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Results for “LaI”
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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Explainable machine learning of the underlying physics of high-energy particle collisions
We present an implementation of an explainable and physics-aware machine learning model capable of inferring the underlying physics of high-energy particle collisions using the information encoded in the energy-momentum four-vectors of the final state particles. We demonstrate the proof-of-concept of our White Box AI approach using a Generative Adversarial Network (GAN) which learns from a DGLAP-based parton shower Monte Carlo event generator. The constrained generator network architecture mimics the structure of a parton shower exhibiting similarities with Recurrent Neural Networks (RNNs). We show, for the first time, that our approach leads to a network that is able to learn not only the final distribution of particles, but also the underlying parton branching mechanism, i.e. the Altarelli-Parisi splitting function, the ordering variable of the shower, and the scaling behavior. While the current work is focused on perturbative physics of the parton shower, we foresee a broad range of applications of our framework to areas that are currently difficult to address from first principles in QCD. Examples include nonperturbative and collective effects, factorization breaking and the modification of the parton shower in heavy-ion, and electron-nucleus collisions.
Precision studies of QCD in the low energy domain of the EIC
This White Paper aims at highlighting the important benefits in the science reach of the EIC. High luminosity operation is generally desirable, as it enables producing and harvesting scientific results in a shorter time period. Furthermore, it becomes crucial for programs that would require many months or even years of operation at lower luminosity.
Recent trends in all-organic polymer dielectrics for high-temperature electrostatic energy storage capacitors
Electrostatic energy storage (EES) capacitors are critical for renewable energy and high-power systems, driving the search for dielectric materials that combine superior electrical insulation, mechanical flexibility, low density, cost-effectiveness, and processability. Polymer-based dielectrics have emerged as leading candidates, particularly for high electric field applications. However, conventional polymers often fail to meet the demands of high-temperature environments due to increased electrical conductivity and reduced discharged energy density at elevated temperatures, resulting in energy loss and reduced performance. High glass transition temperature (T g) polymers show promise but require further optimization to enhance their energy storage capabilities under thermal and electrical stress. This review provides a comprehensive update on recent advancements in high-T g polymer-based dielectrics for EES capacitors, focusing on both intrinsic polymers and all-organic composites. It outlines key design principles, critical performance parameters, and innovative strategies—such as nanofiller doping, layered architectures, physical blending, and chemical crosslinking—to improve electrical, thermal, and mechanical properties. The review also highlights emerging trends, including the integration of machine learning algorithms to explore novel polymer structures and expand the chemical design space. By bridging the gap between academic research and industrial application, this review aims to accelerate the development of next-generation dielectric materials capable of balancing multiple performance metrics for high-temperature EES capacitors.
Quantitative analysis of Cu XANES spectra using linear combination fitting of binary mixtures simulated by FEFF9
We report x-ray absorption near edge structure (XANES) is a powerful tool to probe the fingerprint of local structures, and when coupled with X-ray microscopy, the small spot size enables one to probe very specific regions of interest in a device or material, e.g. interfaces/bulk, different grains, good/bad electrical areas. In this work, we investigate the use of linear combination fitting (LCF) of XANES spectra for the particular case of Cu doping in CdTe. We show that the experimental data seem to be accurately represented by standards of Cu 2 Te and its substoichiometric counterpart, Cu 1.43 Te. We use Cu in CdTe as a case study to evaluate the accuracy of linear combination fitting using simulated standards, given that experimental standards for certain phases (e.g. Cu 1.43 Te) or defect structures (e.g. vacancies) cannot be readily obtained. We discuss how spectral features of the FEFF9-simulated standards, fitting ranges, and noise levels all dictate the accuracy of this type of analysis. We show that the greater the spectral difference between the two standards, the better the LCF is able to differentiate between the two structures and to tolerate experimental noise. Finally, we estimate the error of the fitted weights for different spectral features and noise levels and propose a framework to study local structures semi-quantitatively by using binary mixtures of FEFF9-simulated standards.
Chemical looping based ammonia production - A promising pathway for production of the noncarbon fuel
Ammonia, primarily made with Haber–Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However, the undesired characteristics of the process, including high carbon footprint, necessitate alternative ammonia synthesis methods, and among them is chemical looping ammonia production (CLAP) that uses nitrogen carrier materials and operates at atmospheric pressure with high product selectivity and energy efficiency. To date, neither a systematic review nor a perspective in nitrogen carriers and CLAP has been reported in the critical area. So, this work not only assesses the previous results of CLAP but also provides perspectives towards the future of CLAP. It classifies, characterizes, and holistically analyzes the fundamentally different CLAP pathways and discusses the ways of further improving the CLAP performance with the assistance of plasma technology and artificial intelligence (AI).
Search for CP violation and measurement of branching fractions and decay asymmetry parameters for Λ$^+_c$ → Λ h + and Λ$^+_c$ → Σ 0 h + ( h = K, π )
Here, we report a study of Λ$^+_c$ → Λ h + and Λ$^+_c$ → Σ 0 h + ( h = K, π ) decays based on a data sample of 980 fb -1 collected with the Belle detector at the KEKB energy-asymmetric e + e - collider. The first results of direct CP asymmetry in two-body singly Cabibbo-suppressed (SCS) decays of charmed baryons are measured, A$^{dir}_{CP}(Λ^+_{c} → ΛK^{+})$ = +0.021 ± 0.026 ± 0.001 and A$^{dir}_{CP}(Λ^+_{c} → Σ^{0}K^{+})$ = +0.025 ± 0.054 ± 0.004. We also make the most precise measurement of the decay asymmetry parameters (α) for the four modes of interest and search for CP violation via the α-induced CP asymmetry (A$^α_{CP}$ ). We measure A$^α_{CP}$ ($Λ^+_{c} → ΛK^{+}$) = -0.023 ± 0.086 ± 0.071 and A$^α_{CP}$ ($Λ^+_{c} → Σ^{0}K^{+}$) = +0.08 ± 0.35 ± 0.14, which are the first A$^α_{CP}$ results for SCS decays of charmed baryons. We search for Λ -hyperon CP violation in $Λ^+_{c}$ → (Λ, Σ 0 )π + and find A$^α_{CP}$(Λ → pπ - ) = +0.013 ± 0.007 ± 0.011 . This is the first time that hyperon CP violation has been measured via Cabibbo-favored charm decays. No evidence of baryon CP violation is found. We also obtain the most precise branching fractions for two SCS Λ$^+_c$ decays, $\mathscr{B}$($Λ^+_{c} → ΛK^{+}$) = (6.57 ± 0.17 ± 0.11 ± 0.35) x 10 -4 and $\mathscr{B}$($Λ^+_{c} → Σ^{0}K^{+}$) = (3.58 ± 0.19 ±0.06 ±0.19) x 10 -4 . The first uncertainties are statistical and the second systematic, while the third uncertainties come from the uncertainties on the world average branching fractions of $Λ^+_{c}$ → (Λ, Σ 0 )π + .
Achieving superior carbon transfer efficiency and pH control using membrane carbonation with a wide range of CO 2 contents for the coccolithophore Emiliania huxleyi
The economic viability of microalgal-derived products relies on rapid CO 2 transfer in a cost-effective manner. Many industrial gas streams contain concentrated CO 2 that, if converted to useful products, would lower greenhouse gas emissions and valorize the wasted CO 2 . Membrane carbonation (MC) uses non-porous hollow-fiber gas-transfer membranes to deliver CO 2 without bubble formation, which makes it possible to achieve a high carbon-transfer efficiency (CTE). However, inert gasses in the industrial streams (e.g., N 2 , O 2 , and H 2 O) can significantly lower the CO 2 -delivery rate. The means to overcome the buildup of inert gases in the membrane lumen is to manage the distal end of the membranes to sweep out inert gases while not wasting significant CO 2 . A MC-venting strategy was evaluated for CO 2 inputs from 5% to 100%. Abiotic tests using a restricted exit flow could achieve >95% CTE abiotic for industrial CO 2 streams. When integrated with semi-continuous cultivation of a marine coccolithophore, Emiliania huxleyi , CO 2 delivery and venting were on-demand based on a pH set points and pH-actuated feed and venting valves. MC using the venting strategy achieved 100% CTE biotic when delivering 100% and 50% CO 2 , which was better than 50% CTE biotic obtained from pH-controlled sparging of 100% CO 2 -sparging. E. huxleyi consistently fixed ~80% of the delivered CO 2 into biomass, and the remaining ~20% to calcite coccoliths. Finally, the compact size of MC modules, stable pH control, and no shear forces from bubble agitation during the CO 2 delivery made MC an ideal match for cultivation of coccolithophores, which are sensitive to shear forces and pH fluctuations.
Aerosol iron speciation and seasonal variation of iron oxidation state over the western Antarctic Peninsula
The iron (Fe) speciation and oxidation state have been considered critical factors affecting Fe solubility in the atmosphere and bioavailability in the surface ocean. In this study, elemental composition and Fe speciation in aerosol samples collected at the Palmer Station in the West Antarctic Peninsula were determined using synchrotron-based X-ray fluorescence (XRF) and X-ray Absorption Near-Edge Structure (XANES) spectroscopy. The elemental composition of coarse-mode (>1 mu m) Fe-containing particles suggests that the region's crustal emission is the primary source of aerosol Fe. The Fe minerals in these aerosol particles were predominantly hematite and biotite, but minor fractions of pyrite and ilmenite were observed as well. The Fe oxidation state showed an evident seasonal variation. Further, the Fe(II) content accounted for 71% of the total Fe in the austral summer, while this fraction dropped to 60% in the austral winter. Multivariate linear models involving meteorological parameters suggested that the wind speed, relative humidity, and solar irradiance were the factors that significantly controlled the percentage of Fe(II) in the austral summer. On the contrary, no relationship was found between these factors and the Fe(II) percentage in the austral winter, suggesting that atmospheric photoreduction and regional dust emission were limited. Moreover, the snow depth was significantly (p < 0.05) correlated with the aerosol Fe concentration, confirming the limiting effect of snow/ice cover on the regional dust emission. Given that the Antarctic Peninsula has experienced rapid warming during recent decades, the ice-free areas in the Antarctic Peninsula may act as potential dust sources.
Controls and variability of soil respiration temperature sensitivity across China
Understanding the temperature sensitivity (Q 10 ) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q 10 , a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q 10 at regional scales. Here, therefore, we used a machine learning approach to predict Q 10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q 10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q 10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q 10 . These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q 10 , which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.
Spatial variability of aerosol iron mineralogy and oxidation states over the Arctic Ocean
The mineralogy and oxidation state of aerosol iron (Fe) play important roles in controlling aerosol Fe solubility and consequent bioavailability in seawater. In this study, the spatial variability of Fe mineralogy and oxidation states in aerosols collected during the US GEOTRACES Western Arctic cruise (GN01) were determined using synchrotronbased X-ray absorption near edge structure (XANES) spectroscopy. Both Fe(II) minerals (biotite, ilmenite) and Fe (III) minerals (ferrihydrite, hematite, Fe(III) phosphate) were found in these samples. However, aerosol Fe mineralogy and solubility observed during this cruise varied spatially and can be grouped into three clusters based on the air masses that affected aerosols collected in different regions: (1) biotite-enriched particles (87 % biotite, 13 % hematite) with the air masses passing over Alaska, showing relatively low Fe solubility (4.0 +/- 1.7 %); (2) ferrihydrite-enriched particles (82 % ferrihydrite, 18 % ilmenite) collected in the remote Arctic air, showing relatively high Fe solubility (9.6 +/- 3.3 %); (3) the fresh dust derived from North America and Siberia, primarily dominated by hematite (41 % hematite, 25 % Fe(III) phosphate, 20 % biotite, 13 % ferrihydrite), showing relatively low Fe solubility (5.1 +/- 3.5). A significant positive correlation was found between Fe oxidation state and Fe fractional solubility, suggesting that long-range transport could modify iron (hydr) oxide such as ferrihydrite through atmospheric processing, influencing aerosol Fe solubility and consequently Fe bioavailability in the remote Arctic Ocean.
Origin of strain softening in a nanograined Al alloy
Here, one-step and multi-step nanoindentation experiments were conducted to investigate the mechanical response of an Al-Mg-Li alloy. Opposite to the strain hardening effect observed in the coarse-grained (CG) alloy, the nanograined (NG) alloy exhibits strain softening. Compared with multi-step nanoindentation experiments, the ultralow dislocation density and the grain boundary (GB) segregation promote a higher stress level during one-step nanoindentation experiments. Residual perfect dislocations induced by a previous loading and unloading during multi-step nanoindentation experiments lower the stress required for further plastic deformation. In addition, the storage of partial dislocations also serves to render plastic flow to commence at lower stresses. This work provides new insights for the fabrication and property optimization of NG alloys.
Formation and coarsening of epitaxially-supported metal nanoclusters
This mini-review describes developments over the last ~30 years in characterizing the nucleation & growth of epitaxially-supported metal nanoclusters (NCs) or islands during vapor deposition, as well as their post-deposition coarsening. A beyond-mean-field treatment for homogeneous nucleation & growth corrects the deficiencies of traditional treatments in describing, e.g., the island size distribution, but also necessitates consideration of the spatial distribution of islands and their capture zones. We discuss advances in modeling capabilities, including those based upon on an ab-initio level treatment of periphery diffusion kinetics, for description of the non-equilibrium growth shapes of these NCs, focusing on 2D NCs. For post-deposition coarsening of arrays of NCs, there is generally a competition between Ostwald Ripening (OR) and Smoluchowski Ripening (SR). SR is also known as Particle Migration & Coalescence. For 2D NCs in homoepitaxial systems, conventional OR is observed on pristine fcc(111) surfaces, dramatically enhanced OR in the presence of even trace amounts of chalcogens for Cu(111) and Ag(111), and anomalous OR on anisotropic fcc(110) surfaces. The unexpected discovery of SR for fcc(100) homoepitaxial systems prompted extensive analysis of the underlying diffusivities of 2D NCs as a function of size, as well as of NC coalescence dynamics. A comprehensive understanding of these processes is now available. Self-assembly of 3D NCs during deposition, issues related to heterogeneous nucleation, directed assembly, NC growth structure selection, and coarsening are addressed. Finally, for SR of 3D epitaxial NCs, recent insights into the size-dependence of diffusivity are described.
Nitrogen fixation in Pampinifervens , a new species-rich genus of Aquificaceae that inhabits a wide pH range in terrestrial hot springs
Members of the Aquificota play important roles in hydrogen, sulfur, and carbon cycles in geothermal systems as ubiquitous and abundant chemolithoautotrophs; however, their roles in the nitrogen cycle are poorly defined. Here, we show that Aquificaceae isolate T-2 T from Tengchong, China, fixes nitrogen based on growth with dinitrogen as the sole nitrogen source and incorporation of 15 N atoms when grown with 15 N 2 . We further show evidence that suggests its nitrogen fixation (nif) genes are transcribed in situ in a nearby spring. We propose the name Pampinifervens diazotrophicum gen. et sp. nov., with strain T-2 T (= JCM 35475 T = DSM 116324 T ) as the nomenclatural type. Its close relative designated Pampinifervens florentissimum sp. nov. T-8 T (= CGMC 1.5214 T = JCM 33569 T ) does not fix nitrogen but respires nitrate. Analysis of 104 metagenome-assembled genomes from 84 metagenomes allowed us to circumscribe the genus Pampinifervens and identify at least 16 sympatric Pampinifervens species that dominate the Aquificaceae populations in diverse hot springs in southwest China, with distinct species globally. Analysis of these Pampinifervens genomes revealed variable presence of nif and denitrification genes and frequent gene loss and horizontal transfer. Genes for pH homeostasis were also present in Pampinifervens genomes, with a proliferation in species from Tengchong, consistent with the wide pH growth range of both Pampinifervens isolates and the prevalence of Pampinifervens in both alkaline and acidic springs. The dynamic evolution of nif and denitrification genes, along with pH homeostasis genes, may facilitate the diversification of Pampinifervens into diverse springs with different nitrogen availability.
Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism
Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. Here, these frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit–host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.
Changes in atmospheric circulation amplify extreme snowfall fueled by Arctic sea ice loss over high-latitude land
Arctic sea-ice retreat has been linked to increased winter precipitation and heavy snowfall over land, likely due to a combination of enhanced evaporation from ice-free Arctic marginal seas (AMS) and changes in atmospheric circulation. However, their relative roles and contributions remain uncertain. Here, we show that a greater proportion of AMS evaporative moisture reached high-latitude land during the cold seasons from 1980–1989 to 2012–2021. Atmospheric circulation changes added an additional 13 % increase in the AMS moisture contribution, accounting for 11 % of the total increase in AMS-sourced land precipitation. Notably, 46 % of the increase in AMS-sourced extreme snowfall is attributed to circulation-driven landward moisture transport, representing an 84 % increase beyond the effect of enhanced AMS evaporation alone. Further analysis indicates that both the rise in Arctic moisture and the atmospheric circulation shifts are primarily driven by anthropogenic forcing. These findings highlight how atmospheric circulation changes amplify extreme snowfall fueled by AMS evaporation, underscoring the synergistic effects of Arctic sea ice loss and circulation change on high-latitude winter precipitation.