architecture to predict contemporaneous surface displacement during the caldera collapse sequence, a proxy for fault displacement. We find the model displacement predictions to be excellent. The model is adapted for near-future prediction information and found hints of prediction capability, but the results are not robust. The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligence models developed for encoding audio of speech may have important applications in studying active fault zones.

58 GEOSCIENCES↗
DOE OSTI2026

FunDiff: diffusion models over function spaces for physics-informed generative modeling

Recent advances in generative modeling-particularly diffusion models and flow matching-have been widely used for synthesizing discrete data such as images and videos. However, adapting these models to physical applications remains challenging, as the quantities of interest are continuous functions governed by complex physical laws. To address this, we introduce FunDiff, an efficient and robust framework for generative modeling in function spaces. FunDiff combines a latent diffusion process with a function autoencoder architecture to handle input functions with varying discretizations, generates continuous functions that can be evaluated at arbitrary locations, and seamlessly incorporate physical priors. These priors are enforced through architectural constraints or physics-informed loss functions, ensuring that generated samples satisfy fundamental physical laws. We theoretically establish minimax optimality guarantees for density estimation in function spaces, demonstrating that diffusion-based estimators achieve optimal convergence rates under suitable regularity conditions. We further demonstrate the practical effectiveness of FunDiff across diverse applications in fluid dynamics and solid mechanics. Empirical results indicate that our method can generate physically consistent samples with high fidelity to the target distribution, and exhibit robustness to noisy and low-resolution data.

Wang, Sifan [Yale University, New Haven, CT (Unite↗
DOE OSTI2026

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗
DOE OSTI2020

Machine learning model to project the impact of COVID-19 on U.S. motor gasoline demand

Owing to the global lockdowns that resulted from the COVID-19 pandemic, fuel demand plummeted and the price of oil futures went negative in April 2020. Robust fuel demand projections are crucial to economic and energy planning and policy discussions. Here we incorporate pandemic projections and people's resulting travel and trip activities and fuel usage in a machine-learning-based model to project the US medium-term gasoline demand and study the impact of government intervention. We found that under the reference infection scenario, the US gasoline demand grows slowly after a quick rebound in May, and is unlikely to fully recover prior to October 2020. Under the reference and pessimistic scenario, continual lockdown (no reopening) could worsen the motor gasoline demand temporarily, but it helps the demand recover to a normal level quicker. Under the optimistic infection scenario, gasoline demand will recover close to the non-pandemic level by October 2020. The COVID 19 pandemic and consequent lockdown has had a substantial impact on mobility and therefore fuel demand and it is not clear when demand will recover. Ou et al. use a machine learning model that integrates health recovery scenarios to project the near-term future of gasoline demand.

COVID-19 pandemic↗
DOE OSTI2020

Unprecedented non-hysteretic superelasticity of [001]-oriented NiCoFeGa single crystals

Superelasticity associated with the martensitic transformation has found a broad range of engineering applications. However, the intrinsic hysteresis and temperature sensitivity of the first-order phase transformation significantly hinder the usage of smart metallic components in many critical areas. In this paper, we report a large superelasticity up to 15.2% strain in [001]-oriented NiCoFeGa single crystals, exhibiting non-hysteretic mechanical responses, a small temperature dependence and high-energy-storage capability and cyclic stability over a wide temperature and composition range. In situ synchrotron X-ray diffraction measurements show that the superelasticity is correlated with a stress-induced continuous variation of lattice parameter accompanied by structural fluctuation. Neutron diffraction and electron microscopy observations reveal an unprecedented microstructure consisting of atomic-level entanglement of ordered and disordered crystal structures, which can be manipulated to tune the superelasticity. The discovery of the large elasticity related to the entangled structure paves the way for exploiting elastic strain engineering and development of related functional materials. NiCoFeGa single crystals exhibit large non-hysteretic superelasticity over broad temperature and composition ranges. It is attributed to the continuous phase transition with applied stress, which is related to the fluctuation of entangled ordered and disordered crystal structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Resolving complex intralayer transition motifs in high-Ni-content layered cathode materials for lithium-ion batteries

High-Ni-content layered materials are promising cathodes for next-generation lithium-ion batteries. However, investigating the atomic configurations of the delithiation-induced complex phase boundaries and their transitions remains challenging. Here, in this study, by using deep-learning-aided super-resolution electron microscopy, we resolve the intralayer transition motifs at complex phase boundaries in high-Ni cathodes. We reveal that an O3 → O1 transformation driven by delithiation leads to the formation of two types of O1–O3 interface, the continuous- and abrupt-transition interfaces. The interfacial misfit is accommodated by a continuous shear-transition zone and an abrupt structural unit, respectively. Atomic-scale simulations show that uneven in-plane Li+ distribution contributes to the formation of both types of interface, and the abrupt transition is energetically more favourable in a delithiated state where O1 is dominant, or when there is an uneven in-plane Li + distribution in a delithiated O3 lattice. Moreover, a twin-like motif that introduces structural units analogous to the abrupt-type O1–O3 interface is also uncovered. The structural transition motifs resolved in this study provide further understanding of shear-induced phase transformations and phase boundaries in high-Ni layered cathodes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Space-time crystals from particle-like topological solitons

Time crystals are unexpected states of matter that spontaneously break time-translation symmetry either in a discrete or continuous manner. However, spatially mesoscale space-time crystals that break both space and time symmetries have not been reported. Here we report a continuous space-time crystal in a nematic liquid crystal driven by ambient-power, constant-intensity unstructured light. Our numerically constructed four-dimensional configurations exhibit good agreement with these experimental findings. Although meeting the established criteria to identify time-crystalline order, both experiments and computer simulations reveal a space-time crystallization phase formed by particle-like topological solitons. The robustness against temporal perturbations and spatiotemporal dislocations shows the stability and rigidity of the studied space-time crystals, which relates to their locally topological nature and many-body interactions between emergent spontaneously twisted, particle-like solitonic building blocks. Their potential technological utility includes optical devices, photonic space-time crystal generators, telecommunications and anti-counterfeiting designs, among others.

Liquid crystals↗
DOE OSTI2025

Schrödinger cat states of a nuclear spin qudit in silicon

High-dimensional quantum systems are a valuable resource for quantum information processing. They can be used to encode error-correctable logical qubits, which has been demonstrated using continuous-variable states in microwave cavities or the motional modes of trapped ions. For example, high-dimensional systems can be used to realize ‘Schrödinger cat’ states, which are superpositions of widely displaced coherent states that can be used to illustrate quantum effects at large scales. Recent proposals have suggested encoding qubits in high-spin atomic nuclei, which are finite-dimensional systems that can host hardware-efficient versions of continuous-variable codes. Here, in this study, we demonstrate the creation and manipulation of Schrödinger cat states using the spin-7/2 nucleus of an antimony atom embedded in a silicon nanoelectronic device. We use a multi-frequency control scheme to produce spin rotations that preserve the symmetry of the qudit, and we constitute logical Pauli operations for qubits encoded in the Schrödinger cat states. Our work demonstrates the ability to prepare and control non-classical resource states, which is a prerequisite for applications in quantum information processing and quantum error correction, using our scalable, manufacturable semiconductor platform.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. Here, we discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

09 BIOMASS FUELS↗
DOE OSTI2022

Programmable heating and quenching for efficient thermochemical synthesis

Conventional thermochemical syntheses by continuous heating under near-equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways. As an alternative, we present a non-equilibrium, continuous synthesis technique that uses pulsed heating and quenching (for example, 0.02 s on, 1.08 s off) using a programmable electric current to rapidly switch the reaction between high (for example, up to 2,400 K) and low temperatures. The rapid quenching ensures high selectivity and good catalyst stability, as well as lowers the average temperature to reduce the energy cost. Using CH4 pyrolysis as a model reaction, our programmable heating and quenching technique leads to high selectivity to value-added C2 products (>75% versus <35% by the conventional non-catalytic method and versus <60% by most conventional methods using optimized catalysts). Our technique can be extended to a range of thermochemical reactions, such as NH 3 synthesis, for which we achieve a stable and high synthesis rate of about 6,000 μmol g Fe –1 h –1 at ambient pressure for >100 h using a non-optimized catalyst. Furthermore, this study establishes a new model towards highly efficient non-equilibrium thermochemical synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Origin of structural degradation in Li-rich layered oxide cathode

Li- and Mn-rich (LMR) cathode materials that utilize both cation and anion redox can yield substantial increases in battery energy density 1,2,3 . However, although voltage decay issues cause continuous energy loss and impede commercialization, the prerequisite driving force for this phenomenon remains a mystery 3,4,5,6 In this work, with in situ nanoscale sensitive coherent X-ray diffraction imaging techniques, we reveal that nanostrain and lattice displacement accumulate continuously during operation of the cell. Evidence shows that this effect is the driving force for both structure degradation and oxygen loss, which trigger the well-known rapid voltage decay in LMR cathodes. By carrying out micro- to macro-length characterizations that span atomic structure, the primary particle, multiparticle and electrode levels, we demonstrate that the heterogeneous nature of LMR cathodes inevitably causes pernicious phase displacement/strain, which cannot be eliminated by conventional doping or coating methods. We therefore propose mesostructural design as a strategy to mitigate lattice displacement and inhomogeneous electrochemical/structural evolutions, thereby achieving stable voltage and capacity profiles. These findings highlight the significance of lattice strain/displacement in causing voltage decay and will inspire a wave of efforts to unlock the potential of the broad-scale commercialization of LMR cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2023

Photonically active bowtie nanoassemblies with chirality continuum

Chirality is a geometrical property described by continuous mathematical functions. However, in chemical disciplines, chirality is often treated as a binary left or right characteristic of molecules rather than a continuity of chiral shapes. Although they are theoretically possible, a family of stable chemical structures with similar shapes and progressively tuneable chirality is yet unknown. Here we show that nanostructured microparticles with an anisotropic bowtie shape display chirality continuum and can be made with widely tuneable twist angle, pitch, width, thickness and length. The self-limited assembly of the bowties enables high synthetic reproducibility, size monodispersity and computational predictability of their geometries for different assembly conditions. The bowtie nanoassemblies show several strong circular dichroism peaks originating from absorptive and scattering phenomena. Unlike classical chiral molecules, these particles show a continuum of chirality measures that correlate exponentially with the spectral positions of the circular dichroism peaks. Finally, Bowtie particles with variable polarization rotation were used to print photonically active metasurfaces with spectrally tuneable positive or negative polarization signatures for light detection and ranging (LIDAR) devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗