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At least 91 records · Page 5

Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration

A single-column version of the CNRM-CM6-1 global climate model has been developed to ease development and validation of the boundary layer physics and air–sea coupling in a simplified environment. This framework is then used to assess the ability of the coupled model to represent the sea surface temperature (SST) diurnal cycle. To this aim, the atmospheric–ocean single-column model (AOSCM), called CNRM-CM6-1D, is implemented in a case study derived from the CINDY2011/DYNAMO campaign over the Indian Ocean, where large diurnal SST variabilities have been well documented. Comparing the AOSCM and its uncoupled components (atmospheric SCM and oceanic SCM, called OSCM) highlights the fact that the impact of coupling in the atmosphere results from both the possibility to take into account the diurnal variability of SST, which is not usually available in forcing products, and the change in mean state SST as simulated by the OSCM, with the ocean mean state not being heavily impacted by the coupling. This suggests that coupling feedbacks in the 3D model do not arise from the coupling of ocean and atmosphere vertical column physics but are more due to the large-scale dynamics resolved by the 3D model. Additionally, a sub-daily coupling frequency is needed to represent the SST diurnal variability, but the choice of the coupling time step between 15 min and 3 h does not impact the diurnal temperature range simulated much. The main drawback of a 3 h coupling is delaying the SST diurnal cycle by 5 h in asynchronous coupled models. Overall, the diurnal SST variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m. This framework is shown to be a very valuable tool to develop and validate the boundary layer physics and the coupling interface. It highlights the interest to develop other atmosphere–ocean coupling case studies.

54 ENVIRONMENTAL SCIENCES↗

Efficient Precoding for Single Carrier Modulation in Multi-User Massive MIMO Networks

Abstract—Frequency domain (FD) multi-user detection (MUD) and precoding has been shown to be an effective means of approaching the theoretical per-user capacity for single carrier modulation (SCM) schemes in massive MIMO scenarios with highly dispersive channels. When a cyclic prefix is added to the SCM waveform, the circulant structures of the resulting convolutional channel matrix allows for relatively simple expressions for the FD detection and precoding. In this paper, we further refine the computationally efficient minimum mean squared error (MMSE) FD-MUD technique in a time-division duplexing (TDD) massive MIMO setup by pre-computing the scale factor needed to produce an unbiased estimate. The resulting scale factor and the matrix inverse that was calculated for the uplink is then reused for the downlink to form a computationally efficient precoding scheme with superior performance compared to zero-forcing (ZF) precoding. Performance analysis is provided and confirmed through simulation results.

5G and Beyond Communications↗

Frequency Domain Multi-user Processing for Single Carrier Modulation with Cyclic Prefix

Frequency domain (FD) detection and precoding have been shown to be effective means of approaching the theoretical per-user capacity for single carrier modulation SCM) schemes. When a cyclic prefix is added to the SCM waveform, the circulant structures of the resulting convolutional channel matrix allows for relatively simple expressions for the FD processing, and achieves performance near the theoretical capacity even for high signal to noise ratio values. This paper details the signal processing for uplink and downlink multi-user operation with a multi-antenna base station.

5G and Beyond Communication↗

Generative AI in Supply Chain Management: Applications, Challenges, and Future Directions

Supply chain management (SCM) is undergoing rapid transformation due to increasing global complexity, demand volatility, and operational disruptions. Generative Artificial Intelligence (GenAI) has emerged as a powerful paradigm capable of synthesizing data, simulating operational scenarios, and enabling adaptive decision-making across supply chain networks. This paper presents a survey of GenAI’s role in SCM, focusing on its applications in predictive analytics, autonomous logistics, and fraud detection. Unlike traditional AI systems that rely primarily on predictive analytics, GenAI models, including large language models, generative adversarial networks, and diffusion-based architectures, enable the creation of synthetic supply chain scenarios and autonomous optimization strategies. This survey provides (1) a taxonomy of GenAI techniques for supply chain applications, (2) a comparative analysis of generative AI approaches with traditional machine learning, reinforcement learning, and blockchain-based methods, and (3) a discussion of key challenges such as data privacy, interpretability, and integration with legacy enterprise systems. Furthermore, we outline open research problems and propose directions for future research toward autonomous, resilient, and sustainable AI-driven supply chains.

15 - GEOTHERMAL ENERGY↗

Assessment of the feedstock supply for siting single- and multiple-feedstock biorefineries in the USA and identification of prevalent feedstocks

An integrated multi-feedstock bioenergy (i.e., biofuel, biopower, or bioproduct) supply system has potential to reduce biomass supply system uncertainties and costs. This study identifies optimal configurations of multi-feedstock biomass-to-biorefinery supply chains and pertinent feedstock combinations based on spatial distribution of feedstock and lowest delivered cost to the biorefinery. We used the Supply Characterization Model (SCM) to allocate feedstock supplies to candidate biorefinery facilities. Model runs were performed for herbaceous energy crops, agriculture residue, and woody biomass available in 2017, 2022, 2025, and 2030 as estimated by the Policy Analysis System (POLYSYS) and Forest Sustainable and Economic Analysis Model (ForSEAM) models. Three feedstock supply scenarios were compared: (a) an herbaceous scenario: switchgrass, miscanthus, biosorghum, and corn stover; (b) a woody scenario: coppice wood, noncoppice wood, whole trees, and forestry residues, and (c) a mixed scenario: a combination of all feedstocks in herbaceous and woody scenarios. By 2030 the analyses predicted that 323, 168, and 473 biorefineries were sited in the herbaceous, woody, and mixed scenario, respectively, in the conterminous USA. Feedstock mixes supplied to the biorefineries were mostly dominated by a single feedstock. The most prominent feedstock mixes identified were: (1) switchgrass and miscanthus; (2) coppice and noncoppice wood; and (3) coppice wood, noncoppice wood, switchgrass and miscanthus. Biorefineries using multi-feedstock would be beneficial for growth of bioeconomy, however flexible and cost-effective conversion platforms should be developed to efficiently utilize multiple feedstocks. This analysis identifies biorefinery locations and feedstock supply mixes while minimizing delivered feedstock costs based on spatial and temporal feedstock availability.

09 BIOMASS FUELS↗

Reduction Thermodynamics of Sr 1– x Ce x MnO 3 and Ce x Sr 2– x MnO 4 Perovskites for Solar Thermochemical Hydrogen Production

Herein, the compositional families Sr 1–x Ce x MnO 3 (SCMX, X = 100x, x = 0.10, 0.20, and 0.30) and Ce x Sr 2–x MnO 4 (CSMX, X = 100x, x = 0.10, 0.20, and 0.30) are studied to determine the effects of perovskite structure and cerium content on thermal reduction thermodynamics and the resulting impact on solar thermochemical hydrogen production (STCH). Relying on thermogravimetric results from oxygen nonstoichiometry experiments, fits for various thermodynamic quantities are produced, including defect-reaction specific enthalpy (Δ H) and entropy (Δ S ), as well as the δ-dependent standard partial molar enthalpy, Δh¯$^{°}_{Ο}$, and entropy Δs¯$^{°}_{Ο}$, of oxygen as a function of composition within these two perovskite families. Here, the results of this thermodynamic study are also discussed in the context of structure and cerium dopant level. Experimental hydrogen production results show that the SCM family produces slightly larger amounts of hydrogen per mole of oxide compared with the CSM family under similar reduction and oxidation temperature conditions, however, a direct correlation between structure, cerium content, and water-splitting capacity could not be discerned.

08 HYDROGEN↗

Effect of autogenous shrinkage on microcracking and mass transport properties of concrete containing supplementary cementitious materials

It is well-known that supplementary cementitious materials (SCMs) and low water-to-binder (w/b) ratio increase autogenous shrinkage, but the impact on microcracking and long-term transport properties is less understood. This paper examines the effect of microcracking induced by autogenous shrinkage on transport properties of concretes cured up to ~3.6 years. Variables include SCM type (9% SF, 70% GGBS), w/b ratio (0.20–0.45), maximum-aggregate-size (MSA: 5–20 mm) and shrinkage reducing admixture (SRA). Oxygen diffusivity, permeability and water sorptivity were correlated with microcracks characterised using laser scanning confocal microscopy and 3D X-ray microtomography. Results show greater microcracking in mixes containing SCMs, low w/b ratio and large MSA. At the same w/b ratio and binder type, strong positive correlations are observed between transport and microcracking with increasing MSA, confirming the negative impact of autogenous shrinkage. SRA was effective in reducing these effects. The significance is compared with drying shrinkage and implications for durability are discussed.

36 MATERIALS SCIENCE↗

Application of spectroscopic evidence to diffuse layer model (DLM) parameter estimation for cation adsorption onto ferrihydrite in single- and bi-solute systems

The diffuse layer model (DLM) is one of the most frequently used surface complexation models (SCM) for predicting cation adsorption onto ferrihydrite. However, the DLM with its existing database sometimes fails to predict cation adsorption, especially in multi-solute systems. Notably, the failure is often attributed to inaccurate selection of the surface complexes and/or underestimation of the site density for DLM formulation. DLM simulations of batch adsorption data conducted with cadmium, copper, lead, and zinc on ferrihydrite in CO2 free systems demonstrates the ability of the DLM to fit single-solute data reasonably well but highlights its limitations with respect to predicting bi-solute data. Modifications to the DLM were made in two steps. First, spectroscopic evidence was used to guide cation complexation reactions at the ferrihydrite surface. Second, surface characteristics (reactive site density, specific surface area, and acidity constants) of ferrihydrite were updated according to recent literature. The results from this study suggest that when spectroscopic verification is employed and surface site density is increased, a simple two-site DLM can predict cation adsorption on ferrihydrite in single-solute systems for pH data above 3.5 and in most of the bi-solute systems tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sulfuric Acid Improves the Reactivity of Zeolites via Dealumination

The demand for supplementary cementitious materials (SCMs), like fly ash, slag, and silica fume, is projected to rise over the next few decades. However, global decarbonization efforts, such as decommissioning of coal-fired power plants, will limit the supply of SCMs. Therefore, alternative SCM sources are a critical need for the cement and concrete industry. However, the high crystallinity of zeolites limits their pozzolanic reactivity. The goal of this work was to improve the reactivity of two common zeolites, namely clinoptilolite and SSZ-13, by treating them with sulfuric acid. The treatment enhanced zeolite reactivity via dealumination and decreased particle sizes, which led to increased reactivity with calcium hydroxide, as indicated by a 42.0% increase in reaction heat measured by isothermal calorimetry. Here, we elucidate mechanistic understanding that smaller particle sizes induced by acid treatment accelerated peak heat evolution, while free aluminates from dealumination increased heat via direct reaction with aqueous Ca 2+ .

36 MATERIALS SCIENCE↗

Ultra-low-level measurements of airborne fission products from the Fukushima Daiichi reactor accident using high volume collection systems at Savannah River National Laboratory

For this study, ultra-low-level measurements of radionuclides in air have been conducted at the Savannah River National Laboratory (SRNL) to determine the atmospheric concentration of fission products released following the Fukushima Daiichi reactor accident on March 11, 2011. Air filter samples were acquired from two high-volume collection systems (a traditional filter-based system and an electrostatic precipitator-based system) to monitor airborne radionuclide concentrations in the period covering from 2 weeks to 3 years after the disaster. The world-wide spread of low-level concentrations of airborne fission products from the Fukushima event provided a unique opportunity to demonstrate SRNL's electrostatic particle collection technology and other improvements in environmental monitoring developed at the Savannah River Site (SRS). Detecting and analyzing the release allowed a comprehensive test of SRS systems for monitoring environmental radioactivity. Gamma-ray-emitting fission products ( 131,132 I, 134,136,137 Cs, and 129,132 Te) and cosmogenic isotopes ( 7 Be and 22 Na) in air were detected and quantified by high-resolution gamma-ray spectroscopy at concentrations as low as 0.07 μBq per standard cubic meter (SCM) (50 mBq total 137 Cs), while plutonium content was quantified by thermal ionization mass spectrometry (TIMS) at concentrations as low as 6.5 × 10 –21 g/SCM (3.0 fg 239+240 Pu). Isotope concentrations measured at SRNL from gamma-ray spectroscopy were compared to independent measurements from Chapel Hill, NC, located approximately 370 km (230 mi) NE of SRNL. Meteorological modeling was also used to predict radionuclide transport from the location of release to both measurement locations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Modeling assisted synthesis of Zr-doped Li 3-x In 1-x Zr x Cl 6 with ultrahigh ionic conductivity for lithium-ion batteries

All-solid-state lithium-ion batteries (ASSLBs) are an important milestone for the future of energy storage because of their capability of impressive energy density and outstanding safety. However, oxide and sulfide solid-state electrolytes (SSEs) suffer from either low ionic conductivity or poor chemical stability. In contrast, halide-based SSEs, are promising as candidate materials owing to high conductivity, good stability, and broad cathode compatibility. Though element doping of the SSEs is an effective and common approach to further improve their electrochemical properties, dopant exploration and optimization through solely experimental trials are both costly and time-consuming. For this aspect, computational simulations for dopant element and concentration screening are adopted in this research and zirconium is selected as a suitable dopant for Li 3 InCl 6 . Further, the synthesized Li 2.75 In 0.75 Zr 0.25 Cl 6 exhibited Li ionic conductivity of 5.82 x 10 -3 Scm -1 at room temperature, which is the highest among reported halide SSEs. The ASSLB formed with Li 2 CoO 2 -Li 2.75 In 0.75 Zr 0.25 Cl 6 -Li/In delivers a high initial capacity of 129.3 mAh∙g -1 . Conclusively, this work provides an effective approach which combines computational modeling and experimental verification for the development of halide SSEs with improved stability and conductivity. The successful design approach and compelling results provide further possibilities and capabilities in future SSE research.

25 ENERGY STORAGE↗

Application of GO anchored mediator in a polymer electrolyte membrane for high-rate solid-state supercapacitors

Here, we synthesized a novel polymer electrolyte membrane by combining poly (vinylidene fluoride) (PVDF) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) with graphene oxide (GO) nanosheets and a lithium salt of tungstosilicic acid (Li 4 SiW 12 O 40 , hereafter, referred to SiWLi). The impact of the addition of GO/SiWLi on the microstructure and morphology of the membrane were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). We found that adding the GO/SiWLi to the PVDF/LiTFSI polymer electrolyte membrane significantly reduced the pore size. Furthermore, the addition of the GO/SiWLi resulted in not only an increase of the ionic conductivity from 0.87 $\times$ 10 –2 to 3.12 $\times$ 10 –2 Scm –1 but also an increase in the lithium-ion transference number from 0.52 to 0.87. The polymer electrolyte membranes with and without GO/SiWLi were utilized to fabricate solid-state supercapacitors. The supercapacitors fabricated with the membrane containing GO/SiWLi displayed 37.2% lower equivalent series resistance and 88.2% greater specific capacitance than those fabricated using the membrane without GO/SiWLi at 200mVs –1 .

42 ENGINEERING↗

59 Co(p,X) spallation reaction cross sections for 250 MeV to 2 GeV protons

Cobalt is an advantageous target for probing the physics of nuclear spallation, because it is a naturally mono-isotopic element ( 59 Co), and its per-nucleon binding energy (BE/A = 8.768 MeV) is near the maximum value for all nuclei. We measured nuclear spallation cross sections for the 59 Co(p,X) reaction at five kinetic energies ranging from 250 MeV to 2 GeV. Cross sections for the production of 58 Co, 57 Co, 57 Mn, 56 Co, 56 Mn, 56 Cr, 55 Fe, 53 Fe, 54 Mn, 52 Mn, 51 Cr, 49 Cr, 48 V, 47 Sc, 46 Sc, 44 Sc, and 44 Scm are reported. Where comparable data exist in the EXFOR reaction database, we find that our measured cross sections generally agree. In many cases, we provide data for reactions or energies not currently reported in EXFOR. Our cross sections also provide evidence for the presence of α-clusters within the 59 Co nucleus, a surprising result given the asymmetry in Z (27) and N (32) for this nucleus. Finally, we use our measurements to evaluate the accuracy of spallation cross section simulations from GEANT4-based radiation transport toolkit, performed with the INCLXX-, Bertini-, and Binary-ion-cascade (BIC) based physics lists. This benchmarking activity revealed that the simulations overestimated the cross sections by a factor of ∼2–4 on average, and that the INCL-XX physics list provides the most reliable results. This evaluation informs the selection of the GEANT4 physics lists used for the analysis of data from NASA’s Psyche mission, which will measure γ rays and neutrons resulting from spallation reactions occurring on the surface of an asteroid whose surface is thought to be rich in iron-nickel metal.

43 PARTICLE ACCELERATORS↗

Poly(diallylmethylammonium) proton conducting membranes with high ionic conductivity at intermediate temperatures

High temperature proton exchange membrane fuel cells are being lately investigated because of their high energy efficiency, their superior heat/water management, CO tolerance, and electrode reaction kinetics. To further advance this technology, the polymer membrane portfolio and performance should be improved for intermediate or high temperature operation (>100 °C). In this work we present new poly(diallylmethylammonium) proton conducting membranes with high ionic conductivity at 120 °C. First, new protic ionic liquids, hereafter called DAMAH + X - , were synthesized leading to diallylmethylammonium monomers with different counter-anions. By radical cyclopolymerization through thermal and photoinitiation mechanisms, self-standing protic polymeric membranes of poly(diallylmethylammonium X - ) were obtained. Membranes showed good thermal stability (>250 °C) and mechanical properties without the need of additives such as (protic) ionic liquids, solvents or inorganic charges. Great attention was paid to understand the effect of the different counter-anions on the membrane properties. As a general trend, fluorinated anions coming from strong acids confer high ionic conductivity and allow to reduce the hygroscopic properties on the protic polymeric membranes. Proton structural and dynamical stability at different temperatures and humidification conditions were investigated by Neutron Scattering (QENS and NR). The optimized poly(diallylmethylammonium X - ) shows similar ionic conductivity values than Nafion 212 under varying relative humidity conditions at 80 °C. Furthermore, it shows a high ionic conductivity value of 1.9 × 10 -3 Scm -1 at 120 °C under dry conditions.

08 HYDROGEN↗

A causal perspective on reliability assessment

Causality in an engineered system pertains to how a system output changes due to a controlled change or intervention on the system or system environment. Engineered systems designs reflect a causal theory regarding how a system will work, and predicting the reliability of such systems typically requires knowledge of this underlying causal structure. The aim of this work is to introduce causal modeling tools that inform reliability predictions based on biased data sources. We present a novel application of the popular structural causal modeling (SCM) framework to reliability estimation in an engineering application, illustrating how this framework can inform whether reliability is estimable and how to estimate reliability given a set of data and assumptions about the subject matter and data generating mechanism. When data are insufficient for estimation, sensitivity studies based on problem-specific knowledge can inform how much reliability estimates can change due to biases in the data and what information should be collected next to provide the most additional information. We apply the approach to a pedagogical example related to a real, but proprietary, engineering application, considering how two types of biases in data can influence a reliability calculation.

42 ENGINEERING↗

Calorimetric Energies and Chemical Potentials of Metal Atoms in Catalytic Nanoparticles on Oxide and Carbon Supports: Improved Size Dependencies and Adhesion Energies

The chemical potential of metal atoms, μM, in supported metal nanoparticles is an important descriptor related to both the catalytic activity and the stability of the nanoparticles. Here, we derive an expression relating μM to the radius of the particle’s contact area with the support and the adhesion energy at the metal/support interface (E adh ) that assumes the particles have the shape of spherical caps but of arbitrary contact angle with the support (θ c ) and includes an empirical correction for the increase in metal surface energy and adhesion energy with decreasing radius of curvature. We then show that, at any assumed contact angle, we can simultaneously fit previously reported measurements of both calorimetric μ M (from heats of metal vapor adsorption during nanoparticle growth by vapor deposition) versus metal coverage data and the He + low-energy ion scattering (LEIS) intensities for the metal and/or support versus metal coverage (using our recently developed spherical cap model for quantitative LEIS intensities), to determine the particle size versus coverage and E adh . Only one choice of contact angle gives a pair of values for contact angle and E adh , which is consistent with the Young–Dupré equation for the equilibrium shape of a spherical particle. At this equilibrium shape, we then applied this spherical cap model (SCM) to reanalyze microcalorimetric metal chemical potentials and LEIS signals versus coverage data for nine metal/support combinations that were previously analyzed by assuming that the particles had the shape of hemispherical caps, i.e., with a contact angle of 90°. We show that this revised approach gives close agreement with the calorimetric and LEIS data; the best-fit contact angles vary from 64 to 84°, correcting the earlier assumption of 90°. Furthermore, these results provide significant accuracy improvements in particle size versus coverage, metal chemical potential versus size and coverage, metal/support adhesion energies and contact angles for Cu, Ag and Au on CeO 2 (111), Ni on MgO(100), Ag on Fe 3 O 4 (111) and TiO 2 (100), and Ag, Ni and Pd on Ni-supported graphene. This revised approach is much more broadly applicable than the earlier hemispherical cap model (HCM).

99 GENERAL AND MISCELLANEOUS↗

Compartmentalization and Photo-Regulating Pathways for Incompatible Tandem Catalysis

This contribution describes an advanced compartmentalized micellar nanoreactor that possesses a reversible photoresponsive feature and its application towards photo-regulating reaction pathways for incompatible tandem catalysis under aqueous conditions. The smart nanoreactor is based on multi-functional amphiphilic poly(2-oxazoline)s and covalently crosslinked with spiropyran upon micelle formation in water. It responds to light irradiation in a wavelength-selective manner switching its morphology as confirmed by dynamic light scattering and cryo-transition electron microscopy. The compartmental structure renders distinct nanoconfinements for two incompatible enantioselective transformations: a rhodium-diene complex-catalyzed asymmetric 1,4-addition occurs in the hydrophilic corona while a Rh-TsDPEN-catalyzed asymmetric transfer hydrogenation proceeds in the hydrophobic core. Control experiments and kinetic studies showed that the gated behavior induced by the photo-triggered reversible spiropyran to merocyanine transition in the cross-linking layer is key to discriminate among substrates/reagents during the catalysis. Here, the smart nanoreactor realized photo-regulation to direct the reaction pathway to give a multi-chiral product with high conversions and perfect enantioselectivities in aqueous media. Our SCM catalytic system, on a basic level, mimics the concepts of compartmentalization and responsiveness Nature uses to coordinate thousands of incompatible chemical transformations into streamlined metabolic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isopycnal Submesoscale Stirring Crucially Sustaining Subsurface Chlorophyll Maximum in Ocean Cyclonic Eddies

Abstract Mesoscale and submesoscale processes have crucial impacts on ocean biogeochemistry, importantly enhancing the primary production in nutrient‐deficient ocean regions. Yet, the intricate biophysical interplay still holds mysteries. Using targeted high‐resolution in situ observations in the South China Sea, we reveal that isopycnal submesoscale stirring serves as the primary driver of vertical nutrient transport to sustain the dome‐shaped subsurface chlorophyll maximum (SCM) within a long‐lived cyclonic mesoscale eddy. Density surface doming at the eddy core increased light exposure for phytoplankton production, while along‐isopycnal submesoscale stirring disrupted the mesoscale coherence and drove significant vertical exchange of tracers. These physical processes play a crucial role in maintaining the elevated phytoplankton biomass in the eddy core. Our findings shed light on the universal mechanism of how mesoscale and submesoscale coupling enhances primary production in ocean cyclonic eddies, highlighting the pivotal role of submesoscale stirring in structuring marine ecosystems.

Cao, Haijin↗