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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 451 records · Page 25

High-Q cavity interface for color centers in thin film diamond

Quantum information technology offers the potential to realize unprecedented computational resources via secure channels distributing entanglement between quantum computers. Diamond, as a host to optically-accessible spin qubits, is a leading platform to realize quantum memory nodes needed to extend such quantum links. Photonic crystal (PhC) cavities enhance light-matter interaction and are essential for an efficient interface between spins and photons that are used to store and communicate quantum information respectively. Here, we demonstrate one- and two-dimensional PhC cavities fabricated in thin-film diamonds, featuring quality factors (Q) of 1.8 × 10 5 and 1.6 × 10 5 , respectively, the highest Qs for visible PhC cavities realized in any material. Importantly, our fabrication process is simple and high-yield, based on conventional planar fabrication techniques, in contrast to the previous with complex undercut processes. We also demonstrate fiber-coupled 1D PhC cavities with high photon extraction efficiency, and optical coupling between a single SiV center and such a cavity at 4 K achieving a Purcell factor of 18. The demonstrated photonic platform may fundamentally improve the performance and scalability of quantum nodes and expedite the development of related technologies.

97 MATHEMATICS AND COMPUTING↗

CO2 Enhanced Oil Recovery Evaluation System (CO2_E_EvSystem), Version 2025

The United States Department of Energy’s (DOE’s) Office of Fossil Energy and the National Energy Technology Laboratory (NETL) developed a suite of screening-level, techno-economic models/tools, known as the CO2_E_EvSystem, to evaluate technical aspects and costs of using carbon dioxide (CO2) enhanced oil recovery (EOR) to store CO2 and produce oil. CO2_E_EvSystem has three software components and several input and output files. The software components are CO2_E_EvTool, CO2_Prophet, and CO2_E_COM. Almost all computational work is performed by CO2_Prophet and CO2_E_COM, which are both Fortran programs. The primary role of CO2_E_EvTool is to manage input and output files for the two programs, run the two programs, allow multiple oilfields to be evaluated in a single run, and generate files that summarize the results for all the oilfields run. This version of the CO2_E_EvSystem includes a residual oil zone dataset from the San Andres formation, Permian Basin, to demonstrate the system and guide users on attributes needed for dataset inputs.

AS↗

A Sensitive Electrochemical Cholinesterase-Inhibiting Biosensor for Organophosphorus Pesticides Based on Ti 3 C 2 TX MXene Quantum Dots

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti 3 C 2 T x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10 −17 M and a wide linear range (10 −14 –10 −8 M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection.

Chemistry↗

Jupiter Laser Facility Annual Report, FY 2025

Dear JLF community, I cannot believe I am now entering my third year as JLF director — time definitely flies when you are having fun! FY25 was another pivotal year for the Jupiter Laser Facility, marked by both scientific achievement and growing visibility for our community. Building on the successful reopening and refurbishment of the facility, we continued to demonstrate how JLF drives innovation in high energy density and fusion energy science, laser technology, and workforce development. Across Janus, Titan, and COMET, users executed a diverse portfolio of experiments, from dynamic compression and opacity measurements to laser plasma interactions, laboratory astrophysics, and advanced diagnostics. These efforts are highlighted in this report, including the development of new probes that capture the time evolution of plasmas on a single shot, and diagnostics and platforms that are already impacting experiments at NIF and other large facilities. JLF continues to serve as both a testbed for new ideas and a bridge to larger scale campaigns. FY25 also showcased the broader role of JLF within the Laboratory and the national HED science ecosystem. The NIF JLF User Groups Meeting in February brought nearly 180 participants to Livermore and highlighted the scientific progress made during JLF’s first full year of renewed operations. JLF research and users were recognized with Director’s Institutional Awards and Early and Mid Career awards, underscoring the quality and impact of the work performed here. Our team also contributed prominently to national conversations about laser safety, plasma physics, and inertial fusion energy through invited talks, conferences, and professional society leadership. JLF’s integration with LaserNetUS deepened this year as well. We launched a new technical exchange program across LaserNetUS facilities and kicked it off with a JLF team visit to the BELLA Center at Lawrence Berkeley National Laboratory. These exchanges are strengthening operations, sharing best practices, and improving the user experience across the network. Filming for the LaserNetUS “Behind the Scenes” series and participation in the annual LaserNetUS meeting further increased the visibility of our facility and our users. At the same time, JLF continues to play a central role in ambitious new programs, such as the Big Aperture Thulium laser effort funded through one of the DOE Office of Science Microelectronics Science Research Centers, which will use JLF infrastructure to explore next generation high rep rate lasers for EUV and x-ray source development. A core part of our mission remains training the next generation of scientists. In FY25, we welcomed another cohort of summer students, who joined experimental teams on Titan and presented their research at LLNL’s student poster symposium and national inertial fusion energy meetings. JLF users and early career scientists showcased their work at conferences across the country, highlighting experiments performed at the facility. These hands on experiences, and the mentoring provided by our staff and user teams, are central to JLF’s identity as a true user facility. Finally, FY25 reinforced JLF’s role as a focal point for partnerships and outreach. We hosted visits from international collaborators, science leaders, and we shared the story of the facility through venues such as the Big Ideas Lab podcast. These interactions help connect our work to a broader scientific and policy audience and open new pathways for collaboration. As we look ahead, the combination of refurbished hardware, new capabilities like STILETTO and enhanced short pulse performance on Titan, strong partnerships across LLNL and LaserNetUS, and a growing user community positions JLF for an even more ambitious program in the coming years. I am deeply grateful to our technical and operations staff for their dedication, to our LLNL partners for their continued support, and to our users for bringing bold, creative ideas to the facility. I look forward to more experiments, capabilities, partnerships, and groundbreaking science in the years to come! With brightest regards, Félicie Albert, JLF Director.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗

Human perception of ionizing radiation

Here, in this work, we address the question of whether humans can perceive ionizing radiation. We conducted a thorough review of the clinical and experimental literature related to ionizing radiation, with a focus on its acute effects. Specifically, we examined the three domains of X-ray perception found in animals (abdominal, olfactory, and retinal), which led us to instances of ionizing radiation-induced hearing and taste sensory phenomena in humans thus suggesting that humans can perceive X-rays across various sensory modalities via multiple mechanisms. We also analyzed literature to understand the mechanisms associated with reported symptoms, this led us to the concept of radiomodulation, an understudied modulatory effect of sub-ablative ionizing radiation doses on neurons. Based on this review of the literature we propose the hypothesis that a significant radiomodulation mechanism is the formation of reactive oxygen species from radiolysis which activates immune and sensory signal transduction mechanisms specifically related to the redox activity in TRP and K+ channels. Additionally, we find evidence to support the previous claims of perception stemming from Cherenkov radiation and ozone production which are perceived using canonical sensory modalities. Finally, for we provide a concise summary of the applications of ionizing radiation in clinical imaging and therapy, as well as prospects for future developments of radiation technologies for biomedical and fundamental research.

Ionizing radiation↗

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗

Towards low-carbon low-energy concrete alternatives: Life cycle assessment of carbonated cementitious material-based precast panels

Cement is responsible for 22 % of all global CO 2 emissions from industrial processes. Technological innovation for developing and deploying of alternative materials will be required to decarbonize the cement industry. Carbonated cementitious materials (CCMs) are building materials that rely on carbon mineralization for their strength. A process-based cradle-to-gate life cycle assessment (LCA) was conducted to evaluate the global warming potential (GWP), cumulative energy demand, and water consumption of a lab-scale CCM-based precast panel compared to a conventional precast concrete panel. Since the CCM process is currently a lab-scale early-stage process, the CCM panel showed higher environmental impacts compared to the conventional panel. However, scenario analyses include mature production process scenarios. In conclusion, a sensitivity analysis revealed that the GWP of CCM can be lowered to below that of the conventional panel using polymers, fillers, low-carbon electricity sources, and optimized carbonation parameters.

36 MATERIALS SCIENCE↗

Elucidating the Origins of High Capacity in Iron-Based Conversion Materials: Benefit of Complementary Advanced Characterization toward Mechanistic Understanding

Lithium-ion batteries are recognized as an important electrochemical energy storage technology due to their superior volumetric and gravimetric energy densities. Graphite is widely used as the negative electrode, and its adoption enabled much of the modern portable electronics technology landscape. However, developing markets, such as electric vehicles and grid-scale storage, have increased demands, including higher energy content and a diverse materials supply chain. Alternatives that provide the opportunity to increase capacity and address supply chain concerns are of interest. Understanding the fundamental mechanisms that govern battery function is crucial to driving further improvements in the field. Advanced characterization techniques, such as those enabled by synchrotron light sources and high-resolution electron microscopes, that can uncover these mechanisms have become a necessity for elucidating structural evolution upon electrochemical conversion at the nano- to mesoscales. Performing these experiments with relevant electrochemistry using in situ and operando experiments imparts the ability to identify critical reaction pathways and capture intermediate (dis)charge products not discernible by traditional experiments.

36 MATERIALS SCIENCE↗

In Situ Analysis of Electron-Induced Chemical Transformations in Vapor-Phase-Synthesized Al-Based Inorganic–Organic Hybrid Thin Films for EUV Resist Platform

The rapid advancement and stringent requirements of extreme ultraviolet (EUV) lithography technology necessitate the development of advanced photoresist systems for next-generation microelectronics. Recent studies have demonstrated that inorganic-based hybrid photoresists offer notable improvements in EUV sensitivity, etch resistance, and greater insusceptibility to pattern collapse compared to their purely organic counterparts. However, variations in the synthesis/coating approaches and chemistry of inorganic–organic photoresists can result in distinct exposure mechanisms. In this work, an Al-based hybrid thin film resist system synthesized via molecular (atomic) layer deposition (MLD or MALD) is explored, focusing on its electron-beam and EUV patterning mechanisms. The Al-based hybrid thin films are deposited using trimethylaluminum (TMA) and the organic precursor hydroquinone, exhibiting a saturated growth rate within the temperature range of 150–200°C. In diluted tetramethylammonium hydroxide (TMAH)-based developer solutions, the electron-irradiated Al-based hybrid thin film system behaves as a negative tone resist, achieving a sensitivity of 10.4 mC/cm 2 at 0.1 kV electron beam lithography (EBL). Chemical changes induced by electron exposure are also analyzed in this study using X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and a unique infrared spectroscopy setup, revealing the potential cross-linking pathways. To further correlate the electron-induced chemical transformations with those mediated by EUV irradiations, a combination of X-ray photoemission electron microscopy/low-energy electron microscopy (XPEEM/LEEM) system is also employed. In conclusion, this study provides critical insights into the mechanisms underlying solubility switching and contributes to the design of advanced resist materials for EUV lithography.

36 MATERIALS SCIENCE↗

Assessment of Different Application Grades of Post-Consumer Recycled (PCR) Polyolefins from Material Recovery Facilities (MRFs) in the United States

The recycling of plastics has been gaining traction in the following years as many companies, organizations, and governments are pushing toward a more circular economy. However, plastic recycling rates are still small compared to those of plastic production, especially for polyolefins, such as high-density polyethylene (HDPE) and polypropylene (PP). With the goal of finding applications for recycled plastic resin, recyclers can face some challenges associated with the heterogeneity in the polymer properties of plastic waste streams, which could hinder the full potential of recycling due to the lack of a consistent feedstock. Here, this study assessed how an additional sorting step of recycled HDPE and PP streams, separating them into two categories based on the previous application, impacts the recycled polymer properties, such as physical, molecular, and thermal. It was demonstrated that manually separating HDPE articles previously processed by extrusion blow molding (EBM) or injection molding (IM) and PP articles by thermoforming (TF) or IM could yield recycled resins with more consistent properties, considering the significant differences between them. This highlights that an additional sorting step would allow recyclers to target more premium or currently unattainable plastic processing applications with postconsumer recycled (PCR) resins, which could significantly promote an increase in plastic recycling rates. Nevertheless, the development of new technologies is needed to automate this extra sorting step, as with the increase in scale manual sortation could not be feasible and cost-effective, reducing the attractiveness of using PCR resins in comparison to virgin ones.

36 MATERIALS SCIENCE↗

Polyethylene Upcycling to Diacids Using Acid-Only Activation

There is a pressing need to develop plastic recycling technologies. Chemical upcycling converts low-value waste plastics into higher-value products. Here, polyethylene (PE) upcycling is accomplished by using acid-only activation of PE (PEAA), thus eliminating costly and toxic organic solvents. Acid mixtures of chlorosulfuric acid (CSA) and sulfuric acid (SA) were used to effectively sulfonate PE, allowing for subsequent facile depolymerization. Molecular deconstruction of sulfonated PE using H 2 O 2 in the presence of an Fe(III) catalyst achieved molar yields of C 2 –C 4 diacids exceeding 40% (based on estimates of acids generated from sulfonates). The sulfonation step using PEAA is hypothesized to follow a shrinking core mechanism (SCM), in which PE particles quickly reach a saturated state in the outer sulfonated layer as CSA diffuses radially inward. This proposed mechanism is supported by the fact that, regardless of the extent of sulfonation, similar molar yields of products and ratios of liberated carbon to sulfur are observed. Modeling and experimentation show that deviations from the SCM occur by lowering the Damköhler number (Da) or increasing CSA solubility in PE. In both cases, CSA diffusion is enhanced, which favors kinetically limited sulfonation.

36 MATERIALS SCIENCE↗

Spectroscopic Signatures of Phonon Character in Molecular Electron Spin Relaxation

Spin–lattice relaxation constitutes a key challenge for the development of quantum technologies, as it destroys superpositions in molecular quantum bits (qubits) and magnetic memory in single molecule magnets (SMMs). Gaining mechanistic insight into the spin relaxation process has proven challenging owing to a lack of spectroscopic observables and contradictions among theoretical models. Here, we use pulse electron paramagnetic resonance (EPR) to profile changes in spin relaxation rates (T 1 ) as a function of both temperature and magnetic field orientation, forming a two-dimensional data matrix. For randomly oriented powder samples, spin relaxation anisotropy changes dramatically with temperature, delineating multiple regimes of relaxation processes for each Cu(II) molecule studied. We show that traditional T 1 fitting approaches cannot reliably extract this information. Single-crystal T 1 anisotropy experiments reveal a surprising change in spin relaxation symmetry between these two regimes. We interpret this switch through the concept of a spin relaxation tensor, enabling discrimination between delocalized lattice phonons and localized molecular vibrations in the two relaxation regimes. Variable-temperature T 1 anisotropy thus provides a unique spectroscopic method to interrogate the character of nuclear motions causing spin relaxation and the loss of quantum information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Symmetry-mediated quantum coherence of W 5+ spins in an oxygen-deficient double perovskite

Elucidating the factors limiting quantum coherence in real materials is essential to the development of quantum technologies. Here we report a strategic approach to determine the effect of lattice dynamics on spin coherence lifetimes using oxygen deficient double perovskites as host materials. In addition to obtaining millisecond T 1 spin-lattice lifetimes at T ~ 10 K, measurable quantum superpositions were observed up to room temperature. We determine that T 2 enhancement in Sr 2 CaWO 6-δ over previously studied Ba 2 CaWO 6-δ is caused by a dynamically-driven increase in effective site symmetry around the dominant paramagnetic site, assigned as W 5+ via electron paramagnetic resonance spectroscopy. Further, a combination of experimental and computational techniques enabled quantification of the relative strength of spin-phonon coupling of each phonon mode. This analysis demonstrates the effect of thermodynamics and site symmetry on the spin lifetimes of W 5+ paramagnetic defects, an important step in the process of reducing decoherence to produce longer-lived qubits.

36 MATERIALS SCIENCE↗

Attosecond control and measurement of chiral photoionization dynamics

Many chirality-sensitive light–matter interactions are governed by chiral electron dynamics. Therefore, the development of advanced technologies making use of chiral phenomena would critically benefit from measuring and controlling chiral electron dynamics on their natural attosecond timescales. Such endeavours have so far been hampered by the lack of characterized circularly polarized attosecond pulses, an obstacle that has recently been overcome. Here we introduce chiroptical spectroscopy with attosecond pulses and demonstrate attosecond coherent control over photoelectron circular dichroism (PECD), as well as the measurement of chiral asymmetries in the forward–backward and angle-resolved photoionization delays of chiral molecules. We show that co-rotating attosecond and near-infrared (IR) pulses can nearly double the PECD and even change its sign compared with single-photon ionization. We demonstrate that chiral photoionization delays depend on both polar and azimuthal angles of photoemission in the light-propagation frame, requiring 3D momentum resolution. We measure forward–backward chiral-sensitive delays of up to 60 as and polar-angle-resolved photoionization delays of up to 240 as, which include an asymmetry of about 60 as originating from chirality in the continuum–continuum transitions. Attosecond chiroptical spectroscopy opens the door to quantitatively understanding and controlling the dynamics of chiral molecules on the electronic timescale.

Atomic and molecular interactions with photons↗

Low-cost iron trichloride cathode for all-solid-state lithium-ion batteries

The dominant chemistries of lithium-ion batteries on the market today still rely on flammable organic liquid electrolytes and cathodes containing scarce metals, such as cobalt or nickel, raising safety, cost and environmental concerns. Here we show a FeCl 3 cathode that costs as little as 1% of the cost of a LiCoO 2 cathode or 2% of a LiFePO 4 cathode. Once coupled with a solid halide electrolyte and a lithium-indium (Li–In) alloy anode, it enables all-solid-state lithium-ion batteries without any liquid components. Notably, FeCl 3 exhibits two flat voltage plateaux between 3.5 and 3.8 V versus Li + /Li, and the solid cell retains 83% of its initial capacity after 1,000 cycles with an average Coulombic efficiency of 99.95%. Combined neutron diffraction and X-ray absorption spectroscopy characterizations reveal a Li-ion (de)intercalation mechanism together with a Fe 2+ /Fe 3+ redox process. Further, our work provides a promising avenue for developing sustainable battery technologies with a favourable balance of performance, cost and safety.

25 ENERGY STORAGE↗

Entanglement properties of SU(2) gauge theory

Understanding how isolated quantum systems thermalize is central to both fundamental physics and the development of quantum technologies. In this Perspective, we present recent and new results on thermalization in nonabelian gauge theory from exact real-time simulations of two-dimensional lattice models. We discuss tests of the eigenstate thermalization hypothesis, entanglement entropy dynamics, the absence of persistent non-thermal states, spectral signatures, and measures of quantum complexity. Our new results include a two-step thermalization process in localized regions and the role of higher gauge field representations. These findings suggest that thermalization in gauge theories may offer a test case for quantum advantage.

information theory and computation↗

Machine learning prediction of enzyme optimum pH

The relationship between pH and enzyme catalytic activity, especially the optimal pH (pH opt ) at which enzymes function, is critical for biotechnological applications. Hence, computational methods to predict pH opt will enhance enzyme discovery and design by facilitating accurate identification of enzymes that function optimally at specific pH levels, and by elucidating sequence-function relationships. Here, in this study, we proposed and evaluated various machine learning methods for predicting pH opt , conducting extensive hyperparameter optimization and training over 11,000 model instances. Our results demonstrate that models utilizing language model embeddings markedly outperform other methods in predicting pHopt. We present EpHod, the best-performing model, to predict pHopt, making it publicly available to researchers. From sequence data, EpHod directly learns structural and biophysical features that relate to pH opt , including proximity of residues to the catalytic centre and the accessibility of solvent molecules. Overall, EpHod presents a promising advancement in pH opt prediction and will potentially speed up the development of enzyme technologies.

97 MATHEMATICS AND COMPUTING↗