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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 289 records · Page 16

The Heterogeneous Integration of Electronic Components

Heterogeneous integration (HI) of electronics components is broadly recognized as a powerful and crucial enabler for the continued growth of computing and communication. From 2010 onwards, the value of HI is increasingly visible in the advanced packaging used in artificial intelligence, high-performance computing, smartphones and communications product implementations. In this Perspective, we argue that HI is crucial to semiconductors and more broadly to the continued evolution of computing and communications. We use leading-edge advanced packaging examples to represent the value, advancements and opportunities for HI. To succeed, it is critical to develop comprehensive HI roadmaps that inform collaborations across the design, manufacturing and reliability spectrum between systems architects, packaging and semiconductor technologists to common goals. Although this article does not provide a full roadmap, we instead detail additional parameters for artificial intelligence, smartphone and other cellular communication devices, and their constituent building blocks including interconnects, power electronics, photonics, thermal management, reliability, modelling and co-design, to foster greater collaboration opportunities among academia, research laboratories and industry.

42 ENGINEERING↗

Accurate and reliable thermochemistry by data analysis of complex thermochemical networks using Active Thermochemical Tables: the case of glycine thermochemistry

Active Thermochemical Tables (ATcT) were successfully used to resolve the existing inconsistencies related to the thermochemistry of glycine, based on statistically analyzing and solving a thermochemical network that includes >3350 chemical species interconnected by nearly 35 000 thermochemically-relevant determinations from experiment and high-level theory. Here, the current ATcT results for the 298.15 K enthalpies of formation are −394.70 ± 0.55 kJ mol −1 for gas phase glycine, −528.37 ± 0.20 kJ mol −1 for solid α-glycine, −528.05 ± 0.22 kJ mol −1 for β-glycine, −528.64 ± 0.23 kJ mol −1 for γ-glycine, −514.22 ± 0.20 kJ mol −1 for aqueous undissociated glycine, and −470.09 ± 0.20 kJ mol −1 for fully dissociated aqueous glycine at infinite dilution. In addition, a new set of thermophysical properties of gas phase glycine was obtained from a fully corrected nonrigid rotor anharmonic oscillator (NRRAO) partition function, which includes all conformers. Corresponding sets of thermophysical properties of α-, β-, and γ-glycine are also presented.

Active Thermochemical Tables↗

Enhanced upconversion and photoconductive nanocomposites of lanthanide-doped nanoparticles functionalized with low-vibrational-energy inorganic ligands

Upconverting nanoparticles (UCNPs) convert near-infrared (IR) light into higher-energy visible light, allowing them to be used in applications such as biological imaging, nano-thermometry, and photodetection. It is well known that the upconversion luminescent efficiency of UCNPs can be enhanced by using a host material with low phonon energies, but the use of low-vibrational-energy inorganic ligands and non-epitaxial shells has been relatively underexplored. Here, we investigate the functionalization of lanthanide-doped NaYF4 UCNPs with low-vibrational-energy Sn2S64- ligands. Raman spectroscopy and elemental mapping are employed to confirm the binding of Sn2S64- ligands to UCNPs. This binding enhances upconversion efficiencies up to a factor of 16, consistent with an increase in the luminescent lifetimes of the lanthanide ions. Annealing Sn2S64--capped UCNPs results in the formation of a nanocomposite comprised of UCNPs embedded within an interconnected matrix of SnS2, enabling each UCNP to be electrically accessible through the semiconducting SnS2 matrix. This facilitates the integration of UCNPs into electronic devices, which we demonstrate through the fabrication of a UCNP-SnS2 photodetector that detects UV and near-IR light. Our findings show the promise of using inorganic capping agents to enhance the properties of UCNPs while facilitating their integration into optoelectronic devices.

Pan, Jia-Ahn↗

Signal propagation in reversible digital mechanics

Digital mechanics explores information processing through binary, mechanical circuits. This work demonstrates a flexural, mechanical integrated circuit (m-IC) that achieves reversible, non-reciprocal signal propagation through integrated AND logic and memory. Our approach exploits sequential bistable transitions with symmetric energy wells, tunable stiffness, impedance matching, and AND gate non-linearity, to enable signal propagation, repeatability, and reversibility. We present a generalized model of logic kinematics and energetics, validated experimentally, to study energy flows, quantify energetic limits, and identify operating regimes for reversible logic. Macro-scale experiments confirm propagation dynamics, and new fabrication methods extend the architecture to micro-scale devices. By achieving controlled, reversible signal transmission across interconnected logic and memory, this work establishes a scalable platform for robust mechanical computing and adaptive sensing.

Johnson, Hilary A. [Lawrence Livermore National La↗

Genetic control of morphological transitions in a coacervating protein template

Nature routinely exploits liquid–liquid phase separation (LLPS) of proteins to control the assembly and mineralization of hybrid materials. Here, we show that fusion of the Car9 silica-binding peptide to an elastin-like polypeptide (ELP) yields temperature- and sequence-programmable soft matter templates for the synthesis of silicified architectures ranging in size from nanometers to micrometers. Specifically, we demonstrate unprecedented control over the diameter of silica nanoparticles (SiNP) in the 30–60 nm range with 4 nm precision, show that a single arginine residue (R4) in the Car9 sequence underpins the transition from micelles to proteinosomes, and find that substitutions in other basic residues modulate electrostatic repulsion and solvation to enable access to kinetically trapped species. These structures, which include interconnected micelles, small (∼200 nm) and large (>5 µm) vesicles, are readily visualized by SEM imaging following silicification. Molecular dynamics (MD) simulations and AlphaFold predictions reveal that mutations in positively charged residues alter interfacial packing, hydration, and conformational freedom of the silica-binding segments. Overall, our results establish sequence and thermal energy as synergistic levers for morphological control across length scales using solid-binding ELPs and establish mineralization as a powerful tool to visualize the structure of dynamic soft matter assemblies.

hierarchy↗

Amorphous zinc–molybdenum–sulfide chalcogel as a long-cycle, high-capacity electrode for lithium-ion batteries

The inherent limitations of intercalation-based electrodes in lithium-ion batteries have prompted the search for alternative materials with higher specific capacities and robust electrochemical stability. Sulfur-based electrodes, despite their high theoretical capacities (1672 mAh g −1 ), typically suffer from poor cycling performance. In this work, zinc molybdenum polysulfide (Zn x Mo 3 S 13 , 0.5 ≤ x), an amorphous semiconductor chalcogel, exhibits high specific capacity and excellent cycling stability. Synchrotron X-ray pair distribution function and extended X-ray absorption fine structure analyses reveal a short-range atomic structure comprising Mo–Mo, M–S (M = Mo, Zn), and S–S bonding motifs. The coordination environment of Mo and S closely resembles that of Mo 3 S 13 clusters, interconnected via S–S bridges and Zn 2+ cations. The Li/Zn x Mo 3 S 13 cell delivers an initial discharge capacity of 844 mAh g −1 at C/3, and retains 386.2 mAh g −1 after 1000 cycles with an average coulombic efficiency of 99.99%. The distribution of relaxation times analysis confirms the formation of a stable solid electrolyte interphase, which underpins the cell's long-term stability. In conclusion, this outstanding performance is attributed to the synergistic effects of the chalcogel's unique amorphous framework, semiconductive character, Zn-mediated polysulfide anchoring, and structural resilience, positioning Zn x Mo 3 S 13 chalcogel among the most durable pure metal sulfide cathodes reported for next-generation LIBs.

36 MATERIALS SCIENCE↗

Challenging conventional assumptions in PV: a high-throughput open-air approach to low-cost perovskite module production

Perovskite solar modules (PSMs) offer a promising pathway to low-cost photovoltaics, yet their commercialization is challenged by manufacturing scalability, device uniformity, additive costs, interlayer complexity, and module stability. This study introduces a comprehensive technoeconomic analysis of single junction PSM's and projections for tandem perovskite-Si modules that integrate all materials and manufacturing steps, module performances, projected lifetimes, and manufacturing costs across scales. Here, we highlight an open-air manufacturing approach to fabricate all active layers of serially interconnected PSMs, including electrodes and charge transport layers, enabling high-throughput production without inert or vacuum environments. The analysis reveals two orders of magnitude throughput enhancement and cost reductions of 24% in all-open-air production, escalating to over 60% at 1 GW factory capacity compared to conventional methods. Levelized cost of energy (LCOE) projections for utility-scale installations over 30 years, accounting for module replacement and recycling, demonstrate the potential to achieve the 2030 US target of $0.03 per kWh with realistic 7–11-year PSM lifetimes, outperforming incumbent silicon-based modules. Neither four terminal (4T) nor two terminal (2T) tandem-Si PSMs improve over single junction perovskite or silicon LCOE regardless of higher efficiencies at any modeled lifetime. Addressing PSM technical challenges with a cost-modeling framework guides commercialization efforts and provides a convincing pathway for challenging incumbent Si-based PV.

14 SOLAR ENERGY↗

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Increased thermal conductivity and decreased electron–phonon coupling factor of the aluminum scandium intermetallic phase (Al 3 Sc) compared to solid solutions

Aluminum scandium alloys and their intermetallic phases have arisen as potential candidates for the next generation of electrical interconnects. Here, in this work, we measure the in-plane thermal conductivity and electron–phonon coupling factor of aluminum scandium alloy thin films deposited at different temperatures, where the temperature is used to control the grain size and volume fraction of the Al 3 Sc intermetallic phase. As the Al 3 Sc intermetallic formation increases with higher deposition temperature, we measure increasing in-plane thermal conductivity and a decrease in the electron–phonon coupling factor, which corresponds to an increase in grain size. Our findings demonstrate the role that chemical ordering from the formation of the intermetallic phase has on thermal transport.

Chemical elements↗

Anomalous transport of multi-species edge plasma with the generalized Hasegawa–Wakatani model and the FLR effects

Anomalous transport of multi-species plasma is considered with the generalized Hasegawa–Wakatani model [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)] further extended to incorporate the Finite Larmor Radius (FLR) effects. By introducing the “associated” enstrophy, it is shown that with no FLR effects (where anomalous transport of all ion species is described as a transport of passive scalars in the turbulent fields of the electrostatic potential and electron density fluctuations) the fluctuating densities of ion species converge to the state where they are linearly proportional to electron density and vorticity fluctuations, which confirm previous numerical findings of [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)]. However, in contrast to the “cold” ion approximation, with the FLR effects included, both the plasma turbulence and the dynamics of all ion species become interconnected. Therefore, for simplicity, the FLR effects in this work were considered only for a small “trace” impurity fraction. It is found that for light (neon) “trace” impurity, the FLR effects reduce both anomalous flux and density fluctuations. However, for heavy (tungsten) “trace” impurity, the FLR effects exhibit non-monotonic impact on anomalous transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast and efficient Sb-based type-II phototransistors integrated on silicon

Increasing the energy efficiency and reducing the footprint of on-chip photodetectors enable dense optical interconnects for emerging computational and sensing applications. While heterojunction phototransistors (HPTs) exhibit high energy efficiency and negligible excess noise factor, their gain-bandwidth product (GBP) has been inferior to that of avalanche photodiodes at low optical powers. Here, we demonstrate that utilizing type-II energy band alignment in an Sb-based HPT results in six times smaller junction capacitance per unit area and a significantly higher GBP at low optical powers. These type-II HPTs were scaled down to 2 μm in diameter and fully integrated with photonic waveguides on silicon. Thanks to their extremely low dark current and high internal gain, these devices exhibit a GBP similar to the best avalanche devices (∼270 GHz) but with one order of magnitude better energy efficiency. Their energy consumption is about 5 fJ/bit at 3.2 Gbps, with an error rate below 10−9 at −25 dBm optical power at 1550 nm. These features suggest new opportunities for creating highly efficient and compact optical receivers based on phototransistors with type-II band alignment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗

Perspectives of active Si photonics devices for data communication and optical sensing

Si photonics has made rapid progress in research and commercialization in the past two decades. While it started with electronic–photonic integration on Si to overcome the interconnect bottleneck in data communications, Si photonics has now greatly expanded into optical sensing, light detection and ranging (LiDAR), optical computing, and microwave/RF photonics applications. From an applied physics point of view, this perspective discusses novel materials and integration schemes of active Si photonics devices for a broad range of applications in data communications, spectrally extended complementary metal–oxide–semiconductor (CMOS) image sensing, as well as 3D imaging for LiDAR systems. We also present a brief outlook of future synergy between Si photonic integrated circuits and Si CMOS image sensors toward ultrahigh capacity optical I/O, ultrafast imaging systems, and ultrahigh sensitivity lab-on-chip molecular biosensing.

electronic band structure↗

Nonstationarity in the global terrestrial water cycle and its interlinkages in the Anthropocene

Climate change and human activities alter the global freshwater cycle, causing nonstationary processes as its distribution shifting over time, yet a comprehensive understanding of these changes remains elusive. Here, we develop a remote sensing–informed terrestrial reanalysis and assess the nonstationarity of and interconnections among global water cycle components from 2003 to 2020. We highlight 20 hotspot regions where terrestrial water storage exhibits strong nonstationarity, impacting 35% of the global population and 45% of the area covered by irrigated agriculture. Emerging long-term trends dominate the most often (48.2%), followed by seasonal shifts (32.8%) and changes in extremes (19%). Notably, in mid-latitudes, this encompasses 34% of Asia and 27% of North America. The patterns of nonstationarity and their dominant types differ across other water cycle components, including precipitation, evapotranspiration, runoff, and gross primary production. These differences also manifest uniquely across hotspot regions, illustrating the intricate ways in which each component responds to climate change and human water management. Our findings emphasize the importance of considering nonstationarity when assessing water cycle information toward the development of strategies for sustainable water resource usage, enhancing resilience to extreme events, and effectively addressing other challenges associated with climate change.

Science & Technology - Other Topics↗

Perpendicular crossing chains enable high mobility in a noncrystalline conjugated polymer

The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphogenesis of spin cycloids in a noncollinear antiferromagnet

Pattern formation in spin systems with continuous-rotational symmetry (CRS) provides a powerful platform to study emergent complex magnetic phases and topological defects in condensed-matter physics. However, its understanding and correlation with unconventional magnetic order along with high-resolution nanoscale imaging are challenging. Here, we employ scanning nitrogen vacancy (NV) magnetometry to unveil the morphogenesis of spin cycloids at both the local and global scales within a single ferroelectric domain of (111)-oriented BiFeO 3 , which is a noncollinear antiferromagnet, resulting in formation of a glassy labyrinthine pattern. We find that the domains of locally oriented cycloids are interconnected by an array of topological defects and exhibit isotropic energy landscape predicted by first-principles calculations. We propose that the CRS of spin-cycloid propagation directions within the (111) drives the formation of the labyrinthine pattern and the associated topological defects such as antiferromagnetic skyrmions. Unexpectedly, reversing the as-grown ferroelectric polarization from [$\overline{1}$ $\overline{1}$ $\overline{1}$] to [111] produces a noncycloidal NV image contrast which ¯ could be attributed to either the emergence of a uniformly magnetized state or a reversal of the cycloid polarity. These findings highlight that (111)-oriented BiFeO 3 is not only important for studying the fascinating subject of pattern formation but could also be utilized as an ideal platform for integrating novel topological defects in the field of antiferromagnetic spintronics.

magnetoelectric↗

Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations

Here, in this work, we introduce a novel method to develop whole system digital twins (DTs) for advanced nuclear reactors. This method treats a complex reactor system as a heterogeneous graph: with the system components as different types of graph nodes and their physical interconnections as edges. Based on the heterogeneous graph, a graph neural network combining graph convolution and temporal node attention is developed as the DT, facilitating a comprehensive understanding of the system's dynamic behavior. By utilizing the System Analysis Module (SAM) code for simulating various operational transients, we develop a graph-based database that trains the DT. This DT is characterized by two primary functions: It can infer the entire system's status using sparse node information, and it can predict the progress of transients based on current and historical system information. Our approach is validated through case studies on the Experimental Breeder Reactor II (EBR-II) system and a generic Fluoride-salt-cooled High-temperature Reactor (gFHR), demonstrating the DT's accuracy in forecasting operational transients. The DT's rapid computation capabilities enhance its potential for supporting advanced reactor operations, offering benefits in intelligent simulation, autonomous control, and anomaly detection, paving the way for improved safety analysis and intelligent component health management for advanced reactor systems and reducing their operations and maintenance cost.

EBR-II↗