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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 55 records · Page 3

Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters

Title (20 word): Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters Introduction (120 words): Transport of metal ions across the aqueous-organic phase boundary is an essential step in a hydrometallurgical nuclear fuel reprocessing strategy. The study of transport agents for nuclear fuel elements is imperative to guide the design of ligands that boost the separation efficiency of the recovery process from fission products. However, limited studies have been made on the chemistry of these transport agents when complexing with transuranic elements in gas-phase where all surrounding factors are essentially excluded. This work investigates the reagent ligand complexations to transuranic and other metals and their dissociations in the gas phase. Comparisons are made between 4f and 5f elements and between ligands. Methods (120 words): (N,N-diisobutylcarbamoylmethyl)phenyloctylphosphine oxide (CMPO) and N,N,N',N'-tetraoctyldiglycolamide (TODGA) have been selected to complex with metal nitrates. The actinide americium and lanthanides neodymium, samarium, and europium were investigated as part of this work. The lanthanides were selected to act as size and electron configuration analogues of the minor actinides. Metal complexes with two ligands and two nitrates ([M(NO3)2(CMPO)2]+, for example) are studied in Bruker micrOTOF-Q II mass spectrometer equipped with collision-induced dissociation capability. The comparisons of the mass spectra are made in groups of homogenous ligands and mixed TODGA-CMPO ligands clusters. Comparisons are also made based on the complexed metals (Am and lanthanides). Preliminary data (300 words): Collision-induced dissociation mass spectrometry data are collected on two ligands complexed with metal nitrates where the two ligands are homogenous, with (CMPO)2 or (TODGA)2, or heterogeneous, with (TODGA)(CMPO). Several fragmentation patterns are observed among complexes with the CMPO ligand whereas the TODGA ligand commonly dissociates intact from the complex. Most of the metal complexes exhibit similar fragmentation patterns, but there are a few notable deviations in fragmentation patterns between the Am and Ln-bearing complexes. For the [M(CMPO)2(NO3)2]+ complexes, the initial loss of nitrate in the form of nitric acid is observed in all four complexes. However, [Am(CMPO)2(NO3)2]+ exhibits an additional fragmentation not found in the lanthanide complexes. Also, a significantly different ratio of the second nitric acid loss is found in the Am complex. These deviations may indicate the different interaction behaviors between actinides and lanthanides. The [M(TODGA)2(NO3)2]+ complexes exhibit the fragmentation as the loss of one TODGA ligand as an intact form and the loss of nitrate as nitric acid. The Am complex exhibits an additional fragmentation after losing the TOGDA ligand, which is not observed among the Ln complexes. The heterogeneous [M(TODGA)(CMPO)(NO3)2]+ complexes exhibit both similarities and differences between the Am and Ln complexes. For example, the heterogenous Am complex does not exhibit the loss of an intact TODGA ligand while all three Ln complexes do. This indicates that TODGA may bind more strongly to Am than Ln. Additionally, the intensity of the loss of CMPO ligand (as partially or whole) is found to be significantly larger than that of the loss of TODGA (as partially of whole) indicating that TODGA is bound to the metal significantly stronger than CMPO. Planned computational analysis will help understand the deviation in fragmentation behaviors between americium and lanthanide metal centers, or between TODGA and CMPO ligands. Novel aspect (20 words): Gas-phase actinide and lanthanide complex formation and fragmentation provide insight into the coordination environment differences of f-element metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational methods in solution-based plastics purification

Plastic waste can be recycled into resins with near-virgin properties by solution-based purification processes that selectively dissolve polymers, remove contaminants, or detach printing residues. Here, in this review, we examine computational methods for predicting the behavior governing solution-based plastic purification, motivated by the vast polymer–solvent–contaminant compositional space. We discuss thermodynamic and machine learning methods for predicting polymer–solvent and polymer–contaminant interaction and review physics-based molecular dynamics simulations that resolve molecular-scale phenomena within polymer matrices inaccessible to screening methods. We highlight how these methods have informed experimental design for dissolution-based recycling and solvent-based contaminant removal. Finally, we discuss the prospective role of agentic AI in integrating these computational tools with real-time sorting data to adapt purification conditions to the compositional variability of real post-consumer feedstocks. This review charts a path toward computationally guided solution-based purification workflows that can respond to the complexity inherent in plastic waste streams.

Altamimi, Ali [Univ. of Wisconsin, Madison, WI (Un↗

Chaotrope-Based Approach for Rapid In Vitro Assembly and Loading of Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are proteinaceous organelles that self-assemble into selectively permeable shells that encapsulate enzymatic cargo. BMCs enhance catalytic pathways by reducing crosstalk among metabolites, preventing harmful intermediates from leaking into the cytosol and increasing reaction efficiency via enzyme colocalization. The intrinsic properties of BMCs make them attractive for biotechnological engineering. However, in vivo expression methods for shell synthesis have significant drawbacks that limit the potential design space for these nanocompartments. Here, we describe the development of an efficient and rapid method for the in vitro assembly of BMC shells from their protein building blocks. Our method enables large-scale construction of BMC shells by utilizing urea as a chaotropic agent to control self-assembly and provides an approach for encapsulation of both biotic and abiotic cargo under a broad range of reaction conditions. We demonstrate an enhanced level of control over the assembly of BMC shells in vitro and expand the design parameter space for engineering BMC systems with specialized and enhanced catalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Dual Environment Aging on Flexible Polyurethane Based Adhesive

Abstract Environmental degradation of adhesives naturally increases with the intensity of the ambient weathering agents involved. During service life, these materials are never subjected to a constant environmental loading. Real-time applications expose the material to multiple weather conditions, ranging from dry to humid or fully wet conditions. While some understanding exists about aging environments in isolation, we intend to investigate the effect of multiple environments on the constitutive behavior of the materials in question. The extent of damage can be accessed by analyzing the changes in constitutive behavior and toughness of aged material. Therefore, this aging experiment was designed around two-way aging regimes involving combinations of thermo-oxidation, hydrolytic and hygrothermal aging environments. We selected a polyurethane based flexible adhesive which is commonly used in the automotive industry as a glass sealant. The aged specimens were subjected to uniaxial tensile tests, and variation in material toughness and constitutive behavior was analyzed to ascertain the mechanics involved in the case of each environmental exposure. We outlined how different environments affect the material in isolation and how they interact with other weathering conditions. This study will help better understand and model the damage mechanics involved in exposure to multiple environmental conditions.

Shaafaey, Mamoon↗

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗

Structure of BTK kinase domain with the second-generation inhibitors acalabrutinib and tirabrutinib

Bruton’s tyrosine kinase (BTK) is the target of the therapeutic agent, Ibrutinib, that treats chronic lymphocyte leukemia (CLL), mantle cell lymphoma (MCL) and other B cell malignancies. Ibrutinib is a first in class, covalent BTK inhibitor that limits B-cell survival and proliferation. Designing new inhibitors of BTK has been an important objective for advancing development of improved therapeutic agents against cancer and autoimmune disorders. Based on the success of Ibrutinib, several second-generation irreversible BTK inhibitors have been developed that exhibit fewer off-target effects. However, the binding-mode and their interaction with Btk have not been experimentally determined and evaluated at atomic resolution. Here we determined the first crystal structure of the BTK kinase domain in complex with acalabrutinib. In addition, we report a structure of the BTK/tirabrutinib complex and compare these structures with previously solved structures. The structures provide insight in the superior selectivity reported for acalabrutinb and guide future BTK inhibitor development.

60 APPLIED LIFE SCIENCES↗

Antioxidant-induced transformations of a metal-acid hydrocracking catalyst in the deconstruction of polyethylene waste

Plastics are ideal for numerous applications, as driven by the development of complex formulations containing various additives to improve performance and processability. Unfortunately, chemical valorization strategies (e.g., catalytic deconstruction) often can be challenged by the presence of small-molecule additives, and quantification of the impact of these molecular constituents on upcycling processes remains elusive. Here, this dearth of information restricts catalyst design efforts to combine the robustness and performance necessary to improve plastics circularity. In this communication, we describe a systematic study of common plastics additives—phenolic antioxidants, and we quantify the relationship between additive content and deconstruction yields of high-density polyethylene (HDPE) over a platinum on tungstated zirconium (Pt/WO 3 /ZrO 2 ) hydrocracking catalyst. In the simplest case of a base (antioxidant- and slip agent-containing) HDPE resin versus a pure (additive-stripped) HDPE polymer, a two-fold decrease in the yield of gas and liquid products is noted for base HDPE resin. Furthermore, both antioxidant chemistry and concentration strongly impact conversion and individual product selectivities. Using infrared spectroscopy, we determine that antioxidants change the effective ratio of metal to acid sites (i.e., metal-acid balance) through reactions of phenols and/or other functional groups (e.g., acids, esters) with catalyst active sites. Overall, this work demonstrates the impact of one common set of additives on plastics deconstruction, and the analysis herein provides a blueprint for quantitatively assessing the effects of additives on plastics deconstruction processes and for evaluating the development of more robust catalytic strategies or more tolerable additive formulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis of selective TRPM7 inhibition by the anticancer agent CCT128930

TRP channels are implicated in various diseases, but high structural similarity between them makes selective pharmacological modulation challenging. Here, we study the molecular mechanism underlying specific inhibition of the TRPM7 channel, which is essential for cancer cell proliferation, by the anticancer agent CCT128930 (CCT). Using cryo-EM, functional analysis, and MD simulations, we show that CCT binds to a vanilloid-like (VL) site, stabilizing TRPM7 in the closed non-conducting state. Similar to other allosteric inhibitors of TRPM7, NS8593 and VER155008, binding of CCT is accompanied by displacement of a lipid that resides in the VL site in the apo condition. Moreover, we demonstrate the principal role of several residues in the VL site enabling CCT to inhibit TRPM7 without impacting the homologous TRPM6 channel. Hence, our results uncover the central role of the VL site for the selective interaction of TRPM7 with small molecules that can be explored in future drug design.

59 BASIC BIOLOGICAL SCIENCES↗

Design and Gas Separation Performance of Imidazolium Poly(ILs) Containing Multivalent Imidazolium Fillers and Crosslinking Agents

This work introduces a series of vinyl-imidazolium-based polyelectrolyte composites, which were structurally modified via impregnation with multivalent imidazolium-benzene ionic liquids (ILs) or crosslinked with novel cationic crosslinkers which possess internal imidazolium cations and vinylimidazolium cations at the periphery. A set of eight [C4vim][Tf2N]-based membranes were prepared via UV-initiated free radical polymerization, including four composites containing di-, tri-, tetra-, and hexa-imidazolium benzene ILs and four crosslinked derivatives which utilized tri- and tetra- vinylimidazolium benzene crosslinking agents. Structural and functional characterizations were performed, and pure gas permeation data were collected to better understand the effects of “free” ILs dispersed in the polymeric matrix versus integrated ionic crosslinks on the transport behaviors of these thin films. These imidazolium PIL:IL composites exhibited moderately high CO2 permeabilities (~20–40 Barrer), a 4–7× increase relative to corresponding neat PIL, with excellent selectivities against N2 or CH4. The addition of imidazolium-benzene fillers with increased imidazolium content were shown to correspondingly enhance CO2 solubility (di- < tri- < tetra- < hexa-), with the [C4vim][Tf2N]: [Hexa(Im+)Benz ][Tf2N] composite showing the highest CO2 permeability (PCO2 = 38.4 Barrer), while maintaining modest selectivities (αCO2/CH4 = 20.2, αCO2/N2 = 23.6). Additionally, these metrics were similarly improved with the integration of more ionic content bonded to the polymeric matrix; increased PCO2 with increased wt% of the tri- and tetra-vinylimidazolium benzene crosslinking agent was observed. This study demonstrates the intriguing interactions and effects of ionic additives or crosslinkers within a PIL matrix, revealing the potential for the tuning of the properties and transport behaviors of ionic polymers using ionic liquid-inspired small molecules.

36 MATERIALS SCIENCE↗

Osprey Framework v0.2.2

The Alpha Berkeley Framework is a software architecture for building agentic AI systems that coordinate multi-step workflows in scientific and industrial environments. It is based on a plan-first orchestration model, where natural language requests are translated into execution plans with explicit dependencies and optional human approval. The framework includes capability classification, which selects relevant tools on a per-task basis to keep orchestration efficient as the number of available tools grows. It incorporates task extraction methods that compress conversational context and integrate external resources such as databases, APIs, and knowledge bases into structured, machine-readable tasks. Execution is supported by modular services with checkpointing, artifact management, and error handling, allowing workflows to be paused, inspected, and resumed. The system is designed for deployment in production environments, supporting both local and containerized execution as well as integration with HPC clusters. Interfaces include command-line tools, browser-based workflows, and containerized services. The framework has been demonstrated in tutorial examples and deployed at the Advanced Light Source, where it coordinates accelerator control and analysis workflows.

Hellert, Thorsten [Lawrence Berkeley National Labo↗

HPC4Mfg with ACS

Distillation in the chemical industry accounts for roughly 10% of energy use in the U.S. While porous mass separating agents (MSAs) appear capable of achieving the same separations for a fraction of the energy, the fundamental lack of a well-understood relationship between the behavior of fluid mixtures confined in MSA pores and the selectivity of MSA-based processes presents a major barrier to their widespread industrial application. This work is the first study to systematically and self-consistently explore a range of parameters describing various molecule-material interactions in MSA-based separations. Through high performance computing (HPC), this study has yielded a fundamental understanding of the influence of confined fluid behavior on selectivity. The results also serve as a knowledge base for subsequent investigations needed to transform the framework for rational design of MSA-based separation processes. This will significantly reduce the energy required for separations central to chemical manufacturing.

36 MATERIALS SCIENCE↗

Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems

This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.

Visweswara Sathanur, Arun↗

Quantum model learning agent: characterisation of quantum systems through machine learning

Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distil empirically. Here, we report an algorithm—the quantum model learning agent (QMLA)—to reverse engineer Hamiltonian descriptions of a target system. We test the performance of QMLA on a number of simulated experiments, demonstrating several mechanisms for the design of candidate Hamiltonian models and simultaneously entertaining numerous hypotheses about the nature of the physical interactions governing the system under study. QMLA is shown to identify the true model in the majority of instances, when provided with limited a priori information, and control of the experimental setup. Our protocol can explore Ising, Heisenberg and Hubbard families of models in parallel, reliably identifying the family which best describes the system dynamics. We demonstrate QMLA operating on large model spaces by incorporating a genetic algorithm to formulate new hypothetical models. The selection of models whose features propagate to the next generation is based upon an objective function inspired by the Elo rating scheme, typically used to rate competitors in games such as chess and football. In all instances, our protocol finds models that exhibit F 1 score ≥ 0.88 when compared with the true model, and it precisely identifies the true model in 72% of cases, whilst exploring a space of over 250 000 potential models. By testing which interactions actually occur in the target system, QMLA is a viable tool for both the exploration of fundamental physics and the characterisation and calibration of quantum devices.

97 MATHEMATICS AND COMPUTING↗

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗

Development and Implementation of a New AI-Based Tool to Support Fast Reactor Software Model Generation and Validation

This report summarizes FY26 work to develop Maggie, an artificial intelligence-based assistant designed to support software model generation and validation activities for fast reactor analysis codes. The project established a modular, code-agnostic software architecture that separates reusable agent capabilities from code-specific knowledge and tools, with initial implementation focused on the FRP-supported fast reactor safety analysis code SAS4A/SASSYS1 (SAS). A curated SAS-specific knowledge base was assembled from the code manual, training materials, historical analysis reports, and representative input files, and was integrated through retrieval-augmented generation to ground Maggie’s responses in authoritative sources. Maggie was deployed on the internal Argonne network, where it demonstrated practical user-facing capability as a chatbot for answering natural language questions about SAS and retrieving relevant technical information. Demonstration cases also showed that Maggie can generate useful snippets of SAS input for selected modeling tasks, while highlighting current limitations in reliability and consistency for more complex input generation tasks. Overall, the FY26 effort established the technical foundation for an AI-assisted capability intended to improve the efficiency, consistency, and accessibility of fast reactor software model development at Argonne and, with further improvements, to support eventual use by the broader fast reactor community, including industry users of FRP-supported analysis tools.

Thomas, Rachel [Argonne National Laboratory (ANL),↗

Rational Design of Methylated Triazine‐Based Linear Conjugated Polymers for Efficient CO 2 Photoreduction with Water

The development of semiconducting conjugated polymers for photoredox catalysis holds great promise for sustainable utilization of solar energy. In this work, a new family of porous methylated triazine‐based linear conjugated polymers is reported that enable efficient photoreduction of carbon dioxide (CO 2 ) with water (H 2 O) vapor, in the absence of any additional photosensitizer, sacrificial agents or cocatalysts. It is demonstrated that the key lies in the generation of methylated triazine linkages through a facile condensation reaction between benzamidine and acetic anhydride, which impedes the formation of conventional triazine‐based frameworks. It is also shown that regulating conjugated linear backbones with different lengths of electron‐donated benzyl units provides a facile means to modulate their optical properties and the exciton dissociation, thereby affording more long‐lived photogenerated charge carriers and boosting charge separation and transfer. A high‐performance carbon monoxide (CO) production rate of 218.9 µmol g −1 h −1 is achieved with ≈ 100% CO selectivity, which is accompanied by exceptional H 2 O oxidation to oxygen (O 2 ). It anticipates this new study will advance synthetic approaches toward polymeric semiconductors and facilitate new possibilities for triazine‐based conjugated polymers with promising potential in artificial photocatalysis.

36 MATERIALS SCIENCE↗

Small-molecule modulation of β-arrestins

β-Arrestins are multifunctional regulators of G-protein-coupled receptor (GPCR) signalling and orchestrate diverse downstream signalling events and physiological responses across the GPCR superfamily. Although GPCR pharmacology has advanced to target orthosteric and allosteric sites, as well as G proteins and GPCR kinases, direct chemical tools to modulate β-arrestin activities have remained conspicuously absent. Here we report the identification of small-molecule inhibitors that selectively target β-arrestins and delineate their mechanism of action through integrated pharmacological, biochemical, biophysical and structural analyses. These inhibitors disrupt β-arrestin engagement with agonist-activated GPCRs, impairing desensitization, internalization and β-arrestin-dependent physiological functions while sparing G protein–receptor coupling. Cryo-electron microscopy, molecular dynamics simulations and structure-guided mutagenesis reveal that one modulator, Cmpd-5, engages a pocket within the central crest of β-arrestin1 formed by the middle, C and lariat loops, a critical receptor-binding interface, stabilizing a distinct conformation that is incompatible with full β-arrestin–receptor engagement. Together, these findings establish a mechanistic framework for β-arrestin modulation, reveal a novel allosteric site for structure-based drug design, and open new avenues for transducer-targeted, pathway-specific GPCR therapeutic agents.

Kahsai, Alem W. [Duke University, Durham, NC (Unit↗

A combined management scheme to simultaneously mitigate As and Cd concentrations in rice cultivated in contaminated paddy soil

Paddy soils in southern China are heavily co-polluted by arsenic (As) and cadmium (Cd). The accumulation of these contaminants in rice grains may pose a high health risk. We evaluated the impact of adjusted water management practice (i.e., conventional irrigation and aerobic treatment after heading stage) and the application of two immobilization agents (i.e., CaO and Fe2O3) on the accumulation of As and Cd in rice grains of three rice varieties (i.e., Jinyou-463, Jinyou-268, and Mabayouzhan). The different schemes were tested via conducting a field experiment in paddy soil in Shaoguan, Guangdong Province, China. The results showed that the combined scheme (selecting Jinyou-268, aerobic water management after the heading stage, and 0.09% CaO and 0.5% Fe2O3 amendments) exhibited the best performance in the reduction of As and Cd accumulation in rice grains. This combined scheme decreased the grain As concentration by 26.19% and maintained the Cd at a low level (0.056 mg/kg) as compared to the use of local conventional irrigation patterns. Moreover, health risk assessment demonstrated that by applying the optimal scheme, neither As nor Cd content in rice had carcinogenic risk. However, the grain As remains at a high non-carcinogenic risk. We suggest that future field study design should fully incorporate the uncertainty of the natural environment to make the research conclusions more feasible for popularization and utilization. This study demonstrated an approach of utilizing the synergy effects of various measures for safe rice production in fields subjected to As and Cd contaminations.

Yang, Xiao↗