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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Antimicrobial Peptides Can Facilitate Whole Blood Safety from Bacteria: A Proof of Concept

With continuous improvements to blood donor deferrals and the availability of sensitive tests for donation screening for infectious agents, bacterial contamination of whole blood (WB) and blood components stored for transfusion is a rare event. Nonetheless, it still occurs and remains a transfusion-associated risk in terms of septic transfusion reactions (STRs) and transfusion-transmitted bacterial infections with morbidity and mortality outcomes. One of the risk mitigation strategies for bacterial contamination is to implement treatment with currently available proactive pathogen reduction technologies (PRTs) for these transfusion products. Here, as a proof of concept, we tested two recently developed unique cationic antimicrobial peptides (AMPs; D-CONGA and D-CONGA-Q7) for WB safety from bacterial contamination. In this study, WB was inoculated with Escherichia coli and Staphylococcus epidermidis and treated with the two peptides to evaluate their bactericidal efficacy. The results demonstrated that D-CONGA and D-CONGA-Q7 exhibit potent inhibitory activity against the bacteria with a minimal inhibitory concentration (MIC) range of 4–8 and 1–8 μM, respectively, depending on the bacterial species tested. Time-kill kinetics further confirmed that the peptides exhibit bactericidal efficacy at 8 μM by achieving a 5-log 10 reduction (99.999%) of the bacterial load in WB with a time-dependent killing profile. Furthermore, even at 20 μM, the AMPs did not negatively impact hemolysis or hemostatic properties. We have further demonstrated using a cationic exchange resin that the cationic AMPs can be separated and removed from WB after the peptide treatments. During 35-day WB storage at 2–8 °C, 4 μM D-CONGA-Q7 one-time treatment prevented S. epidermidis growth and preserved WB quality and integrity. Overall, the results described here provide the first proof of concept that certain AMPs, such as D-CONGA and D-CONGA-Q7, can facilitate WB safety from bacteria during storage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Chiral flat-band optical cavity with atomically thin mirrors

A fundamental requirement for photonic technologies is the ability to control the confinement and propagation of light. Widely used platforms include two-dimensional (2D) optical microcavities in which electromagnetic waves are confined in either metallic or distributed Bragg reflectors. Recently, transition metal dichalcogenides hosting tightly bound excitons with high optical quality have emerged as promising atomically thin mirrors. In this work, we propose and experimentally demonstrate a subwavelength 2D nanocavity using two atomically thin mirrors with degenerate resonances. Angle-resolved measurements show a flat band, which sets this system apart from conventional photonic cavities. We demonstrate how the excitonic nature of the mirrors enables the formation of chiral and tunable optical modes upon the application of an external magnetic field. Moreover, we show the electrical tunability of the confined mode. Our work demonstrates a mechanism for confining light with high-quality excitonic materials, opening perspectives for spin-photon interfaces, and chiral cavity electrodynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)

The project “Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)” addressed food waste disposal challenges by successfully converting food waste to bioplastics (known as PHAs). The novel process created by our team of researchers from universities, national labs, and industry substantially enhanced overall carbon conversion efficiency of food waste processing (> 50%), while reducing disposal costs (> 25%). The project showed economic viability potential at community scale through pilot-scale demonstration at a relevant scale (50 L reactor volume) with more than 100 hours of PHA production using realistic conditions. The project goal was to valorize food waste by shunting traditional anaerobic digestion processing and creating a value-added PHA processing route that improves the economics and sustainability of local, community-scale, wet organic waste treatment. First, the food waste undergoes microbial-based, dark fermentation to break down the food to small carbon chains known as volatile fatty acids (VFAs). Instead of microorganisms converting the VFAs into methane using normal anaerobic digestion processing, our innovative process inhibits methane production. This preserves the produced VFAs for extraction and use by a novel Haloferax mediterranei (HM) archaea, which effectively converts the VFAs to bioplastics. The project added microbial electrochemical cells (MEC) to the dark fermentation process to enhance the VFAs produced and optimize the type of bioplastics formed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Foaming prediction in pure liquids from dimensionless numbers inspired by the theory of fluid behavior for drops

Foaming prediction is critical for selecting materials and designing processes in industries such as bioprocessing and gas processing. Existing models lack the generality needed for a wide range of materials and overlook the foaming behavior in pure liquids. Here, this work presents a novel method for predicting foaming in pure liquids based on their density, surface tension, and viscosity, using Reynolds ( Re ) and Ohnesorge ( Oh ) numbers. A foaming prediction map, leveraging the theory of fluid drop behavior, was developed by plotting these numbers. This map delineates distinct non-foaming and foaming regions, functioning as a binary classifier for foaming predictions. The map was fitted and validated through shake test experiments on 46 liquids, demonstrating reliable predictions, except for a specific region characterized by small Oh and large Re numbers. This region corresponded to relatively low foam stability and high turbulence, making foaming predictions challenging for liquids in this category.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

AGFormer: Adaptive Spatiotemporal graph informed transformer for multi-reservoir inflow forecasting

Accurate reservoir inflow forecasting is crucial for effective water resource management, yet most machine learning models focus on single-reservoir prediction and overlook spatial dependencies among hydrologically connected reservoirs. Here, we propose AGFormer (Adaptive Graph-Informed Transformer), an end-to-end framework that integrates adaptive graph learning with temporal sequence modeling for multi-reservoir inflow forecasting. A shared encoder and graph attention mechanism generate reservoir-specific embeddings, which are then processed by the Transformer-based encoder–decoder for multi-step inflow forecasting. We also introduce a pretraining paradigm to learn robust temporal embeddings from misaligned historical records. Evaluated on 30 reservoirs in the Upper Colorado River Basin, AGFormer achieves superior seven-day-ahead forecasts, with NSE > 0.75 for 20 reservoirs—outperforming Encoder–Decoder LSTM, GCN+LSTM, and Transformer baselines. Adaptive graph learning captures dynamic inter-reservoir dependencies, and feature attribution aligns with snowmelt-driven hydrology. Incorporating forecasted meteorological inputs further enhances accuracy, demonstrating AGFormer’s potential to support reservoir management under dynamic hydrological conditions.

Adaptive graph learning↗
DOE OSTI2025

Hydrogen-rich syngas production from the steam co-gasification of low-density polyethylene and coal refuse

Gasification provides a promising pathway for transforming waste materials into valuable products, such as fuels and chemicals. Here, this study investigates the steam co-gasification of low-density polyethylene (LDPE) and compressed thickener underflow, representative of coal refuse (CR), in a drop tube reactor. The effects of feed blend ratio (0–100 wt% LDPE) and temperature (800–1000 °C) on syngas composition, tar formation, and process efficiency are examined. The high volatility of LDPE makes it more reactive than CR but also promotes the formation of 2–7 ring aromatic tars. Increasing temperature improves carbon conversion efficiency (CCE), cold gas efficiency (CGE), and syngas yield, although the lower heating value (LHV) of syngas decreases. Hydrogen is the dominant gas product, reaching 59 vol% with the H 2 /CO molar ratio ranging from 2.27 to 4.74. Synergistic effects from alkali and alkali earth metals (AAEMs), particularly K and Ca, in CR ash enhance syngas yield by catalyzing char gasification and tar cracking. Hematite (Fe 2 O 3 ) and ash from sub-bituminous/bituminous coals are explored as tar reforming catalysts. Fe 2 O 3 achieves 100 % tar reforming efficiency, while coal ash, with a lower Fe 2 O 3 content (15 wt%), is less effective at cracking polycyclic aromatic hydrocarbons, particularly naphthalene. These findings demonstrate the flexibility of co-gasification, allowing precise tuning of syngas characteristics for specific downstream applications. Further optimization of waste-derived catalysts could enhance the economic viability of gasification in waste-to-energy processes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

A foundation model for non-destructive defect identification from vibrational spectra

Defects are ubiquitous in solids and strongly influence materials’ functional properties. However, non-destructive characterization and quantification of defects, especially when multiple types coexist, remain a long-standing challenge. Here, we introduce DefectNet, a foundation machine learning model that predicts the chemical identity and concentration of substitutional point defects with multiple coexisting elements directly from vibrational spectra, specifically phonon density-of-states (PDoS). Trained on over 16,000 simulated spectra from 2,000 semiconductors, DefectNet employs a tailored attention mechanism to identify up to six distinct defect elements at concentrations ranging from 0.2% to 25%. The model generalizes well to unseen crystals across 56 elements and can be fine-tuned on experimental data. Validation using inelastic scattering measurements of SiGe alloys and MgB 2 superconductor demonstrates its accuracy and transferability. Furthermore, our work establishes vibrational spectroscopy as a viable, non-destructive probe for bulk point defect quantification, and highlights the promise of foundation models in data-driven defect engineering.

artificial intelligence↗
DOE OSTI2025

Real-time reconstruction of ground motion during small magnitude earthquakes: A pilot study

This study presents a pilot investigation into a novel method for reconstructing real-time ground motion during small magnitude earthquakes (M < 4.5), removing the need for computationally expensive source characterization and simulation processes to assess ground shaking. Small magnitude earthquakes, which occur frequently and can be modeled as point sources, provide ideal conditions for evaluating real-time reconstruction methods. Utilizing sparse observation data, the method applies the Gappy Auto-Encoder (Gappy AE) algorithm for efficient field data reconstruction. This is the first study to apply the Gappy AE algorithm to earthquake ground motion reconstruction. Numerical experiments conducted with SW4 simulations demonstrate the method’s accuracy and speed across varying seismic scenarios. The reconstruction performance is further validated using real seismic data from the Berkeley area in California, USA, demonstrating the potential for practical application of real-time earthquake data reconstruction using Gappy AE. As a pilot investigation, it lays the groundwork for future applications to larger and more complex seismic events.

58 GEOSCIENCES↗
DOE OSTI2025

Reversible long-range domain wall motion in an improper ferroelectric

Reversible ferroelectric domain wall movements beyond the 10 nm range associated with Rayleigh behavior are usually restricted to specific defect-engineered systems. Here, we demonstrate that such long-range movements naturally occur in the improper ferroelectric ErMnO 3 during electric-field-cycling. We study the electric-field-driven motion of domain walls, showing that they readily return to their initial position after having traveled distances exceeding 250 nm. By applying switching spectroscopy band-excitation piezoresponse force microscopy, we track the domain wall movement with nanometric spatial precision and analyze the local switching behavior. Phase field simulations show that the reversible long-range motion is intrinsic to the hexagonal manganites, linking it to their improper ferroelectricity and topologically protected structural vortex lines, which serve as anchor point for the ferroelectric domain walls. Our results give new insight into the local dynamics of domain walls in improper ferroelectrics and demonstrate the possibility to reversibly displace domain walls over much larger distances than commonly expected for ferroelectric systems in their pristine state, ensuring predictable device behavior for applications such as tunable capacitors or sensors.

Zahn, Manuel [Norwegian Univ. of Science and Techn↗
DOE OSTI2025

Advanced Simulation of ITER Core X-ray Crystal Spectroscopy

X-Ray Simulation Analysis (XRSA) is an analytical ray-tracing mixed code developed specifically for the ITER Core X-Ray Crystal Spectroscopy (XRCS-Core) diagnostic, which employs a dual-reflection configuration incorporating multiple pre-reflectors made of Highly Oriented Pyrolytic Graphite (HOPG) and spherically curved analyzing crystals. The ITER XRCS-Core is designed for high spectral resolution measurement in specific wavelength ranges, including narrow bands around 1.354 Å for W 64+ , 2.19 Å for Xe 51+ , and 2.555 Å for Xe 44+ and Xe 47+ , enabling diagnostic capability across a broad electron temperature range in the ITER plasma. XRSA facilitates efficient simulation of the spectral performance of this complex X-ray spectroscopic system. Recent updates to the XRSA code have incorporated two critical effects: auto-focusing, which specifically applies to HOPG, and polarization. These two effects are particularly important in the dual-reflection configuration used in the ITER XRCS-Core system to provide more accurate modeling results. Here, simulations conducted with the updated code demonstrate that polarization has a substantial impact on the performance of the dual-reflection system. Additionally, the combined influence of polarization and system layout introduces performance variations across channels through the same crystal.

Computer graphics↗
DOE OSTI2025

An enzyme-based approach for highly efficient self-replication of DNA origami dimers

Self-replication and exponential growth are essential to all living things, the driving force for Darwinian evolution, and potentially useful in nanotechnology for large-scale production of nanoscopic materials. An artificial (nonliving) self-replication system has been shown to exhibit exponential growth and selection using DNA monomer origami tiles templated on a dimer seed. That system purposefully avoided the use of enzymes to get a hint of how self-replication might have evolved in a prebiotic world by using CNV K and UV light to crosslink complementary DNA single strands. For further investigations into competition and extinction and for potential applications involving biocompatibility, we wanted to investigate enzymatic ligation to replace the chemical photo crosslinking step. Here, we present a system which uses thermotolerant T4 DNA ligase and no UV. This system has several additional advantages including a much faster cycling time, yielding 2,000,000 amplifications in 12 h. We also introduce competition to study the possibility of Darwinian-like evolution. Two pairs of DNA origami tiles compete for the same connection strands and show different growth rates under different connection strand concentrations. This system has the potential to combine with other enzymes, such as RNA polymerase to support feedback, allowing us to fine-tune replication dynamics and achieve sophisticated, life-like behaviors. The highly efficient self-replication and exponential growth of DNA origami dimers demonstrated in this work not only enhances our understanding of Darwinian evolution in nature but also opens the door to applications ranging from synthetic biology to smart materials.

Science & Technology - Other Topics↗
DOE OSTI2026

String-Breaking Dynamics in Quantum Adiabatic and Diabatic Processes

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking : the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments.

Ising model↗
DOE OSTI2026

Single-shot imaging with randomized structured illumination at a free electron laser

Stroboscopic nanoscale imaging with free electron laser light is revolutionizing our understanding of fast dynamics in heterogeneous systems. The short wavelength of X-ray and extreme ultraviolet radiation makes it possible to achieve nanoscale resolution, while resonance with atomic transitions gives access to electronic and magnetic degrees of freedom. Here, we report on our implementation of a recently developed imaging method, randomized probe imaging, at a free electron laser. The advantage of randomized probe imaging over existing methods is its compatibility with extended and strongly scattering samples. Our implementation delivers robust single-shot reconstructions at up to a full-pitch resolution of 400 nm over a field of view with a 40 µm diameter. We also demonstrate single-shot imaging of magnetic domain structures using circular dichroism at resonance, paving the way to future time-resolved studies of magnetic dynamics, shock physics, and the dynamics of collective electronic phases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗
DOE OSTI2025

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.

Wei, Yuxiang [Georgia Institute of Technology]↗
DOE OSTI2025

Mechanism of Lithium Ion Exchange Into Spinel Manganese Oxide

Lithium manganese oxide (LMO) is an effective absorbent for lithium recovery from brines, characterized by its high adsorption capacity, excellent regeneration performance, and selectivity. Here, this study investigates the mechanisms of material degradation during lithium loading and unloading in LMO, employing a combination of time‐resolved Raman spectroscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy. Key findings reveal that the A 1g vibrational mode wavenumber shifts from 635 cm −1 at the onset of lithium ion exchange to 656 cm −1 after 12 min, indicating local symmetry loss and manganese (Mn) loss during lithium intercalation. The proposed lithium exchange mechanism involves initial occupation of tetrahedral interstitial voids, followed by migration into interstitial sites between Mn octahedral sites. Computational modeling suggests that the loss of symmetry in MnO cubane‐like groups occurs as lithium migrates, significantly affecting the Raman spectra. Importantly, the study demonstrates that after 100 cycles of lithium/hydrogen loading, a 24% loss in Mn is observed, which correlates with decreased structural stability; however, the structural integrity of LMO is enhanced when subjected to multiple cycles without complete loading. Here, these insights contribute to the understanding of LMO's performance in lithium recovery applications and highlight potential strategies to optimize its use in future technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Nanoscale polarization transient gratings

Light manipulation at the nanoscale is essential both for fundamental science and modern technology. The quest to shorter lengthscales, however, requires the use of light wavelengths beyond the visible. In particular, in the extreme ultraviolet regime these manipulation capabilities are hampered by the lack of efficient optics, especially for polarization control. Here, we present a method to create periodic, polarization modulations at the nanoscale using a tailored configuration of the FERMI free electron laser and demonstrate its capabilities by comparing the dynamics induced by this polarization transient grating with those driven by a conventional intensity grating on a thin ferrimagnetic alloy. While the intensity grating signal is dominated by the thermoelastic response, the polarization grating excitation minimizes it, uncovering helicity-dependent responses previously undetected. We anticipate nanoscale polarization transient gratings to become useful for the study of physical, chemical and biological systems possessing chiral symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Optical control of integer and fractional Chern insulators

Optical control of topology, particularly in the presence of electron correlations, is an interesting topic with broad scientific and technological impact. Twisted MoTe 2 bilayer (tMoTe 2 ) is a zero-field fractional Chern insulator (FCI), exhibiting the fractionally quantized anomalous Hall effect. As the chirality of the edge states and sign of the Chern number are determined by the underlying ferromagnetic polarization, manipulation of ferromagnetism would realize control of the Chern insulator (CI)/FCI states. Here, in this work, we demonstrate control of ferromagnetic polarization, and thus the CI and FCI states, by circularly polarized optical pumping in tMoTe 2 . At low excitation power, we achieve on-demand preparation of ferromagnetic polarization by optical training, that is, electrically tuning the system from non-ferromagnetic to desirable ferromagnetic states under helicity-selective optical pumping. With increased excitation power, we further realize direct optical switching of ferromagnetic polarization at a temperature far below the Curie temperature. Both optical training and direct switching are most effective near CI and FCI states, which we attribute to a gap-enhanced valley polarization of optically pumped holes. The magnetization can be dynamically switched by modulating the helicity of optical excitation. Spatially resolved measurements further demonstrate optical writing of ferromagnetic, and thus CI (or FCI) domains. Our work realizes precise optical control of a topological quantum many-body system with potential applications in topological spintronics, quantum memories and creation of exotic edge states by programmable patterning of integer and fractionally quantized anomalous Hall domains.

ferromagnetism↗