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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Magnetic skyrmionic structures with variable topological charges in engineered Dzyaloshinskii-Moriya interaction systems

Magnetic skyrmionic structures, including magnetic skyrmions and antiskyrmions, are characterized by swirling spin textures with non-trivial topologies. They are featured with specific topological charges, Q , which are of crucial importance in determining their topological properties. Owing to the invariance of the chiral nature, it is generally believed that Q is conserved in a given magnetic skyrmionic structure and is hard to alter. Here, we experimentally realize the control of Q of magnetic skyrmionic structures at room temperature in a Dzyaloshinskii-Moriya interaction (DMI) platform with spatially alternating signs. Depending on how many times it crosses the interfaces between DMI regions with opposite signs, the magnetic skyrmionic structures possess different Q . Modifying the DMI energy landscape through chemisorbed oxygen, a magnetic topological transition is realized. This creation and manipulation of magnetic skyrmionic structures with controllable Q , in particular the DMI-stabilized thin-film antiskyrmions and high- Q skyrmionic structures, enables a new degree of freedom to control their dynamics via a novel DMI confinement effect. Our findings open up an unexplored avenue on various topological magnetic skyrmionic structures and their potential applications.

magnetic properties and materials↗
DOE OSTI2025

Geometric control of hyperbolic exciton-polariton condensate dimers

Coupled many-body quantum systems exhibit rich emergent physics with diverse stationary and dynamical behaviours. By engineering platforms with tunable and distinct coupling mechanisms, new insights emerge into the collective behaviour of coupled many body systems. Particles can be exchanged via evanescent or ballistic coupling: the former, based on proximity, yields large spectral splitting, while the latter requires strict phase-matching, analogous to phase-coupled harmonic oscillators and has a smaller impact on the energy landscape. We demonstrate an all-optically tunable quantum fluid dimer based on exciton-polariton condensates in a photonic crystal waveguide with hyperbolic (saddle-like) dispersion. Varying the dimer’s angle relative to the grating tunes the coupling from evanescent to ballistic. We directly observe spectral features and mass flow shaped by the saddle dispersion. This work highlights photonic crystals as powerful platforms to explore condensed matter phenomena lying at the interface between delay-coupled nonlinear oscillators and tight binding physics.

Georgakilas, Ioannis [IBM Research-Zurich, Rüschli↗
DOE OSTI2025

Room-temperature valley-selective emission in Si-MoSe 2 heterostructures enabled by high-quality-factor chiroptical cavities

Transition metal dichalcogenides possess valley pseudospin, enabling coupling between photon spin and electron spin for classical and quantum information processing. However, rapid valley-dephasing processes have impeded the development of scalable, high-performance valleytronic devices operating at room temperature. Here we demonstrate that a chiral resonant metasurface can enable room-temperature valley-selective emission in MoSe 2 monolayers independent of excitation polarization. This platform provides circular eigen-polarization states with a high quality factor (Q-factor) and strong chiral near-field enhancement. The fabricated Si chiral metasurfaces exhibit chiroptical resonances with Q-factors up to 450 at visible wavelengths. We reveal degrees of circular polarization (DOP) reaching a record high of 0.5 at room temperature. Our measurements show that the high DOP can be attributed to the significantly increased chiroptical local density of states, which enhances valley-specific radiative transition rates by a factor of ~13. Our work could facilitate the development of ultracompact chiral classical and quantum light sources.

42 ENGINEERING↗
DOE OSTI2025

Observation of interface piezoelectricity in superconducting devices on silicon

The development of superconducting quantum processors relies on understanding and mitigating decoherence in superconducting qubits. Piezoelectric coupling contributes to decoherence by mediating energy exchange between microwave photons and acoustic phonons. Although bulk centrosymmetric materials like silicon and sapphire are non-piezoelectric and commonly used as qubit substrates, the lack of centrosymmetry at interfaces may induce piezoelectric losses. This effect was predicted decades ago but never experimentally observed in superconducting devices. Here, we report interface piezoelectricity at aluminum-silicon junctions and demonstrate it as a significant loss channel in superconducting devices. Using aluminum interdigital transducers on silicon, we observe piezoelectric transduction from room to millikelvin temperatures, with an effective electromechanical coupling factor K 2 ≈ (3 ± 0.4) × 10−5%, comparable to weakly piezoelectric substrates. Modeling shows this mechanism limits qubit quality factors to Q ~ 10 4 − 10 8 , depending on surface participation and mode matching. These findings reveal interface piezoelectricity as a major dissipation channel and highlight the need for heterostructure and phononic engineering in next-generation superconducting qubits.

Zhou, Haoxin [University of California, Berkeley, ↗
DOE OSTI2026

Nonlinear thermodynamic computing out of equilibrium

We present the design for a thermodynamic computer that can perform arbitrary nonlinear calculations in or out of equilibrium. Simple thermodynamic circuits, fluctuating degrees of freedom in contact with a thermal bath and confined by a quartic potential, display an activity that is a nonlinear function of their input. Such circuits can therefore be regarded as thermodynamic neurons, and can serve as the building blocks of networked structures that act as thermodynamic neural networks, universal function approximators whose operation is powered by thermal fluctuations. We simulate a digital model of a thermodynamic neural network, and show that its parameters can be adjusted by genetic algorithm to perform nonlinear calculations at specified observation times, regardless of whether the system has attained thermal equilibrium. This work expands the field of thermodynamic computing beyond the regime of thermal equilibrium, enabling fully nonlinear computations, analogous to those performed by classical neural networks, at specified observation times.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2026

CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

Plant roots release a wide array of metabolites into the rhizosphere, shaping microbial communities and their functions. While metagenomics has expanded our understanding of these communities, little is known about the physiology of their members in host environments. Transcriptome analysis via RNA sequencing is a common approach to learning more, but its use has been challenging because of low bacterial biomass and interference from plant RNA. To overcome this, we developed a randomly-barcoded promoter-library insertion sequencing (RB-PI-seq) combined with chassis-independent recombinase-assisted genome engineering (CRAGE). Using Pseudomonas simiae WCS417 as a model rhizobacterium, this method enabled targeted amplification of barcoded transcripts, bypassing plant RNA interference and allowing measurement of thousands of promoter activities during Arabidopsis root colonization. Our analysis revealed temporally resolved transcriptional regulation, including those associated with cell growth, chemotaxis, plant immune suppression, biofilm formation, and stress responses, reflecting the coordinated physiological adaptation to the root environment. Additionally, we discovered that transcriptional activation of xanthine dehydrogenase and a lysozyme inhibitor is crucial for evading plant immune systems. This framework is scalable to other bacterial species and provides new opportunities for understanding rhizobacterial gene regulation in native environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Perovskite-driven solar C 2 hydrocarbon synthesis from CO 2

Photoelectrochemistry (PEC) presents a direct pathway to solar fuel synthesis by integrating light absorption and catalysis into compact electrodes. Yet, PEC hydrocarbon production remains elusive due to high catalytic overpotentials and insufficient semiconductor photovoltage. Here we demonstrate ethane and ethylene synthesis by interfacing lead halide perovskite photoabsorbers with suitable copper nanoflower electrocatalysts. The resulting perovskite photocathodes attain a 9.8% Faradaic yield towards C 2 hydrocarbon production at 0 V against the reversible hydrogen electrode. The catalyst and perovskite geometric surface areas strongly influence C 2 photocathode selectivity, which indicates a role of local current density in product distribution. The thermodynamic limitations of water oxidation are overcome by coupling the photocathodes to Si nanowire photoanodes for glycerol oxidation. These unassisted perovskite–silicon PEC devices attain partial C 2 hydrocarbon photocurrent densities of 155 µA cm -2 , 200-fold higher than conventional perovskite–BiVO 4 artificial leaves for water and CO 2 splitting. These insights establish perovskite semiconductors as a versatile platform towards PEC multicarbon synthesis.

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

A polyketide-based biosynthetic platform for diols, amino alcohols and hydroxy acids

Medium- and branched-chain diols and amino alcohols are important industrial solvents, polymer building blocks, cosmetics and pharmaceutical ingredients, yet biosynthetically challenging to produce. Here we present an approach that uses a modular polyketide synthase (PKS) platform for the efficient production of these compounds. This platform takes advantage of a versatile loading module from the rimocidin PKS and nicotinamide adenine dinucleotide phosphate-dependent terminal thioreductases. Reduction of the terminal aldehyde with alcohol dehydrogenases enables the production of diols, oxidation enables the production of hydroxy acids and specific transaminases allow the production of various amino alcohols. Furthermore, replacement of the malonyl-coenzyme A-specific acyltransferase in the extension module with methyl- or ethylmalonyl-coenzyme A-specific acyltransferase enables the production of branched-chain diols, amino alcohols and carboxylic acids in high titres. Use of our PKS platform in Streptomyces albus demonstrated the high tunability and efficiency of the platform.

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

An AI-accelerated pathway for reproducible and stable halide perovskites

Halide perovskites (HPs) have remarkable optoelectronic properties, and in the last decade their photovoltaic power conversion efficiency and light-emitting diode efficiency have skyrocketed. Despite the surge in research on these burgeoning materials, two key challenges in the field remain: material irreproducibility and instability. Their behavior is especially dynamic in response to environmental stressors, due to complex interactions with the perovskite crystal lattice. Here, in this review, we survey the latest achievements in HP materials research accomplished with the assistance of artificial intelligence (AI), through the implementation of automated experimentation and machine learning (ML) data analysis. Automated synthesis and characterization tackle problems with material irreproducibility by systematically controlling parameters with very high precision, creating massive datasets, and allowing methodical comparisons from which unbiased conclusions can be drawn. AI can reveal otherwise unnoticed trends, inform future experiments with the highest potential information gain, and forecast future performance. The review concludes with a forward viewpoint of how human-assisted closed-loop laboratories and shared databases allow halide perovskite materials’ processing, properties, and performance to be potentially optimized with AI, accelerating the development of highly reproducible and stable optoelectronic devices.

Hering, Abigail R. [Univ. of California, Davis, CA↗
DOE OSTI2025

Advancing microelectronics through nanoscale science: A perspective on needs and opportunities from the nanoscale science research centers

Microelectronics are the cornerstone of the modern world, enhancing our daily lives by providing services such as communications and datacenters. These resources are accessible thanks to the continual pursuit of a deeper understanding of the chemical and physical phenomena underlying the materials synthesis approaches and fabrication processes used to create microelectronic components and subsequently the components' responses to electrical, optical, and other stimuli that are utilized within microelectronic systems. Today, further development of microelectronics requires multidisciplinary expertise across scientific disciplines and fields of study—synthesis, materials characterization, nanoscale fabrication, and performance characterization—with focus placed on comprehending the nanoscale forms and features of microelectronic components. The Nanoscale Science Research Centers (NSRCs) are Department of Energy, Office of Science user facilities that support the international scientific community in advancing nanoscale science and technology. As a key component of the U.S. Government's National Nanotechnology Initiative, the NSRCs enable transformative discoveries by providing world-class facilities, expertise, and collaborative opportunities. Here, in this perspective, we showcase a non-exhaustive cross-section of the capabilities housed at and developed by the NSRCs and their user communities to address fundamental synthesis, metrology, fabrication, and performance considerations toward advancing the development of new microelectronics. Finally, we provide a timely outlook on the next major areas of necessary development in nanoscale sciences to continue the innovation of microelectronics into the next generation.

2D materials↗
DOE OSTI2025

Unraveling the Origin of Glassy Thermal Transport in Medium-Entropy Semiconductors: From Nanoscale Phase Segregation to Atomic-Scale Lattice Distortion

Thermoelectric (TE) materials can directly and reversibly convert heat into electricity, offering a promising pathway for reshaping the global energy landscape. The performance of thermoelectric materials is evaluated using the figure of merit, zT = S 2 σT/κ, which can be optimized by improving Seebeck coefficient (S) and electrical conductivity (σ) while suppressing the thermal conductivity (κ) at the operating temperature (T). Here, we introduce a medium-entropy metal chalcogenide that exhibits phonon-glass electron-crystal behavior. The conventional perspective hypothesizes that the suppression of thermal transport arises solely from disordered atomic occupation, which enhances alloy scattering mechanisms for phonon transport. However, emerging evidence suggests the presence of structural and chemical inhomogeneity at multiple length scales in entropy-engineered materials, a phenomenon that has rarely been investigated in detail.

Liu, Yukun [Northwestern Univ]↗
DOE OSTI2026

Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.

4D-STEM↗
DOE OSTI2025

Carrier Localization and Spontaneous Formation of Two-Dimensional Polarization Domain in Halide Perovskites

Halide perovskites are known for their rich phase diagram and superior performance in diverse optoelectronics applications. The latter property is often attributed to the long electron-hole recombination time, whose underlying physical mechanism has been a long-standing controversy. In this Letter, we investigate the transport and localization properties of electron and hole carriers in a prototypical halide perovskite (CsPbBr 3 ), through ab initio tight-binding nonadiabatic dynamics approach for large-scale (tens of nm size) supercell calculations, to simulate electron and ion dynamics on the same footing. Here, we found distinct structural, lattice polarization, and electron-phonon coupling properties at low (below 100 K) and high temperatures, consistent with experimental observations. In particular, at low temperature we find spontaneous formation of polar grain boundaries in the nonpolar bulk systems, which result in two-dimensional polarization patterns that serve to localize and separate electrons and holes. We reveal phonon-assisted variable-range hopping mostly responsible for low-temperature transport, and their characteristic frequency correlates with temperature-dependent phonon power spectrum and energy oscillation frequency in nonadiabatic dynamics. We answer the critical questions of long electron-hole recombination lifetime at low temperature and offer the correlation among polarization domains, electron-phonon couplings, and photocarrier dynamics.

Carrier generation & recombination↗
DOE OSTI2025

First-principles computations of the Stark shift of a defect-bound exciton: The case of the T center in silicon

The T center in silicon has recently drawn a lot of attention for its potential in quantum information science. The sensitivity of the zero-phonon line (ZPL) to electrical field was recently investigated by a combination of different experimental methods but there are still few first principles studies on the Stark shift of the T center. Dealing with the defect-bound exciton nature of the excited state is particularly challenging using density functional theory because of the large spatial delocalization associated with the wavefunction. Here, in this work, we tackle this issue by performing a convergence study over the supercell size. We obtain an exciton binding energy of 28.5 meV, in good agreement with experimental results. We then calculate the Stark shift through the dipole moment change of the ZPL transition of the T center using the modern theory of polarization formalism and find a modest linear coefficient of Δ⁢𝜇=0.79⁢D along X and Δ⁢𝜇=0.03⁢𝐷 along Y. We discuss our results in light of the recent experimental measurements of the Stark shift. Our analysis suggests that bound-exciton defects could be particularly sensitive to local field effect as a result of their large spatial extent.

color centers↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2025

Dipolar Aleppo lattice: Ground state ordering and ergodic dynamics in the absence of vertex frustration

We introduce the Aleppo spin ice geometry, another variation of decimated square ice patterns, which in contrast to similar systems previously studied, does not exhibit vertex frustration. Using synchrotron-based photoemission electron microscopy, we directly visualize low-energy states achieved after thermal annealing, in addition to temperature-dependent moment fluctuations. The results reveal the observation of ground state patterns and the absence of ergodicity-breaking dynamics. Our observations further confirm vertex frustration to be an important criterion for the emergence of ergodicity transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Neural units with time-dependent functionality

We show that the time-resolved dynamics of an underdamped harmonic oscillator can be used to do multifunctional computation, performing distinct computations at distinct times within a single dynamical trajectory. We consider the amplitude of an oscillator whose inputs influence its frequency. The activity of the oscillator at fixed times is a nonmonotonic function of its inputs, so it can solve problems such as XOR that are not linearly separable. The activity of the oscillator at fixed input is a nonmonotonic function of time, so it is multifunctional in a temporal sense, and able to carry out distinct nonlinear computations at distinct times within the same dynamical trajectory. We show that a single oscillator, observed at different times, can act as all of the elementary logic gates and perform binary addition, the latter usually implemented in hardware using five logic gates. We show that a set of n oscillators, observed at different times, can perform an arbitrary number of analog-to-n-bit digital conversions. We also show that oscillators can be trained by gradient descent to perform distinct classification tasks at distinct times. Computing with time-dependent functionality can be done in or out of equilibrium, and suggests a way of reducing the number of parameters or devices required to do nonlinear computations.

97 MATHEMATICS AND COMPUTING↗