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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 1,099 records · Page 61

Extraction, purification, and reuse of dyes from coloured polyester textiles

The removal of dyes from coloured textile waste represents a sustainable approach to textile recycling, enabling the recovery of valuable chemical, and material resources that would otherwise be discarded. Up to 40% of the greenhouse gas emissions from textiles originate from dye production, making efficient recycling of dyes a major opportunity for curbing emissions and minimizing waste in both textile manufacturing and recycling. Here, in this study, we demonstrate a process for the extraction, purification, and reuse of mixed dyes from polyester textiles using bio-based, non-hazardous solvents selected on the basis of computational predictions for polyester and dye solubilities. Extracted dyes are purified to individual compounds using counter-current chromatography and analysed via liquid chromatography-mass spectrometry. Post-extraction characterization of the extracted dyes and polymer substrate confirms dye colour retention and polyester fabric property preservation. Dye recycling is demonstrated by redyeing colour-free fabrics with the recovered dyes. We further show a potential process configuration for dye removal using a flow-through reactor packed with a textile substrate. The proposed dye removal process produces reusable, recyclable dyes, and dye-free fabrics, thus facilitating textile recycling.

36 MATERIALS SCIENCE↗

A novel, mesoporous molybdenum doped titanium dioxide/reduced graphene oxide composite as a green, highly efficient solid acid catalyst for acetalization

A novel, mesoporous composite of Mo doped TiO 2 /reduced graphene oxide is synthesized to be used as a highly efficient heterogeneous acid catalyst. The composite has a high surface area (263 m 2 g -1 ) and a monomodal pore size distribution with an average pore diameter of 3.4 nm. A comprehensive characterization of the synthesized material was done using PXRD, Raman, BET, SEM, EDX, TEM, TGA, and XPS. The composite exhibited excellent catalytic activity (1.6 h -1 TOF, >99% GC yield, and >99% selectivity) towards acetalization of cyclohexanone at room tempertaure within 30 minutes. The catalyst was reusable up to 4 reaction cycles without any significant loss in the activity and the acidic site calculations showed that the reaction is mostly driven by the weak acidic sites on the composite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterogenization of polyoxometalates as solid catalysts in aerobic oxidation of glycerol

A series of heterogeneous catalysts based on phosphomolybdic salts with different metals in counter or substituent positions, L n PMo 12 O 40 (L = Al 3+ , Fe 3+ , Cr 3+ , Ti 4+ , Zr 4+ and Zn 2+ , abbreviated as LPMo 12 ) and H x PMo 11 LO 39 (L = Zn 2+ , Cr 3+ , Fe 3+ , Al 3+ , Ti 4+ , for Ti 4+ ; the amount of O is 40, abbreviated as HPMo 11 L), were prepared using a simple calcination treatment and were evaluated in aerobic oxidation of glycerol. After calcination at about 250 °C for 4 h, homogeneous Ln P Mo 12 O 40 ·nH 2 O and H x PMo 11 LO 39 ·mH 2 O became heterogeneous. Their specific surface areas were also enhanced as well as their activity and reusability. Similar to the homogeneous catalysts, AlPMo 12 treated at 400 °C (AlPMo 12 -400) was found to be the most active catalyst in glycerol oxidation to lactic acid, with 96.1% yield and 98.6% conversion at 60 °C for 5 h with 1 MPa of O 2 ; it gave a turnover number (TON; TON = [LA]/[catalyst]) of 2.4 × 10 2 , higher than that of AlPMo 12 -250 treated at 250 °C (TON = 2.0 × 10 2 ). AlPMo 12 behaved as a heterogeneous catalyst in glycerol oxidation and could be reused at least 12 times. AlPMo 12 -400 also performed well in crude glycerol oxidation, affording lactic acid yields as high as 86.8%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

One-step production of renewable adipic acid esters from mucic acid over an Ir–ReO x /C catalyst with low Ir loading

The production of adipic acid, a large-volume platform chemical, from biomass represents a petroleum-free route to manufacturing nylon and other polymers more sustainably. In this study, a one-step conversion of bioderived mucic acid to adipates is reported over a heterogeneous, bifunctional Ir–ReO x /C catalyst via deoxydehydration (DODH) and catalytic transfer hydrogenation (CTH) using isopropanol as a green solvent and reductant. With very low Ir content (0.05 wt%), the catalyst provides a low-cost option for the tandem DODH–CTH process, while still enabling reuse and regeneration for at least five cycles. The reported catalytic system generates adipates in good yield (63%) without the need for additives (acids or halogens) or high pressure H 2 . Through model reactions and spectroscopic analyses, a bifunctional DODH–CTH mechanism was supported, with the Re VI/IV redox pair as the active DODH species and Ir0 saturating the dialkene intermediate via CTH. Thermal treatment in catalyst preparation and regeneration was optimized to limit metal leaching while maintaining good activity. Further, the present work outlines a one-step deoxygenation of an aldaric acid substrate from biomass using a bimetallic catalyst of low noble metal content to an important monomer for the polymer industry. This system facilitates use in future syntheses of sustainable chemicals from renewable oxygenates where the catalyst is reusable and affordable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical detection of alcohols with a Cu($\tiny{I}$)HETPHEN complex by reversible aldehyde to hemiacetal conversion

A heteroleptic copper(I) bis(phenanthroline) complex with aldehyde groups at the 4,7 positions of the phenanthroline ligand was synthesized. Here, the complex is responsive to alcohol, resulting in a distinct colour change caused by the facile reaction of the aldehyde group with alcohol, forming a hemiacetal product. The aldehyde species can be regenerated after heating the intermediate at 80 °C for 10 minutes, demonstrating the reusability of the complex for alcohol detection. This work presents a new strategy for applying transition metal complexes in small molecule sensing by installing functional groups in the secondary coordination sphere which reversibly react with analytes.

36 MATERIALS SCIENCE↗

Glycerol-based sustainably sourced resin for volumetric printing

Volumetric Additive Manufacturing (VAM) represents a revolutionary advancement in the field of Additive Manufacturing, as it allows for the creation of objects in a single, cohesive process, rather than in a layer-by-layer approach. This innovative technique offers unparalleled design freedom and significantly reduces printing times. A current limitation of VAM is the availability of suitable resins with the required photoreactive chemistry and from sustainable sources. To support the application of this technology, we have developed a sustainable resin based on polyglycerol, a bioderived (e.g., vegetable origin), colourless, and easily functionisable oligomer produced from glycerol. To transform polyglycerol-6 into an acrylate photo-printable resin we adopted a simple, one-step, and scalable synthesis route. Polyglycerol-6-acrylate fulfils all the necessary criteria for volumetric printing (transparency, photo-reactivity, viscosity) and was successfully used to print a variety of models with intricate geometries and good resolution. The waste resin was found to be reusable with minimal performance issues, improving resin utilisation and minimising waste material. Furthermore, by incorporating dopants such as poly(glycerol) adipate acrylate (PGA-A) and 10,12-pentacosadyinoic acid (PCDA), we demonstrated the ability to print objects with a diverse range of functionalities, including temperature sensing probes and a polyester excipient, highlighting the potential applications of these new resins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biopolymer-supramolecular polymer hybrids for photocatalytic hydrogen production

Solar generation of H 2 is a promising strategy for dense energy storage. Supramolecular polymers composed of chromophore amphiphile monomers containing perylene monoimide (PMI) have been reported as crystalline light-harvesting assemblies for aqueous H 2 -evolving catalysts. Gelation of these supramolecular polymers with multivalent ions creates hydrogels with high diffusivity but insufficient mechanical stability and catalyst retention for reusability. We report here on using sodium alginate (SA) biopolymer to both induce supramolecular polymerization of PMI and co-immobilize them with catalysts in a robust hydrogel with high diffusivity that can also be 3D-printed. Faster mass transfer was achieved by controlling the material macrostructure by reducing gel diameter and microstructure by reducing biopolymer loading. Optimized gels produce H 2 at rates rivaling solution-based PMI and generate H 2 for up to 6 days. The PMI assemblies in the SA matrix create a percolation network capable of bulk-electron transfer under illumination. These PMI–SA materials were then 3D-printed on conductive substrates to create 3D hydrogel photoelectrodes with optimized porosity. The design of these versatile hybrid materials was bioinspired by the soft matter environment of natural photosynthetic systems and opens the opportunity to carry out light-to-fuel conversion within soft matter with arbitrary shapes and particular local environments.

36 MATERIALS SCIENCE↗

Image plate multi-scan response to fusion protons in the range of 1–14 MeV

Image plates (IPs) are a quickly recoverable and reusable radiation detector often used to measure proton and x-ray fluence in laser-driven experiments. Recently, IPs have been used in a proton radiography detector stack on the OMEGA laser, a diagnostic historically implemented with CR-39, or radiochromic film. The IPs used in this and other diagnostics detect charged particles, neutrons, and x-rays indiscriminately. IPs detect radiation using a photo-stimulated luminescence (PSL) material, often phosphor, in which electrons are excited to metastable states by ionizing radiation. Protons at MeV energies deposit energy deeper into the IP compared with x rays below ∼20 keV due to the Bragg peak present for protons. This property is exploited to discriminate between radiation types. Doses of mono-energetic protons between 1.7 and 14 MeV are applied to IPs using the MIT linear electrostatic ion accelerator. This paper presents the results from consecutive scans of IPs irradiated with different proton energies. The PSL ratios between subsequent scans are shown to depend on proton energy, with higher energy protons having lower PSL ratios for each scan. This finding is separate from the known energy dependence in the absolute sensitivity of IPs. The results can be compared to complimentary work on x rays, showing a difference between protons and x rays, forging a path to discriminate between proton and x-ray fluence in mixed radiation environments.

Instruments & Instrumentation↗

Assessment of Critical Experiment Benchmark Applicability to a Large-Capacity HALEU Transportation Package Concept

This work presents an assessment of the applicability of existing benchmark critical experiments to the criticality safety code validation for a large-capacity high-assay low-enriched uranium (HALEU) transportation package concept. Numerous next-generation nuclear reactor designs require HALEU fuel, which is characterized by an enrichment between 5 and 20 wt% 235 U. The U.S. Department of Energy (DOE) has proposed to recover and downblend highly enriched uranium from DOE-owned used nuclear fuel to accelerate the demonstration of commercially viable microreactor technologies. One element of the infrastructure needed to demonstrate HALEU-fueled reactors is the ability to safely transport enriched product to be used for fuel fabrication. There is uncertainty as to whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. The anticipated chemical form of the HALEU in the proposed transportation concept is UO 2 with 20 wt% 235 U/U. The concept uses a combination of an existing transportation packaging design and a novel basket design, including borated aluminum flux traps. The basket provides space for 18 reusable, stainless steel canisters that contain the HALEU. In 10 CFR 71, normal conditions of transport (NCTs) and hypothetical accident conditions (HACs) are defined for fissile material transportation packages. NCT and HAC KENO-VI models of the transportation package were developed using the Standardized Computer Analyses for Licensing Evaluation (SCALE) 6.2.3 computer code package, and optimum moderation conditions were determined using the SCALE SAMPLER sequence. The SCALE Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) sequences were then used to compare the neutronic characteristics of 1584 International Criticality Safety Benchmark Evaluation Project benchmark critical experiments with the NCT and HAC HALEU transportation models. The TSUNAMI integral correlation coefficient c k was the criterion used to rank neutronic similarity. Thirty-four experiments were identified as similar (c k ≥ 0.9) to the NCT model, and 55 experiments were identified as similar to the HAC model. Hundreds of experiments were also identified as at least marginally similar (c k ≥ 0.8) to both models. The results indicate that additional critical experiments are unlikely to be needed to support HALEU transportation criticality safety analyses for package concepts similar to the concept package analyzed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deceptive Infusion of Data: A Novel Data Masking Paradigm for High-Valued Systems

This work addresses how analysts of a high-valued system (e.g., nuclear reactor, aircraft turbine designs) can extract findable, accessible, interoperable, and reusable scientific data for public dissemination to artificial intelligence and machine-learning (AI/ML) researchers in a manner that cannot be reverse-engineered, potentially compromising sensitive or proprietary information. State-of-the-art methods address this problem through data masking techniques, which allow access to a subset of the information while obfuscating private and potentially identifying information (e.g., personally identifying medical data). These methods are unsuitable for industrial engineering processes, where AI/ML tools need explicit access to all the data available to draw the best inference about the system to help optimize its performance and identify its vulnerabilities, etc. Our novel deceptive infusion of data paradigm provides a solution to this conundrum by developing a mathematical approach capable of concealing the identity of the system while providing full access to all the features employed by AI/ML tools to ensure their optimal performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗

Production and testing of the powerboard for ATLAS ITk Strip barrel modules

The upgrade of the ATLAS ITk strips detector for HL-LHC will employ a custom PCB (powerboard) for on-module DC-DC conversion, HV switching, and monitoring. Production of about 14100 of such PCBs with high reliability is a big challenge. In this paper we will present the production procedure and quality control (QC) testing system for the powerboards to be installed on ITk Strip barrel modules. During production, about 150 powerboards will be produced every week. Each powerboard will need to pass QC tests before they are assembled to module. The QC tests include thermal cycling between -35 °C and 40 °C, soak test (continuous running of DC-DC converter at high load at 20 °C), and basic functionality and characterization electrical tests of the low voltage (LV), high voltage (HV), and monitoring functions of the powerboard. A custom QC test system is described, which is based on a reusable PCB (active board) with all testing circuits, a one-time powerboard carrier card, and a Z-turn SoC board which hosts and runs the testing program. The production procedure and QC test system has been tested with 400 powerboards during pre-production, and the system has been proven ready for production with the desired testing program, speed, safety, and cost. Performance and typical failures of powerboards observed during the QC test of pre-production powerboards is also presented.

47 OTHER INSTRUMENTATION↗

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗

Hosting downscaled decision-relevant community data products in ESGF2-US

As regionally-relevant high-resolution Earth system data is increasingly relied upon across scientific, policy, and practitioner communities, there is an urgent need for coordinated and federated infrastructure to store, manage, standardize, and distribute decision-relevant community data products. Substantial effort is required to ensure that these products, which are often critical for regional impact assessments and decision-making, are findable, accessible, interoperable, and reusable. The Earth System Grid Federation US project (ESGF2-US) is addressing this challenge by expanding its open-source, distributed platform to support the hosting and dissemination of downscaled Earth system datasets. This expansion includes aligning new downscaled datasets with developing community standards for metadata and file structure, consistent with existing ESGF archives. This includes ensuring CF-compliance, applying CMORization where appropriate, and developing tools to streamline user access. In this paper, we highlight the technical and coordination work required to bring downscaled data into ESGF2-US and aim to inform the broader Earth system data user community about the growing availability and utility of these curated resources.

ESGF↗