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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of Sugarcane Cultivation on C Cycling in Southeastern United States Following Conversion From Grazed Pastures

ABSTRACT The expansion of sugarcane, a tropical high‐yielding feedstock, will likely reshape the Southeastern United States (SE US) bioenergy landscape. However, the sustainability of sugarcane, particularly as it displaces grazed pastures, is highly uncertain. Here, we investigated how pasture conversion to sugarcane in subtropical Florida impacts net ecosystem CO 2 exchange (NEE) and net ecosystem carbon (C) balance (NECB). Measurements were made over three full growth cycles (> 3 years) in sugarcane—plant cane, PC; first ratoon cane, FRC; second ratoon cane, SRC—and in improved (IM) and semi‐native (SN) pastures, which make up ca. 37% of agricultural land in the region. Immediately following conversion, PC was a stronger net source of CO 2 than pastures, indicating the importance of CO 2 losses related to land disturbance. Sugarcane, however, shifted to a strong net sink of CO 2 after first regrowth, and overall sugarcane was a stronger net CO 2 sink than pastures. Both stand age and low water availability during cane emergence and tillering substantially decreased its potential gross CO 2 uptake. Accounting for all C gains and removals (i.e., NECB), greater frequency of burn events and repeated harvest increased removals and overall made sugarcane a stronger C source relative to pastures despite substantial C inputs from the previous land use and a stronger CO 2 sink strength. Time since conversion substantially reduced C losses from sugarcane, and the NECB of SRC was similar to that of IM pasture but lower than that of SN pasture, indicating a rapid shift in the NECB of cane. We conclude that the C‐balance implications following conversion will depend on the proportion of IM versus SN pastures converted to sugarcane. Furthermore, our findings suggest that no‐burn harvest management strategies will be critical to the development of a sustainable bioenergy landscape in SE US.

Gomez‐Casanovas, Nuria↗
DOE OSTI2025

Why is height-dependent mixing observed in stratocumulus clouds?

Recent aircraft measurements in stratocumulus clouds suggest that entrainment mixing is inhomogeneous (IM) near cloud top and homogeneous (HM) within the cloud. However, this proposed height-dependence of mixing transition is uncertain because of artifacts involved in the aircraft measurements. In this study, we use the Explicit Mixing Parcel Model to simulate mixing scenarios in stratocumulus clouds and reconstruct the virtual aircraft measurements to investigate the mixing signature. Results show that, from the aircraft-measurement perspective, the mixing signature always exhibits IM characteristic near cloud top and HM characteristic within cloud, independent of the types of the local entrainment-mixing process. The appearance of the vertical IM-to-HM transition is essentially a collective behavior of multiple parcels sampled at the same height, experiencing distinct entrainment-mixing-evaporation histories. This bulk view of mixing process, which is widely used for aircraft measurements, could lead to misinterpretations of the true mixing mechanism occurring in clouds. Our result underscores the limitations of using aircraft measurements to identify the entrainment-mixing mechanism at the process level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reduktive Eliminierung von Tetraalkylcupraten [Me n Cu(CF 3 ) 4− n ] − ( n =0–4): jenseits einfacher Oxidationsstufen

Abstract In den letzten Jahren haben Organocuprate im Allgemeinen und der Komplex [Cu(CF 3 ) 4 ] − im Besonderen wegen ihrer elektronischen Strukturen erhebliches Interesse auf sich gezogen. Obwohl der Reaktivität dieser Spezies in diesem Zusammenhang eine Schlüsselrolle zukommen dürfte, fand dieser Aspekt bisher nur wenig Beachtung. Wir untersuchen hier systematisch die Reihe der Tetraalkylcuprate [Me n Cu(CF 3 ) 4− n ] − und ihre Gasphasenreaktivität, die sowohl konzertierte reduktive Eliminierungen als auch Radikalverluste umfasst. Mit Hilfe quantenchemischer Rechnungen charakterisieren wir die elektronischen Strukturen der Komplexe und zeigen, wie sie mit der Reaktivität zusammenhängen. Wir finden, dass alle Ionen [Me n Cu(CF 3 ) 4− n ] − invertierte Ligandenfelder aufweisen und dass sich die unterschiedlichen Reaktivitäten der individuellen Komplexe aus dem Zusammenspiel verschiedener Effekte ergeben.

Zimmer, Bastian↗
DOE OSTI2024

Low‐Temperature and High‐Rate Rechargeable Aluminum Batteries Enabled by Ternary Eutectic Electrolytes

Abstract Rechargeable aluminum batteries (RABs) have garnered extensive scientific attention as a promising alternative chemistry due to the inherent advantages associated with aluminum (Al) metal anodes, including their high theoretical capacities, cost‐effectiveness, environmental friendliness, and inherent non‐flammable properties. Nonetheless, the practical energy density of RABs is constrained by the electrolytes that support lower operational voltage windows. Herein, we report a ternary eutectic electrolyte composed of 1‐ethyl‐3‐methylimidazolium chloride ([C 2 C 1 im]Cl):1‐butyl‐3‐methylimidazolium chloride ([C 4 C 1 im]Cl):aluminum chloride (AlCl 3 ) for the application of RABs. The electrolyte exhibits a high operational potential window (~3 V vs. Al/Al 3+ on SS 316) and high ionic conductivity (~8.3 mS cm −1 ) while exhibiting only a low temperature glass transition at −65 °C suitable for all‐climate conditions. Al||graphene nanoplatelets cell delivers a high capacity of ~117 mAh/g, and ~43 mAh/g at a very high current densities of 1 A/g and 5 A/g, respectively. The cells render a reversible capacity of 20 mAh/g at −20 °C and 17 mAh/g at −40 °C, indicating their suitability for operation under extreme environmental conditions. We comprehensively evaluated the design and optimization of carbon paper‐based battery systems. The ternary eutectic electrolyte demonstrates exceptional electrochemical performance, thus signifying its substantial potential for utilization in high‐performance energy storage systems in all climates.

Vadthya, Raju↗
DOE OSTI2025

Interlaboratory comparison of secondary ion mass spectrometry analysis results from the 7th international technical nuclear forensics working group collaborative material exercise

A review and interlaboratory comparison of secondary ion mass spectrometry (SIMS) data obtained by laboratories participating in the International Technical Nuclear Forensics Working Group (ITWG) 7th Collaborative Material Exercise (CMX-7) has been conducted. The analyzed materials were two uranium compounds in powder form and two pieces of uranium metal. The instruments used in this comparison were a small-geometry (SG) SIMS, CAMECA IMS 7f from the Research Centre Rez, and a large-geometry (LG) SIMS, CAMECA IMS 1280 from Los Alamos National Laboratory. Despite the differences in instruments and analytical procedures, e.g., sample preparation, SIMS setups, and data post-processing, there was good agreement for the 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios in the analyzed materials. The main difference was in the precision, which was, as expected, higher for the LG-SIMS. In addition, a comparison between the laboratories was also made for the image processing algorithms applied to raw data acquired in automated particle measurement (APM) mode. In conclusion, the result of this comparison has led to identification of best practices for setting up parameters of the APM software.

and nuclear chemistry↗
DOE OSTI2025

127 Xe quantification method development and intercomparison exercise

Monitoring of the atmosphere for fission products ( 131m Xe, 133m Xe, 133 Xe, and 135 Xe) is performed by various laboratories to detect nuclear explosions. Quantification of 127 Xe is not routinely performed by laboratories measuring atmospheric radioxenon because it is not a fission product. 127 Xe was recently detected by a ground-based beta-gamma air monitoring system. When measured using beta-gamma coincidence detector systems, such as those in use on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), 127 Xe can interfere with the quantification of fission product radioxenon due to overlap of the 127 Xe beta-gamma coincidence signatures with those of fission product radioxenon. Here, this work demonstrates quantification of 127 Xe at different laboratories with different measurement techniques. Production and purification of 127 Xe was performed by neutron activation of enriched 126 Xe. The purified 127 Xe was then split between laboratories, and detection and quantification methods were developed. At Idaho National Laboratory, a quantification method involving high purity germanium detectors was devised that included self-attenuation correction. At AWE, a beta-gamma coincidence counting method, as used in support of the IMS, was modified to enable the measurement and analysis of the 127 Xe samples. Corrections were made for self-attenuation, which showed a strong xenon volume dependency, for some coincidence signatures. The gas sample activity concentration was used as the comparison metric and it showed excellent agreement between the methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Mass spectrometry structural analysis of intrinsically disordered phosphoproteins

Phosphorylation is a ubiquitous protein modification that is known to play important roles in many biological phenomena including cell signaling, the opening and closing of membrane protein channels, and even triggering of amyloid protein aggregation. Despite the effects phosphorylation has on protein function, the impact phosphorylation has on the structure of proteins is not well understood. Here, to determine how phosphorylation affects the structure of proteins, top-down mass spectrometry (TD-MS) and ion mobility-mass spectrometry (IM-MS) were performed on various phosphorylated proteins and their dephosphorylated proteoforms. TD-MS with collision- and electron-based fragmentation techniques was utilized to locate phosphorylation sites on the intrinsically disordered amyloid proteins β-casein and α-synuclein. TD-MS also provided evidence that alkaline phosphatase dephosphorylates β-casein from the N-terminus to the C-terminus. Furthermore, IM-MS of common phosphorylated proteins such as β-casein, α-casein, ovalbumin, and phosvitin indicates that phosphorylation promotes compaction of protein structure in denaturing as well as native conditions. Increases in abundance of more compact conformers are also observed when the disease related amyloid protein α-synuclein is phosphorylated at serine 129. We interpret the increased abundance of more compact conformers when proteins are phosphorylated as evidence that salt bridges form between negatively charged phosphates and positively charged residues, which alters protein structure. Salt bridge formation due to phosphorylation could be a mechanism for regulating protein function and be responsible for many of the phenomena observed in nature.

Amyloid proteins↗
DOE OSTI2026

First measurement of polarized spin-density matrix elements and differential cross sections dσ/dt in ω photoproduction off the proton for 2.7 < Eγ < 5.2 GeV using CLAS at Jefferson Lab

We report on the differential cross sections dσ/dt, the unpolarized spin-density matrix elements ρ 00 0 , ρ 1 − 1 0 , Re ρ 10 0 , and the first extraction of the polarized elements Im ρ 10 3 , Im ρ 1 − 1 3 for the reaction γp → pω using the CLAS spectrometer at Jefferson Laboratory. The ω mesons were detected in their dominant charged decay mode, ω → π + π − π 0 , and all t-dependent results are presented in a fine binning for incident photon energies between 2.73 and 5.16 GeV (corresponding to the center-of-mass energy range W ∈ [ 2.45, 3.25 ] GeV). All matrix elements are first measurements for − t > 0.6 GeV2. Moreover, differential cross sections dσ/d(cos Θ c . m . ω ) and the corresponding angle-dependent unpolarized spin-density matrix elements in the Adair frame are presented for the incident photon energy range 1.56–3.80 GeV (corresponding to W ∈ [ 1.95, 2.83 ] GeV). These new ω photoproduction data are consistent with earlier CLAS results but extend the energy range well beyond the nucleon resonance region into the Regge regime. The comparison with Regge-theory-based model predictions shows that the new data impose more stringent constraints on our understanding of ω photoproduction.

Hu, T.↗
DOE OSTI2025

Structural Changes in Metal Chalcogenide Nanoclusters Associated with Single Heteroatom Incorporation

Atomically precise nanoclusters (NCs) are promising building blocks for designing materials and interfaces with unique properties. By incorporating heteroatoms into the core, the electronic and magnetic properties of NCs can be precisely tuned. To accurately predict these properties, density functional theory (DFT) is often employed, making the rigorous benchmarking of DFT results particularly important. In this study, we present a benchmarking approach based on metal chalcogenide NCs as a model system. We synthesized a series of bimetallic, iron-cobalt chalcogenide NCs [Co 6-x Fe x S 8 (PEt 3 ) 6 ] + (x = 0-6) (PEt = triethyl phosphine) and investigated the effect of heteroatoms in the octahedral metal chalcogenide core on their size and electronic properties. Using ion mobility-mass spectrometry (IM-MS), we observed a gradual increase in the collision cross section (CCS) with an increase in the number of Fe atoms in the core. DFT calculations combined with trajectory method CCS simulations successfully reproduced this trend, revealing that the increase in cluster size is primarily due to changes in metal-ligand bond lengths, while the electronic properties of the core remain largely unchanged. Moreover, this method allowed us to exclude certain multiplicity states of the NCs, as their CCS values were significantly different from those predicted for the lowest-energy structures. Here, this study demonstrates that gas-phase IM-MS is a powerful technique for detecting subtle size differences in atomically precise NCs, which are often challenging to observe using conventional NC characterization methods. Accurate CCS measurements are established as a benchmark for comparison with theoretical calculations. The excellent correspondence between experimental data and theoretical predictions establishes a robust foundation for investigating structural changes of transition metal NCs of interest to a broad range of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

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↗
DOE OSTI2025

A Modified DBC Substrate Improving Thermal Performance for Confined Space Applications

High-power modules use substrates to house the semiconductor device and for electrical insulation. These substrates are constructed with thermally conductive dielectric material sandwiched between two metals to extract heat from semiconductor chips. Thus, the required cooling performance of a power module is linked to the substrate’s thermal performance and can vary based on the substrate technologies. Here, in this study, five substrate technologies were evaluated for space-restricted applications: direct-bonded copper (DBC), an insulated metal substrate (IMS), a thermally annealed pyrolytic graphite (TPG)-based IMS, DBC-based double-sided cooling, and direct-bonded aluminum (DBA) where the heat sink is directly attached without thermal interface materials (TIMs). The finite element (FE) analysis results suggest that the popular DBC substrate has thermal performance better than that of the other substrates for space-constrained applications. To further improve the thermal performance, a modified DBC substrate was proposed where a copper block was added between the semiconductor and the DBC substrate to achieve heat spreading underneath the chip. The modified DBC performance was then compared with the aforementioned substrates and the results showed significant thermal performance improvement. The results were verified with experimental results where the proposed substrate showed 20% more loss handling capability compared to an identical DBC substrate.

42 ENGINEERING↗
DOE OSTI2025

Structural architecture of TolQ-TolR inner membrane protein complex from opportunistic pathogen Acinetobacter baumannii

Gram-negative bacteria harness the proton motive force (PMF) within their inner membrane (IM) to uphold cell envelope integrity, an indispensable aspect for both division and survival. The IM TolQ-TolR complex is the essential part of the Tol-Pal system, serving as a conduit for PMF energy transfer to the outer membrane. Here we present cryo–electron microscopy reconstructions ofAcinetobacter baumanniiTolQ in apo and TolR-bound forms at atomic resolution. The apo TolQ configuration manifests as a symmetric pentameric pore, featuring a transmembrane funnel leading toward a cytoplasmic chamber. In contrast, the TolQ-TolR complex assumes a proton nonpermeable stance, characterized by the TolQ pentamer’s flexure to accommodate the TolR dimer, where two protomers undergo a translation-based relationship. Our structure-guided analysis and simulations support the rotor-stator mechanism of action, wherein the rotation of the TolQ pentamer harmonizes with the TolR protomers’ interplay. These findings broaden our mechanistic comprehension of molecular stator units empowering critical functions within the Gram-negative bacterial cell envelope.

Science & Technology - Other Topics↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2025

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Binding Free Energy Analysis of Colicin D, E3 and E8 to Their Respective Cognate Immunity Proteins Using Computational Simulations

Colicins are antimicrobial proteins produced by bacteria for the purpose of destroying neighboring bacteria. Colicin activity is neutralized by a specific cognate immunity protein in order to protect the host. This study investigates the structural and binding mechanisms underlying the interaction of colicin-D, -E3 and -E8 to their respective immunity proteins (ImD, Im3 and Im8) using structure prediction, molecular dynamics (MD) simulations and MM-PBSA approach of free energy calculations. High-confidence colicin-immunity (Col-Im) complex structures predicted using AlphaFold2 were subjected to MD simulations of 150 ns with GROMACS and were analyzed for the binding free energy calculation using gmx_MMPBSA. Results showed that the complex of Col_E3-Im3 exhibited the most favorable binding free energy, driven by strong van der Waals and electrostatic interactions. Col_D-ImD and Col_E8-Im8 also showed the favorable binding. Electrostatics and hydrogen bonding emerged as a key factor driving binding and stability, while polar solvation acted as a destabilizing factor across all systems. These outcomes provide an understanding of the molecular mechanisms of Col-Im systems, with potential applications for developing natural antimicrobials for food safety.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Global Carbon Budget 2025

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions (E FOS ) are based on energy and cement production data. Emissions from land-use change (E LUC ) are estimated by bookkeeping models based on land-use data. The global atmospheric CO 2 growth rate (G ATM ) is computed from changes in concentration measured at surface stations. The global net uptake of CO 2 by the ocean (S OCEAN ) is estimated with global ocean biogeochemistry models and observation-based fCO 2 -products. The global net uptake of CO 2 by the land (S LAND ) is estimated with dynamic global vegetation models. Additional lines of evidence are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. This year, we introduced corrections on the E LUC , S OCEAN and S LAND estimates. The sum of all sources and sinks results in the carbon budget imbalance (B IM ), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ± 1σ. For the year 2024, E FOS increased by 1.1 % relative to 2023, with fossil emissions at 10.3 ± 0.5 GtC yr −1 (including the cement carbonation sink, 0.2 GtC yr −1 ), E LUC was 1.3 ± 0.7 GtC yr −1 , for total anthropogenic CO 2 emissions of 11.6 ± 0.9 GtC yr −1 (42.4 ± 3.2 GtCO2 yr −1 ). Also, for 2024, G ATM was 7.9 ± 0.2 GtC yr−1 (3.73 ± 0.1 ppm yr −1 ), 2.2 GtC above the 2023 growth rate. SOCEAN was 3.4 ± 0.4 GtC yr −1 and S LAND was 1.9 ± 1.1 GtC yr −1 , leaving a large negative B IM (−1.7 GtC yr −1 ), suggesting that the total sink or G ATM is strongly overestimated in 2024. The global atmospheric CO 2 concentration averaged over 2024 reached 422.8 ± 0.1 ppm. Preliminary data for 2025 suggest an increase in E FOS relative to 2024 of +1.0 % (0.2 % to 1.7 %) globally, and atmospheric CO 2 concentration increasing by 2.1 ppm reaching 425.6 ppm, 53 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr −1 persist for the representation of annual to decadal variability in CO 2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2025 (Friedlingstein et al., 2025c).

54 ENVIRONMENTAL SCIENCES↗