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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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Rheo–Electric Foundations and Engineering of Carbon Slurry Flow Electrodes

Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.

25 ENERGY STORAGE↗

TuFF internal WRAP for Rapid Pipeline Repair (TuFF iWRAP)

The goal of “TuFF internal WRAP for Rapid Pipeline Repair” (TuFF iWRAP) program was to develop a novel material system and placement process to fabricate structural pipe within the existing deteriorated pipelines without disruption of gas delivery. The team (University of Delaware – Center for Composite Materials (UD-CCM) and Plitzie Inc.) addressed this challenge by developing a new material feedstock and pipe in pipe (PIP) repair strategy. This allows the potential for significant cost reduction and has minimum operational impact on gas customers. The new robotic based placement design allows discontinuous placement of pipe sections creating a stand-alone structural liner within the legacy pipeline without the need for pipe shutdown. Here, the material is supplied using a tethered material feeding system and is placed and UV cured with the internal Wound Rapid Automated Placement (iWRAP) system. This provides maximum placement efficiency capable of traversing 90 angle bends in 12-inch pipe and overall design customization to meet pipe repair requirements (e.g., variable wall thickness, bridging gaps, etc.). UV-curable fiber reinforced composite material has been optimized to meet structural performance and placement/cure times. Superior strength and fatigue life has been demonstrated by improving fiber-matrix adhesion using new fiber sizing for UV resins. Rapid cure approaches using new liner and resins have been evaluated with industry. The appropriate design of the section joints has been developed and tested. We estimate coating time to be ~100 hours per mile enabling typical pipe repair within 1 week.

03 NATURAL GAS↗

Air‐Ice‐Ocean Coupling During a Strong Mid‐Winter Cyclone: Observing Coupled Dynamic Interactions Across Scales

Abstract Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air‐ice‐ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid‐winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post‐cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low‐level jet (LLJ) behind the trailing cold front and changing wind directions between the warm‐sector LLJ and post cold‐frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice‐ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.

Meteorology & Atmospheric Sciences↗

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗

Structure and sequence evolution in the pennycress ( Thlaspi arvense ) pangenome

Eukaryotic genomes harbor many forms of variation, including nucleotide diversity and structural polymorphisms, which experience natural selection and contribute to genome evolution and biodiversity. Harnessing this variation for agriculture hinges on our ability to detect, quantify, catalog, and deploy genetic diversity. Here, we explore seven complete genomes of the emerging biofuel crop pennycress ( Thlaspi arvense ) drawn from across the species' current genetic diversity to catalog variation in genome structure and content. Across this new pangenome resource, we find contrasting evolutionary modes in different genomic zones. Gene-poor, repeat-rich pericentromeric regions experience frequent rearrangements, including repeated centromere repositioning. By contrast, conserved gene-dense chromosome arms maintain large-scale synteny across accessions even in fast-evolving NOD-like receptor immune genes, where microsynteny breaks down across species, but gene cluster positioning macrosynteny is maintained. Our findings highlight that multiple elements of the genome experience dynamic evolution that conserves functional content on the chromosome scale but allows repositioning and presence–absence variation on a local scale. This diversity is invisible to classical reference-based strategies and highlights the strength and utility of pangenomic resources. These results provide a valuable case study of rapid genomic structural evolution within a species and powerful resources for crop development in an emerging biofuel crop.

Thlaspi arvense↗

Microstructure characteristics of LPBF&HIP fabricated graded composite transition joint between ferritic steel and austenitic stainless steel

Graded composite transition joints (GCTJs) offer a promising alternative to conventional dissimilar metal welds (DMWs) by enabling smooth compositional and microstructural transitions. However, GCTJs fabricated solely through additive manufacturing (AM) face challenges such as heat accumulation, complex parameter control, and elemental segregation. In this study, we propose a novel approach that relies on AM to design a spatially graded structure in one alloy and then employs hot isostatic pressing (HIP) as a diffusion bonding method to join it with a second alloy. Here, this method combines the flexibility of AM with the powder net-shaping advantage of HIP. Specifically, a series of closely packed austenitic stainless steel 304 conical structures were printed using laser powder bed fusion (LPBF) and then combined with ferritic steel P91 powder via HIP. By using electron backscatter diffraction (EBSD), electron probe microanalysis (EPMA), and transmission electron microscopy (TEM) techniques, the microstructure characteristics of the GCTJ of 304&P91, especially the interdiffusion zone (IDZ), have been systematically investigated. The microstructure at the interface transitions from austenite-ferrite (A+F) to austenite-martensite-ferrite (A+M+F), and finally to martensite-ferrite (M+F) due to diffusion. Additionally, the diffusion width between 304 and P91 increases with the volume fraction of P91. This unique design also ensures a gradual transition in both hardness and thermal expansion coefficient from 304 to P91, thereby enabling a smooth gradient in functional properties. Overall, this study proposes a novel approach for fabricating GCTJs and contributes to advancing design concepts in the field of dissimilar metal joining.

Additively manufacturing (AM)↗

BaCu 4/3 Si 2/3 P 2 and BaCu 2–( x + y ) Zn x Si y P 2 : Expanding the Semiconducting Landscape in the ThCr 2 Si 2 -Type Family

ThCr 2 Si 2 -type layered materials are a large family of compounds with applications ranging from thermoelectricity to magnetism, with the vast majority of the members exhibiting metallic behavior. Here, in this study, we synthesized a new group of materials with Cu-Si and Cu-Zn-Si square nets with the general formula BaCu 1.33 Si 0.67 P 2 and BaCu 2–(x+y) Zn x Si y P 2 (0 ≤ x ≤ 0.9; 0.3 ≤ y ≤ 0.7). Several synthesized compounds are charge-balanced semiconductors, which are rare in the ThCr 2 Si 2 family. All the reported compounds crystallize in the ThCr 2 Si 2 -type tetragonal I4/mmm space group, with Cu/Zn/Si jointly occupying the same 4d crystallographic site. In the Zn-free composition, BaCu 1.33 Si 0.67 P 2 , Ba, and P each occupy a single crystallographic site. The introduction of Zn results in the expansion of the unit cell and splitting the Ba atomic sites along the [001] direction. Such structural displacement of the Ba atoms was confirmed by the heat capacity measurements. Band structure and density-of-states calculations on ordered hypothetical structural models reveal either a small bandgap (∼0.2 eV) or semimetallic band structures. The compounds reported here exhibit high Seebeck coefficients and ultralow thermal conductivity, making them promising candidates for the development of thermoelectric materials.

crystal structure↗

Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models

Purpose To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)'s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.Methods We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANNs) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.Results The optimal ANN for SimCRC had 4 hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had 1 hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 h for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.Conclusions Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, such as the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating 3 realistic CRC individual-level models using a Bayesian approach.

artificial neural networks↗

Atacama Cosmology Telescope DR6 and DESI: Structure growth measurements from the cross-correlation of DESI legacy imaging galaxies and CMB lensing from ACT DR6 and 𝑃⁢𝑙⁢𝑎⁢𝑛⁢𝑐⁢𝑘 PR4

We measure the growth of cosmic density fluctuations on large scales and across the redshift range 0.3 < 𝑧 < 0.8 through galaxy clustering and the cross-correlation of the ACT data release 6 cosmic microwave background (CMB) lensing map and galaxies from the Dark Energy Spectroscopic Instrument Legacy Survey, using three galaxy samples spanning the redshifts of 0.3 ≲ 𝑧 ≲ 0.45, 0.45 ≲ 𝑧 ≲ 0.6, 0.6 ≲ 𝑧 ≲ 0.8. We adopt a scale cut where nonlinear effects are negligible, so that the cosmological constraints are derived from the linear regime. We determine the amplitude of matter fluctuations over all three redshift bins using Atacama Cosmology Telescope (ACT) data alone to be 𝑆 8 ≡ 𝜎 8 ⁢(Ω 𝑚 /0.3) 0.5 =0.772 ± 0.040 in a joint analysis combining the three redshift bins and ACT lensing alone. Using a combination of ACT and Planck data we obtain 𝑆 8 = 0.765 ± 0.032. The lowest redshift bin used is the least constraining and exhibits a ∼2⁢𝜎 tension with the other redshift bins; thus we also report constraints excluding the first redshift bin, giving 𝑆 8 = 0.785 ± 0.033 for the combination of ACT and Planck. This result is in excellent agreement at the 0.3⁢𝜎 level with measurements from galaxy lensing, but is 1.8⁢𝜎 lower than predictions based on Planck primary CMB data. Understanding whether this hint of discrepancy in the growth of structure at low redshifts arises from a fluctuation, from systematics in data, or from new physics is a high priority for forthcoming CMB lensing and galaxy cross-correlation analyses.

cosmic microwave background↗

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗

Design and Analysis of an Integrated Additively Manufactured Test Article for Plasma-Facing Components

Current plasma-facing components (PFCs) used in helium-cooled divertor modules are complex structures with tungsten tile, steel sleeve components, and cartridges, all assembled in a helium-cooled multiple jet (HEMJ) structure. The goal of this project is to simplify the complex PFC design using additive manufacturing techniques to create a single integrated tungsten test article. Apart from the flexibility this opens up in exploring a wide array of geometries for the article, having a single integrated article significantly reduces the number of joints and parts in the article, thus reducing chances of leaks. A process called electron beam melting has shown to produce very high-density samples and unique geometries, enabling HEMJ or similar designs. To validate and optimize this novel design, the model underwent a series of computational fluid dynamics and finite element analysis simulations to replicate steady-state heat flux in the divertors. The simulations presented in this study consider a steady-state base heat flux of 5 MW/m 2 , with water serving as the coolant. Future research will explore the use of helium as a coolant, simulate edge-localized-mode conditions, and include experimental validation. Since 3D-printed tungsten is anisotropic, the build direction versus build plane of the article are taken into consideration for the test article strength. Because of the high operating temperatures and low ductility of tungsten, thermal creep and brittle fracture are important failure mechanisms to consider. In conclusion, the cap is evaluated with various flow velocities and nozzle diameters, and an optimal design choice is made for which this cap will survive the divertor conditions with a conservative safety margin.

Divertor↗

Atacama Cosmology Telescope DR6 and DESI: Structure growth measurements from the cross-correlation of DESI legacy imaging galaxies and CMB lensing from ACT DR6 and P l a n c k PR4

We measure the growth of cosmic density fluctuations on large scales and across the redshift range 0.3 < z < 0.8 through galaxy clustering and the cross-correlation of the ACT data release 6 cosmic microwave background (CMB) lensing map and galaxies from the Dark Energy Spectroscopic Instrument Legacy Survey, using three galaxy samples spanning the redshifts of 0.3 ≲ z ≲ 0.45 , 0.45 ≲ z ≲ 0.6 , 0.6 ≲ z ≲ 0.8 . We adopt a scale cut where nonlinear effects are negligible, so that the cosmological constraints are derived from the linear regime. We determine the amplitude of matter fluctuations over all three redshift bins using Atacama Cosmology Telescope (ACT) data alone to be S 8 ≡ σ 8 ( Ω m / 0.3 ) 0.5 = 0.772 ± 0.040 in a joint analysis combining the three redshift bins and ACT lensing alone. Using a combination of ACT and Planck data we obtain S 8 = 0.765 ± 0.032 . The lowest redshift bin used is the least constraining and exhibits a ∼ 2 σ tension with the other redshift bins; thus we also report constraints excluding the first redshift bin, giving S 8 = 0.785 ± 0.033 for the combination of ACT and Planck. This result is in excellent agreement at the 0.3 σ level with measurements from galaxy lensing, but is 1.8 σ lower than predictions based on Planck primary CMB data. Understanding whether this hint of discrepancy in the growth of structure at low redshifts arises from a fluctuation, from systematics in data, or from new physics is a high priority for forthcoming CMB lensing and galaxy cross-correlation analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Final Technical Report for U.S.-Japan Hadronic Physics Exchange Program for Studies of Hadron Structure and QCD

Nuclear physics explores the fundamental properties of matter -- how protons and neutrons emerge as quantum systems of elementary particles, how they form the atomic nuclei, and how they give rise to the wide variety of phenomena and applications at biological, technical, and astronomical scales. It is a global scientific effort centered around large-scale experimental user facilities (particle accelerators and detectors), advanced theoretical methods and concepts, and computational techniques and resources. Exchange of knowledge and ideas, scientific collaboration, and workforce development on a global scale are essential for the future of the field. The nuclear physics program envisaged in the 2023 DOE/NSF NSAC Long-Range Plan and pursued at the U.S. National Labs has strong synergies with programs at other facilities worldwide and will realize significant benefits from international collaboration. Nuclear physics is also recognized for promoting international cooperation in the broadest sense through joint construction and operation of experimental equipment, personal contacts between scientists, and education and training. The U.S.-Japan Hadronic Physics Exchange Program (USJPHE) supported collaborative scientific research in hadronic physics and quantum chromodynamics. USJHPE focused on subject areas related to the programs at current and future experimental facilities in the U.S.\ and Japan and supported both experimental and theoretical studies. USJHPE particularly aimed to realize synergies between the hadronic physics programs at Jefferson Lab 12 GeV and J-PARC resulting from the complementarity of electromagnetic and hadronic probes in the multi-GeV energy range. Subject areas of common interest included the quark-gluon structure of hadrons and nuclei, meson and baryon spectroscopy, strangeness and hypernuclear physics, and other related topics. USJHPE also supported research in hadronic physics and nuclear-physics-enabled tests of fundamental symmetries related to the programs at Brookhaven National Lab, Fermilab, KEK, Spring-8, and university-based facilities in the U.S. and Japan. USJHPE especially promoted collaboration between the U.S. and Japanese nuclear physics communities in developing the physics program and instrumentation for the future Electron-Ion Collider. USJHPE was intended to provide travel grants to U.S.-based scientists (primary institutional affiliation with a U.S.\ university, national laboratory, or other research center) to visit Japanese institutions and conduct collaborative research there. The program supported senior researchers, postdoctoral fellows, and students. Continuing the setup of the preceding grant period, J-PARC served as the Japanese “hub” for U.S. physicists for short- and long-term visits, and JLab served as the corresponding U.S. “hub”. The program was officially managed through the U. of Connecticut in Storrs, CT. Support for Japanese physicists visiting the U.S. was provided through funds from Japanese funding agencies. The USJHPE program promoted the scientific exchange and the collaborative spirit in hadronic physics between the two countries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dark energy survey year 3 results: Cosmological constraints from cluster abundances, weak lensing, and galaxy clustering

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the Λ⁢CDM model. This work presents the first set of cosmological constraints derived with ∼16,000 optically selected redMaPPer clusters across nearly 5000 deg 2 using DES year 3 datasets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3 × 2⁢pt), ensuring direct comparability with the DES-Y3 3 × 2⁢pt analysis. Here, we obtain constraints of 𝑆 8 = 0.864 ± 0.035 and Ω m = $0.26⁢5^{+0.019}_{−0.031}$ from the cluster-based data vector. We find that cluster constraints and 3 × 2⁢pt constraints are consistent under the Λ⁢CDM model with a posterior predictive distribution (PPD) value of 0.53. The consistency between clusters and 3 × 2⁢pt provides a stringent test of Λ⁢CDM across different mass and spatial scales. Jointly analyzing clusters with 3 × 2⁢pt further improves cosmological constraints, yielding 𝑆 8 = $0.81⁢1^{+0.022}_{−0.020}$ and Ω m = $0.29⁢4^{+0.022}_{−0.033}$, a 24% improvement in the Ω m − 𝑆 8 figure of merit over 3 × 2⁢pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of 0.6, significantly reducing previous 𝑆 8 tension claims. Finally, combining DES 3 × 2⁢pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of ∑𝑚 𝜈 < 0.26 eV at 95% confidence under the Λ⁢CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming stage-IV surveys such as LSST, Euclid, and Roman.

Abbott, T. M. C. [NSF’s National Optical-Infrared ↗

Cross-Domain Reasoning for Neuromorphic Model Design

Designing performant neuromorphic models requires reasoning across neuroscience, neuromorphic computing, and machine learning, making it a natural target for cross-domain hypothesis generation. Our primary contribution is a multi-corpus knowledge graph spanning all three domains, which we show substantially increases cross-domain retrieval novelty over single-corpus baselines. We additionally introduce NeuKReAct, an agentic reasoning framework that iteratively retrieves from this graph and synthesizes design hypotheses via a step-by-step blackboard architecture, enabling structured compartmentalization of design decisions. Lastly, we introduce an execution head that translates hypotheses into structured design documents and runnable code. We evaluate novelty using a combinatorial creativity metric that measures cross-domain retrieval distance across the citation graph. Our results confirm that corpus breadth is the dominant driver of novelty. Moreover, we highlight a concrete instance of the novelty-utility tradeoff within NeuKReAct, underscoring a need for joint creativity evaluation, balancing both novelty and utility.

Ramavarapu, Vikram [ORNL] (ORCID:0009000188757213)↗

Plant sulfate transporter protein sequences for phylogenetic analysis

Sulfur is an essential macronutrient that supports plant growth, development, and responses to environmental stress. Sulfate is the predominant inorganic form of sulfur in soils, and its uptake by roots and translocation to shoots are facilitated by the sulfate transporter (SULTR) family of proteins. Although the first plant SULTR gene was identified nearly three decades ago, several subfamily members, particularly those in the expansive and angiosperm-specific SULTR3 group, remain poorly characterized. To support comprehensive phylogenetic and sequence-based analyses, we compiled a curated dataset of 262 SULTR protein sequences from 22 plant species spanning the evolutionary breadth of land plants. This collection includes representatives from two basal lineages, two early-divergent angiosperms, six monocots, and ten dicots. All sequences were extracted from genome assemblies available in Phytozome v13 (Joint Genome Institute) and manually curated, with cross-referencing to additional databases such as NCBI when needed. This dataset provides a valuable resource for reconstructing the evolutionary history of the SULTR family, with particular emphasis on the diversification of SULTR3 transporters in flowering plants. This resource may also support functional annotation, comparative genomics, and structural modeling of sulfate transport proteins.

CBI↗

Vapor-Phase Heteroatom Incorporation into Semiconductive Molecular-Scale Magic-Size Clusters

Magic-size metal chalcogenide clusters of molecular size exhibit well-defined structure and unique properties that might be further expanded with the incorporation or substitution of a second metal. Here, we report the postmodification of magic-size clusters synthesized in polymer thin films via exposure to volatile metal organic precursors commonly utilized for atomic layer deposition. Exposure of In 6 S 6 (CH 3 ) 6 clusters to dimethylcadmium results in exposure-dependent incorporation of Cd 2+ , which extends the optical absorbance of the clusters into the visible spectrum. The mechanism for Cd 2+ incorporation is consistent with Cd 2+ replacement of In 3+ that includes methyl ligand removal to maintain charge neutrality. Even for clusters embedded in a polymer matrix, ligand loss leads to sintering and transformation into larger nanoscale aggregates with zinc blende-type structure. The extent of Cd incorporation can be modulated by varying the process temperature and volatile metal organic exposure as well as the choice of volatile metal organic precursor. A computational thermodynamic analysis of heteroatom incorporation for several metals and chemistries reveals that both the stability of the substituted cluster and the favorability of reaction byproducts jointly determine the favorability of cation incorporation.

atomic layer deposition↗