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At least 775 records · Page 43

Fabrication and accelerated long-term stability test of asymmetrical hollow fiber-supported thin film oxygen separation membrane

Asymmetrical hollow fiber-supported thin film membrane may provide microstructural advantages for air separation and oxygen production. The fabrication of such a membrane is usually very difficult, particularly the sintering behaviors and thermal expansion coefficient (TEC) mismatch among multiple layers. This directly affects the reliability and long-term stability of the membrane. Here, in this research, the sintering behaviors of a set of simple oxides are systematically studied and ZnO is identified as a material component for composite substrate La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ (LSCF)-ZnO. The LSCF-ZnO ratios are further optimized by trading off several factors, e.g., matching the sintering behaviors and TECs of the LSCF-ZnO composite with those of LSCF thin film separation layer while enhancing the substrate strength. With the identified LSCF-ZnO ratio, the LSCF-ZnO composite hollow fiber substrate precursor is formed through slurry spinning process with porous microstructure being formed via phase inversion process. The thin film LSCF dense separation layer is then dip-coated on the substrate followed by co-sintering process. A thin, porous PrBaCo(Fe 0.6 Zr 0.2 Y 0.2 )O 5+δ (PBCFZY) catalyst layer is fabricated on the dense LSCF separation layer with dip-coating and sintering process, forming an asymmetrical membrane device LSCF-ZnO/LSCF/PBCFZY. Oxygen permeation test of the device is systematically conducted, and the fundamental mechanisms are analyzed. An accelerated long-term stability test of the membrane is also conducted (~550h, 46 thermal cycling loads), demonstrating excellent robustness and durability. The device is characterized and analyzed before and after the test. By replacing a considerable amount of high cost LSCF with low cost ZnO in the substrate, it not only enhances the stability but also reduces the capital cost of the membrane for practical applications.

42 ENGINEERING↗

Laser powder bed fusion of ODS Fe–Cr–Al (0.3Zr, 0.3Y 2 O 3 ): Unveiling processing-microstructure- mechanical property relationships

Here, this study investigates the fabrication of oxide dispersion strengthened (ODS) Fe-Cr-Al alloys via laser powder bed fusion (LPBF) with strategic additions of 0.3 wt% Zr and 0.3 wt% Y 2 O 3 for enhanced mechanical performance in nuclear applications. Systematic processing parameter optimization yielded three distinct conditions: one low-density product with significant defects and two near-full-density materials with improved consolidation. Comprehensive characterization confirmed single-phase α-ferrite matrix formation with successful incorporation of Y-, Zr-, O-, and C-rich precipitates characteristic of ODS alloys. However, precipitate density remained low (∼10 7 cm −3 ), resulting in sink strength values substantially below optimal levels for radiation resistance. Microhardness values (mid-200s HV) correlated inversely with grain size following the Hall-Petch relationship, indicating grain boundary strengthening as the dominant mechanism rather than precipitation strengthening. The optimized processing conditions achieved excellent mechanical properties with room temperature yield strength of approximately 500 MPa and 30 % elongation, demonstrating superior strength-ductility synergy compared to other additively manufactured ODS materials and performance consistent with literature values for LPBF-processed ODS-FeCrAl alloys. This investigation reveals both the potential and limitations of LPBF processing for ODS Fe-Cr-Al alloys. While successful defect-free fabrication was achieved, results highlight the critical need for systematic optimization of processing parameters and post-processing heat treatments to enhance precipitate density for effective dispersion strengthening and radiation resistance while maintaining additive manufacturing advantages.

Additive manufacturing↗

IRDFF-II: A New Neutron Metrology Library

High quality nuclear data is the most fundamental underpinning for all neutron metrology applications. This paper describes the release of version II of the International Reactor Dosimetry and Fusion File (IRDFF-II) that contains a consistent set of nuclear data for fission and fusion neutron metrology applications up to 60 MeV neutron energy. The library is intended to support: a) applications in research reactors; b) safety and regulatory applications in the nuclear power generation in commercial fission reactors; and c) material damage studies in support of the research and development of advanced fusion concepts. The paper describes the contents of the library, documents the thorough verification process used in its preparation, and provides an extensive set of validation data gathered from a wide range of neutron benchmark fields. The new IRDFF-II library includes 119 metrology reactions, four cover material reactions to support self-shielding corrections, five metrology metrics used by the dosimetry community, and cumulative fission products yields for seven fission products in three different neutron energy regions. In support of characterizing the measurement of the residual nuclei from the dosimetry reactions and the fission product decay modes, the present document lists the recommended decay data, particle emission energies and probabilities for 68 activation products. It also includes neutron spectral characterization data for 29 neutron benchmark fields for the validation of the library contents. Additional six reference fields were assessed (four from plutonium critical assemblies, two measured fields for thermal-neutron induced fission on 233U and 239Pu targets) but not used for validation due to systematic discrepancies in C/E reaction rate values or lack of reaction-rate experimental data. Another ten analytical functions are included that can be useful for calculating average cross sections, average energy, thermal spectrum average cross sections and resonance integrals. The IRDFF-II library and comprehensive documentation is available online at www-nds.iaea.org/IRDFF/. Evaluated cross sections can be compared with experimental data and other evaluations at www-nds.iaea.org/exfor/endf.htm. The new library is expected to become the international reference in neutron metrology for multiple applications.

IAEA IRDFF↗

Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra

γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

System-size dependence of the charged-particle pseudorapidity density at $\sqrt{s_{NN}}$ = 5.02 TeV for pp, p–Pb, and Pb–Pb collisions

We present the first systematic comparison of the charged-particle pseudorapidity densities for three widely different collision systems, pp, p–Pb, and Pb–Pb, at the top energy of the Large Hadron Collider ($\sqrt{s_{NN}}$ = 5.02 TeV) measured over a wide pseudorapidity range (-3.5 < η < 5), the widest possible among the four experiments at that facility. The systematic uncertainties are minimised since the measurements are recorded by the same experimental apparatus (ALICE). The distributions for p–Pb and Pb–Pb collisions are determined as a function of the centrality of the collisions, while results from pp collisions are reported for inelastic events with at least one charged particle at midrapidity. The charged-particle pseudorapidity densities are, under simple and robust assumptions, transformed to charged-particle rapidity densities. This allows for the calculation and the presentation of the evolution of the width of the rapidity distributions and of a lower bound on the Bjorken energy density, as a function of the number of participants in all three collision systems. We find a decreasing width of the particle production, and roughly a smooth ten fold increase in the energy density, as the system size grows, which is consistent with a gradually higher dense phase of matter

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Effect of 3D-printed surface textures on wear mechanism in 3-body abrasion of soil

This study systematically investigates the enhancement of wear resistance in 3D printed surface textures through both experimental and theoretical approaches. Three distinct surface morphologies (Smooth Surface, Surface with uniformly distributed Pits, and Surface with uniformly distributed Bumps) were fabricated using High-Impact Polystyrene, where the meso-scale textures were precisely controlled through the 3D printing process. Wear behavior was evaluated using a 3-body wear tester in an abrasive particle environment, analyzing the influence of surface textures under various operating conditions. Systematic wear tests revealed that optimally designed surface textures achieved a remarkable 77 % reduction in wear compared to the worst-performing sample. The wear mechanisms were comprehensively characterized through weight loss measurements, Scanning Electron Microscopy (SEM), and Energy Dispersive Spectroscopy (EDS) analyses, elucidating the surface morphology changes and their interaction with wear particles. Notably, the study identified how the geometric characteristics of surface textures influence the movement of wear particles and the distribution of contact stresses. Discrete element method simulations corroborated the experimental findings, providing theoretical validation for the enhanced wear resistance of the optimal structure. The high correlation between simulated wear patterns and experimental results validates the reliability of the proposed design methodology. In conclusion, these results demonstrate that 3D printed surface texturing offers a cost-effective and scalable approach to significantly improve wear resistance in engineering applications, presenting a practical alternative to conventional, high-cost surface engineering methods.

3-body abrasion↗

Performance estimation of resonance-enhanced dual-buoy wave energy converter using coupled time-domain simulation

This article presents the modeling methodology and performance evaluation of the resonance-enhanced dual-buoy WEC (Wave Energy Converter) by HEM (hydrodynamic & electro-magnetic) fully-coupled-dynamics time-domain-simulation program. The numerical results are systematically compared with the authors’ 1/6-scale experiment. With a direct-drive linear generator, the WEC consists of dual floating cylinders and a moon-pool between the cylinders, which can utilize three resonance phenomena from moon-pool dynamics as well as heave motions of inner and outer buoys. The contact and friction between the two buoys observed in the experiment are also properly modeled in the time-domain simulation by the Coulomb-friction model. Moon-pool resonance peaks significantly exaggerated in linear potential theory are empirically adjusted through comparisons with measured values. A systematic comparative study between the simulations and experiments with and without PTO (power-take-off) is conducted, and the relative heave displacements/velocities and power outputs are well matched. Then, parametric studies are carried out with the simulation program to determine optimum generator parameters. The performance with various wave conditions is also assessed.

16 TIDAL AND WAVE POWER↗

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Current nature-based biological practices for rare earth elements extraction and recovery: Bioleaching and biosorption

There is a growing demand for advancing products and renewable technologies worldwide that rely on rare earth elements (REEs), including those directly necessary for a low-carbon energy transition, national security applications, and consumer electronics. This study focuses on current nature-based biological methods (i.e., bioleaching and biosorption) for REEs extraction from electronic wastes (e-wastes) and ore deposits. Herein, comprehensive narrative and systematic reviews of bioleaching and biosorption extraction methods are performed to identify their sustainability challenges and benefits, and highlight the potential pathways that would address the existing gaps. From the narrative review, it is evident that biological methods for REEs extraction are more environmentally friendly than conventional methods currently used in the REE mining industry (e.g., acid leaching and solvent extraction). From the systematic review, it is clear that bioleaching and biosorption research has been a rapidly growing field of interest over the last 10 years, particularly for precious metals extraction (e.g., copper and gold). From both reviews, it is apparent that REEs extraction from domestic ore deposits alone is inadequate, and sustainable REEs recovery from e-wastes is also necessary to meet the growing REEs demand. It is concluded that targeted mixed REEs extraction for specific products can be a potential pathway for sustainable REEs extraction from both ore and e-wastes that would reduce separation costs and emissions from the associated use of harsh chemicals. It is further concluded that nature-based biological REE extraction solutions offer an opportunity to generate significant socio-economic and environmental benefits.

54 ENVIRONMENTAL SCIENCES↗

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evidence of a $J/ψΛ$ structure and observaton of excited $Ξ_{b}^{-}$ → $J/ψΛΚ^{-}$ decay

First evidence of a structure in the $J/ψΛ$ invariant mass distribution is obtained from an amplitude analysis of $Ξ_{b}^{-}$ → $J/ψΛΚ^{-}$ decays. The observed structure is consistent with being due to a charmonium pentaquark with strangeness with a significance of 3.1σ including systematic uncertainties and look elsewhere effect. Its mass and width are determined to be 4458.8 ± $2.9_{-1.1}^{+4.7}$ MeV and 17.3 ± $6.5_{-5.7}^{+8.0}$ MeV respectively, where the quoted uncertainties are statistical and systematic. The structure is also consistent with being due to two resonances. In addition, the narrow excited $Ξ^{-}$ states, $Ξ(1690)^{-}$ and $Ξ(1820)^{-}$, are seen for the first time in a $Ξ_{b}^{-}$ decay, and their masses and widths are measured with improved precision. The analysis is performed using $pp$ collision data corresponding to a total integrated luminosity of 9 fb -1 , collected with the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine-learning-aided density functional theory calculations of stacking fault energies in steel

A combined large-scale first principles approach with machine learning and materials informatics is proposed to quickly sweep the chemistry-composition space of advanced high strength steels (AHSS). AHSS are composed of iron and key alloying elements such as aluminum and manganese. A systematic exploration of the distribution of aluminum and manganese atoms in iron is used to investigate low stacking fault energies configurations using first principles calculations. To overcome the computational cost of exploring the composition space, this process is sped up using an automated machine learning tool: DeepHyper. Here our results predict that it is energetically favorable for Al to stay away from a stacking fault, but Mn atoms do not affect the stacking fault energy and can stay in the vicinity of the fault. The distribution of Al and Mn atoms in systems containing stacking faults and the effects of their interactions on the equilibrium distribution are systematically analyzed.

36 MATERIALS SCIENCE↗

Improved field evaluation of reference cells using spectral measurements

Output from an IMT reference solar cell mounted on a one-axis tracking surface is investigated using spectral measurements covering the 350–1650 nm range for selected days throughout the year. Comparisons are made to a Class-A pyranometer also mounted on the one-axis tracking surface. Systematic biases over the day and year are observed in the ratio of the reference cell’s measurements to reference pyranometer measurements. This systematic bias is associated with the spectral, temperature, and angle-of-incident effects that differ between the reference cell and the reference pyranometer. The comparison is done for selected clear and totally cloudy days to determine the magnitude of the effects and to characterize the influence of these effects on the reference cell measurements. A model to calculate the reference cell output based on spectral irradiance and reference cell temperature is introduced.

14 SOLAR ENERGY↗

Overcoming significant challenges in extracting off-stoichiometric thermodynamics using the compound energy formalism through complementary use of experimental and first principles data: A case study of Ba 1-x Sr x FeO 3-δ

The compound energy formalism (CEF) is a powerful framework to describe the thermodynamics of metal oxides as a function of off-stoichiometry, temperature, and composition. The thermodynamic properties are crucial materials design attributes in metal oxide-based oxygen-exchange chemical processes. Despite the richness of information an accurate CEF model provides, a method to determine a unique and accurate fit for oxygen exchange materials remains elusive. This contribution details a method for fitting the CEF model that overcomes the current fitting challenges through three innovations: 1) the combination of density functional theory calculations with experimental data decorrelates excess terms and delineates the enthalpic/entropic contributions to the Gibbs free energy; 2) a systematic determination of the important CEF model terms, removing thermodynamic predetermining human intervention; 3) a self-consistent solution of the starting oxygen offstoichiometry (δ 0 ) of thermogravimetric measurements. Thus, our method enables the reliable extraction of off-stoichiometric metal oxide thermodynamic properties and facilitates rapid materials compositional screening, and reliable process design of systems dependent on off-stoichiometric redox-active metal oxides. We apply this method to a Ba x Sr 1-x FeO 3-δ test case. We find by systematically examining the performance of the CEF model fit with and without each innovation that all three innovations are necessary for an accurate fit. We determined that reduction enthalpy is higher and more sensitive to off-stoichiometry when the Sr fraction is large (139.5 and 185.3 kJ/mol O 2 for SrFeO 3 at δ = 0 and δ = 0.5, respectively vs. nearly constant 83 kJ/mol O 2 for BaFeO 3 ). However, the reduction entropy is mostly insensitive to Sr fraction, but highly dependent on δ suggesting larger contributions in the non-configurational entropy parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mineral scaling on brass and aluminum surfaces with a range of wettability

Crystallization fouling, or mineral scaling, is fundamental to various surfaces in energy and environmental applications. This paper considers, for the first time, a systematic investigation of scaling of nonwetting aluminum and brass surfaces relative to their bare counterparts. Metallic surfaces with a range of nonwetting characteristics from hydrophilic to superhydrophobic and lubricant infused surfaces were fabricated using a facile etching method. Systematic dynamic flow scaling experiments are conducted on the six different surface types at three flow levels and two temperature levels. The interactive effects of the different parameters are analyzed relative to their correspondence to the nucleation theory. The study reveals that nonwetting metallic superhydrophobic or hydrophobic surfaces reduce fouling by over 50% compared to bare counterparts. Further, lubricant infused metallic surfaces demonstrate superior anti-scaling performance by over 60% and up to 90% fouling reduction. The study is the first to present fundamental insights into the engineering and anti-scaling performance of nonwetting brass and aluminum surfaces.

36 MATERIALS SCIENCE↗

Chemodiversity of riverine dissolved organic matter: Effects of local environments and watershed characteristics

Riverine dissolved organic matter (DOM) is crucial to global carbon cycling and aquatic ecosystems. However, the geographical patterns and environmental correlates of DOM chemodiversity remain elusive especially in surface waters and sediments of global rivers. Here, we systematically analyzed DOM molecular diversity and composition in surface waters and sediments across 97 globally distributed rivers using data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. Here, we further examined the associations of molecular richness and composition with geographical, climatic, physicochemical variables, as well as the watershed characteristics. We found that molecular richness significantly decreased toward higher latitudes, but only in sediments (r = -0.24, P < 0.001). The environmental variables like precipitation and non-purgeable organic carbon showed strong associations with DOM molecular richness and composition. Interestingly, we identified that less-documented factors like watershed characteristics were also related to DOM molecular richness and composition, and were stronger in waters than sediments. Such associations were further supported by the fact that 11 out of 13 watershed characteristics (e.g., land cover variables) showed more positive than negative correlations with molecular abundance especially in waters. The molecules positively and negatively correlated with specific watershed characteristics had distinct traits, such as stoichiometric ratios and aromaticity. Land covers shifted from natural (e.g., forests) to human-modified (e.g., impervious area) were associated with systematic changes in DOM molecular chemistry. Our findings imply that it may be possible to use a small set of broadly available data types to predict DOM molecular richness and composition across diverse river systems. Elucidation of mechanisms underlying these relationships will provide further enhancements to such predictions, especially when extrapolating to unsampled systems.

54 ENVIRONMENTAL SCIENCES↗

Proteome reallocation enables the selective de novo biosynthesis of non-linear, branched-chain acetate esters

The one-carbon recursive ketoacid elongation pathway is responsible for making various branched-chain amino acids, aldehydes, alcohols, and acetate esters in living cells. Controlling selective microbial biosynthesis of these target molecules at high efficiency is challenging due to enzyme promiscuity, regulation, and metabolic burden. In this study, we present a systematic modular design approach to control proteome reallocation for selective microbial biosynthesis of branched-chain acetate esters. Through pathway modularization, we partitioned the branched-chain ester pathways into four submodules including keto-isovalerate submodule for converting pyruvate to keto-isovalerate, ketoacid elongation submodule for producing longer carbon-chain keto-acids, ketoacid decarboxylase submodule for converting ketoacids to alcohols, and alcohol acyltransferase submodule for producing branched-chain acetate esters by condensing alcohols and acetyl-CoA. By systematic manipulation of pathway gene replication and transcription, enzyme specificity of the first committed steps of these submodules, and downstream competing pathways, we demonstrated selective microbial production of isoamyl acetate over isobutyl acetate. In this work, we found that the optimized isoamyl acetate pathway globally redistributed the amino acid fractions in the proteomes and required up to 23-31% proteome reallocation at the expense of other cellular resources, such as those required to generate precursor metabolites and energy for growth and amino acid biosynthesis. From glucose fed-batch fermentation, the engineered strains produced isoamyl acetate up to a titer of 8.8 g/L (> 0.25 g/L toxicity limit), a yield of 0.22 g/g (61% of maximal theoretical value), and 86% selectivity, achieving the highest titers, yields and selectivity of isoamyl acetate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗