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At least 1,171 records · Page 65

Fabrication, thermal analysis, and heavy ion irradiation resistance of epoxy matrix nanocomposites loaded with silane-functionalized ceria nanoparticles

This paper describes a detailed understanding of how nanofillers function as radiation barriers within the polymer matrix, and how their effectiveness is impacted by factors such as composition, size, loading, surface chemistry, and dispersion. Here, we designed a comprehensive investigation of heavy ion irradiation resistance in epoxy matrix composites loaded with surface-modified ceria nanofillers, utilizing tandem computational and experimental methods to elucidate radiolytic damage processes and relate them to chemical and structural changes observed through thermal analysis, vibrational spectroscopy, and electron microscopy. A detailed mechanistic examination supported by FTIR spectroscopy data identified the bisphenol A moiety as a primary target for degradation reactions. Results of computational modeling by the Stopping Range of Ions in Matter (SRIM) Monte Carlo simulation were in good agreement with damage analysis from surface and cross-sectional SEM imaging. All metrics indicated that ceria nanofillers reduce the damage area in polymer nanocomposites, and that nanofiller loading and homogeneity of dispersion are key to effective damage prevention. The results of this study represent a significant pathway for engineered irradiation tolerance in a diverse array of polymer nanocomposite materials. Numerous areas of materials science can benefit from utilizing this facile and effective method to extend the reliability of polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct numerical simulation of supercritical oxy-methane mixing layers with CO 2 substituted counterparts

Direct numerical simulations (DNS) of temporally developing, three dimensional, CH 4 /CO 2 , CH 4 /O 2 and CO 2 /O 2 mixing layers, are conducted at a supercritical pressure of 300 atm. To effectively model the supercritical regime, the employed formulation includes the compressible form of the governing equations, the cubic Peng-Robinson equation of state and a generalized formulation for heat and mass flux vectors derived from non-equilibrium thermodynamics and fluctuation theory. A linear inviscid stability analysis is also performed for each case, to determine its most unstable wavelength. Flow visualizations reveal the presence of high density gradient magnitude regions for all three mixing layers, with conditional averages indicating increased presence of heavier fluid species within these regions. No significant departures are observed from perfect gas behavior, with compressibility factors very close to unity for all three mixing cases. Applicability of presumed probability density function methods (PDF) is examined for the three supercritical mixing layers. An a priori analysis is also conducted to investigate various simplifying assumptions employed in modeling various subgrid scale (SGS) flux models. Two additional terms are identified in the large eddy simulations (LES) equations, the gradient of SGS contribution of pressure in the momentum equation and the gradient of SGS contribution of heat flux in energy equation, whose magnitudes are similar and comparable with their respective resolved terms. The performance of the scale similarity model to represent these additional terms is investigated. Lastly, the performance of Smagorinsky, gradient and scale similarity models are also investigated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Kβ X-ray Emission Spectra Analysis Using Bayesian Optimization

The Kβ X-ray emission spectrum of 3 d transition metals is rich with electronic and structural information due to strong exchange interactions with the valence shell of the metal, and has become crucial for understanding their spin and oxidation states. The spectrum is commonly treated using crystal-field multiplet theory, a semi-empirical theory that uses tunable parameters to control the strength of the effects present in X-ray emission spectroscopy (XES). However, determining the experimental values of these parameters remains a challenge. We present a methodology that applies Bayesian optimization to crystal-field multiplet theory to determine parameter values. The algorithm is tested on the X-ray emission spectra of a collection of Mn, Co, and Ni oxides. We are able to find optimal values for the four most impactful parameters: Slater−Condon reduction factors F dd , F pd , and G pd , and crystal field splitting 10 Dq . The algorithm produces significantly improved accuracy compared to current analysis methods, and probes interparameter dependencies by modeling the error landscape. This advancement enhances XES analysis by offering an approach of obtaining quantitative electronic structural information on 3 d transition metal valence shells, facilitating applications across various scientific fields.

Bayesian optimization↗

A dispersive analysis of $$\varvec{\eta '\rightarrow \pi ^+\pi ^-\gamma }$$ and $$\varvec{\eta '\rightarrow \ell ^+\ell ^-\gamma }$$

Abstract We present a dispersive representation of the $$\eta '$$ η ′ transition form factor that allows one to account, in a consistent way, for the effects of $$\rho $$ ρ – $$\omega $$ ω mixing in both the isoscalar and the isovector contributions. Using this formalism, we analyze recent data on $$\eta '\rightarrow \pi ^+\pi ^-\gamma $$ η ′ → π + π - γ to constrain the isovector part of the form factor, individually and in combination with data for the pion vector form factor, which suggests a tension in the $$\rho $$ ρ – $$\omega $$ ω mixing parameter. As a first application, we use our results, in combination with the most recent input for the isoscalar part of the form factor, to predict the corresponding spectrum of $$\eta '\rightarrow \ell ^+\ell ^-\gamma $$ η ′ → ℓ + ℓ - γ , in particular we find the slope parameter $$b_{\eta '}=1.455(24)\,\text {GeV}^{-2}$$ b η ′ = 1.455 ( 24 ) GeV - 2 . With forthcoming data on the latter process, our results establish the necessary framework to improve the evaluation of the $$\eta '$$ η ′ -pole contribution to the anomalous magnetic moment of the muon using experimental input from both $$\eta '$$ η ′ decay channels.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ethylene oxidation on unpromoted silver catalysts: Reaction pathway and selectivity analysis using DFT calculations

Chemical conversions in catalytic partial oxidation processes of light hydrocarbons are responsible for the production of numerous industrial chemicals, plastics, and intermediates. These processes are relatively expensive to perform, and are typically operated at high thermodynamic inefficiency, so the development of novel, highly efficient catalysts would prove to be very cost effective. Herein, our study focused on surface catalytic mechanisms of the ethylene oxide (EO) formation process. Periodic plane-wave Density Functional Theory (DFT) methods were used to analyze related reaction mechanisms on the Ag(111) surface facet with low coverage. Energetic changes of related species and pathways were calculated. Key surface species are identified to suggest the factors for the observed selectivity during EO formation. Our results are consistent with previous kinetic modeling efforts in the literature which did not employ DFT analysis. Lastly, our study demonstrates how fundamental theoretical investigations and multi-scale modeling techniques are currently impacting the advancement of rational catalyst design and microkinetic modeling techniques in the light hydrocarbon processing industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tensile testing and fracture mechanism analysis of polyvinyl alcohol nanofibrous webs

Abstract A tensile properties testing study was conducted to understand the influence of thickness, cross‐head speed (speed of testing), gauge length (GL; specimen test length), and sample shape on important tensile properties of polyvinyl alcohol (PVA) nanofiber webs. The effects of each testing parameter on load at break, extension at break, Young's modulus, and tensile stress–strain curve of PVA nanofiber webs are analyzed. The Welch two sample t ‐tests show the significant difference among tested data. Using interaction plots, two‐way analysis of variance, and margin mean plots, the interaction effects among testing parameters have been analyzed. Of all the factors, cross‐head speed, the interaction among GL, and sample thickness (GL: Thickness) and the interaction among GL, testing speed and sample thickness (GL: Speed: Thickness) have significant influence on the tensile properties of PVA nanofiber webs. Moreover, the hypothesized model of mechanism of tensile strain–stress curve of PVA nanofiber webs has been proposed. Based on the model, the tensile strain–stress curve can be split into three stages: linear elastic, partial break up, and complete breakage. This study will provide a better understanding of tensile testing parameters' effects and their interaction effects on the tensile properties of nanowebs.

Lou, Lihua↗

Numerical and experimental analysis of precooled desiccant system

This paper presents a numerical and experimental study of four novel, desiccant air-conditioning systems based on pre-cooling of the ambient air. The purpose of the study is to: 1) establish which configuration is most profitable for the future studies through numerical and experimental methods; 2) verify the concept of precooled system and confirm that it is working in experimental conditions (for this purpose two prototypes of evaporative cooling units were developed and compared for different operation arrangements with desiccant wheel); 3) Analyze practical aspects of the systems, which includes water consumption analysis, economic analysis and establishing operational modes during a cooling season in temperate climate conditions (the proposed solution has a significant advantage during operation in a temperate climate, since it can utilize its first evaporative cooler the only source of cooling energy when the humidity of outdoor air allows to to meet the latent cooling load). Four arrangements of the system with different dew point evaporative air cooler prototypes were selected and developed for comparative analysis. The system was simulated as a whole, also, each component was individually tested on measurement station. develop the optimal arrangement of the system through numerical and experimental analysis. Four different performance indicators were considered: thermal COP (Coefficient Of Performance), the ERR (Energy Efficiency Ratio), coefficient a describing the potential in compensating indoor cooling loads, water consumption ratio. Also costs of the systems were compared through economic analysis. It was established that arrangement which is characterized by best-averaged performance in terms of all considered factors is a unit combined with two different types of evaporative coolers (marked as System B)- this is caused by the favorable arrangement of two units, where one is better suited to the pre-cooler role, while the other is better suited as the post-cooler.

42 ENGINEERING↗

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes can rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but few have been shown to hydrolyze synthetic polyamides. Here, in this work, we synthesized and characterized a panel of 95 enzymes from the N-terminal nucleophile hydrolase superfamily with 30%–50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, but there was no relationship between phylogeny and activity, nor any evidence of prior evolutionary selection for nylon hydrolysis. Several newly identified hydrolases showed substrate selectivity, generating up to 20-fold higher product titers with nylon-6,6 versus nylon-6. However, the yield was still less than 1%, necessitating further optimization before potential applications. Finally, we determined the crystal structure and oligomerization state of a nylon-6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases.

nylon↗

Selective pseudocapacitive immobilization of REE elements on carbon based electrodes

Current extraction technologies for rare earth elements at ambient conditions are reagent and energy intensive, giving rise to significant quantities of secondary waste streams. Exploration of the removal of common cations from aqueous streams has been undertaken with carbon materials and have shown promising results. However, those promising materials have not been explored extensively for rare earth element capture from aqueous process streams. In this study, a carbon electrode was investigated for the adsorption and immobilization of REE elements from aqueous solutions. Cyclic voltammetry studies of the carbon electrode displayed a pseudocapacitive behavior where it was verified that cation adsorption is accompanied by an electron transfer process. Preliminary tests showed that a current density of 89.1 mA. g -1 , allowed for the pseudocapacitive adsorption (PSA) of Nd 3+ cation without the formation of rare earth hydroxides. Hence, the selective PSA of Nd 3+ was verified in an electrolyte solution with equimolar concentrations of Nd 3+ , Mg 2+ , Li + , Na + and K + , achieving separation factors of 8.6, 1.1, and 10.9 for Nd 3+ /Li + , Nd 3+ /Na + , and Nd 3+ /Mg 2+ , respectively. Analysis of the potential-time curves for the various cations suggests that storage of ions in the electrode involved pore-spacings rather than interlayer spacings and was corroborated by XRD analysis. Specific capacitance as high as >640 F.g -1 for Nd 3+ was also observed for the carbon electrode, with Faradaic efficiencies (FE) of > 20% for Nd 3+ and Mg 2+ , and > 9% for Na + . Furthermore, adsorption capacity of >125 mg g -1 after 4hrs of electrosorption was observed for Nd 3+ . In the presence of the Nd 3+ electrolyte, the electrode achieved increasing storage of Nd 3+ with >94% retention of Nd 3+ with a FE > 20% over 6 cycles between loading and releases in 1 M KCl solution. In conclusion, these preliminary results provide information and some guidance on the selective recovery of rare earth elements, such as Nd, in aqueous streams in the presence of competitive cations employing the use of carbon-based materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗

Mitigation of shunt in poly -Si/SiO$_{x}$ passivated interdigitated back contact monocrystalline Si solar cells by self-aligned etching between doped fingers

Polycrystalline silicon on silicon oxide (poly-Si/SiO x ) passivating contacts can be used for ultra-high-efficiency interdigitated back contact (IBC) monocrystalline silicon solar cells. We evaluate the use of intrinsic poly-Si for the region that isolates the p- and n-type fingers at the back side of IBC devices. To mitigate shunt across the isolation region between the doped p- and n-type fingers, we demonstrate self-aligned subtractive processing by etching the poly-Si in the isolation region using SF6 plasma followed by etching in a tetramethylammonium hydroxide (TMAH) solution. After removal of the poly-Si, the isolation region was passivated with SiN x and Al 2 O 3 , which resulted in an 11.7% increase in the fill factor in a 19.8% efficient device. Furthermore, we evaluate the limitations of this device through Suns-V oc analysis and simulations using SunSolve and Quokka3 solar cell simulation software. Through Quokka3, we show that the most significant efficiency losses come from junction recombination current (J 02 ) in the isolation region between doped fingers. We predict that the cell efficiency can be most improved with reduced J 02 through better isolation of heavily doped fingers by etching the isolation region deeper into the bulk or through enhanced surface chemical passivation in this region.

14 SOLAR ENERGY↗

Characterization of Electronic Stress-Induced Changes in Multilayer MoS 2

Transition metal dichalcogenides like molybdenum disulfide (MoS 2 ) are compelling for next-generation electronic devices. In this work, we investigate the impact of electronic stress on MoS 2 to illustrate that observational and phenomenological information on multiple devices can be useful to describe changes in the device, and caution against the rationalization of paltry results as representative or correlative to device behavior. Here, we stress MoS 2 by applying a sustained 20 V DC bias to study the material’s response. Post-stress electronic characterization revealed nonuniform shifts in current–voltage (I–V) behavior alongside microscale changes. Complementary mechanical, spectroscopic, and scanning microwave impedance measurements showed that stress-induced features locally modulate stiffness, surface potential, Raman intensity, and charge carrier density. We correlated I–V behavior with morphological features (wrinkles, tears, folds, height) and device-level geometry (MoS 2 overlap with electrodes, channel area, contact length) on 50 test structures across five chips to move beyond anecdotal conclusions. We found no universal correlations before DC stress. However, device-level geometry was correlated with I–V behavior after DC stress, suggesting that electrode contacts play a more dominant role than morphology in determining performance. Delamination and thinning induced by DC stress led to localized reductions in charge carrier density within the affected regions. Further, delamination and thinning appear to map to I–V device performance in a few samples, but the correlation is lost when a larger sample size is considered. This suggests significant sample-to-sample variability in surface electronic states of the test structures. We also discuss how environmental factors introduced during fabrication may contribute to the observed heterogeneous device response. Progress will require high-resolution, multimodal analysis across many samples constructed under controlled, clean conditions. By building data sets that capture variability, we can better identify the true drivers of performance.

36 MATERIALS SCIENCE↗

Chemical Robotics Enabled Exploration of Stability in Multicomponent Lead Halide Perovskites via Machine Learning

Metal halide perovskites have attracted immense interest as a promising material for a variety of optoelectronic and sensing applications. However, issues regarding long-term stability have emerged as the key bottleneck for commercialization. Here, we develop an automated experimental workflow based on combinatorial synthesis and rapid throughput characterization to explore long-term stability of these materials in ambient conditions. We apply it to four model perovskite systems: MA x FA y Cs 1–x–y PbBr 3 , MA x FA y Cs 1–x–y PbI 3 , Cs x FA y MA 1–x–y Pb(Br x+y I 1–x–y ) 3 , and Cs x MA y FA 1–x–y Pb(I x+y Br 1–x–y ) 3 . Non-negative matrix factorization and Gaussian process regression are used to interpolate the photoluminescent behavior of the phase diagram. This interpolative regression analysis helps to distinguish mixtures that form solid solutions from those that segregate into multiple materials, pointing out the most stable regions of the phase diagram. Here, we find stability dependence on composition to be nonuniform within the composition space, suggesting the presence of potential preferential compositional regions. This proposed workflow is universal and can be applied to other solution-processable materials.

36 MATERIALS SCIENCE↗

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗

Tau PET positivity in individuals with and without cognitive impairment varies with age, amyloid-β status, APOE genotype and sex

Abstract Tau positron emission tomography (PET) imaging allows in vivo detection of tau proteinopathy in Alzheimer’s disease, which is associated with neurodegeneration and cognitive decline. Understanding how demographic, clinical and genetic factors relate to tau PET positivity will facilitate its use for clinical practice and research. Here we conducted an analysis of 42 cohorts worldwide (N = 12,048), including 7,394 cognitively unimpaired (CU) participants, 2,177 participants with mild cognitive impairment (MCI) and 2,477 participants with dementia. We found that from age 60 years to 80 years, tau PET positivity in a temporal composite region increased from 1.1% to 4.4% among CU amyloid-β (Aβ)-negative participants and from 17.4% to 22.2% among CU Aβ-positive participants. Across the same age span, tau PET positivity decreased from 68.0% to 52.9% in participants with MCI and from 91.5% to 74.6% in participants with dementia. Age, Aβ status,APOEε4 carriership and female sex were all associated with a higher prevalence of tau PET positivity across groups.APOEε4 carriership in CU individuals lowered the age at onset of both Aβ positivity and tau positivity by decades. Finally, we replicated these associations in an independent autopsy dataset (N = 5,072 from 3 cohorts).

Neurosciences & Neurology↗

An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part I: Flux and Eigenvalue Solutions

Computing in the energy dimension is one of the greatest challenges confronting present-day deterministic neutron transport solvers. Accurately resolving the neutron flux as neutrons downscatter across resonances in the nuclear cross sections currently requires considerable computing power and suffers from approximation errors. Flux uncertainty resulting from the uncertainty of the resonance structure is the single-largest cause of reactivity uncertainty. Any additional reference solution for the critical neutron downscattering problem with resonance phenomena would be a boon to verification and validation of neutronics codes. This paper establishes a benchmark to verify the accuracy of neutron transport criticality solvers along the energy dimension. For the first time, the analytic solution of the flux amplitude is derived in the particular case of an infinite homogeneous medium with isotropic scattering in the center of mass and an arbitrary number of no-threshold, neutral particle reaction resonances (e.g., radiative capture, fission, and resonance scattering). Furthermore, original analytic expressions are established to quantify the discrepancy between the ψ k (E) and ψ α (E) flux amplitudes, respective solutions of the multiplication factor k, or the exponential time-evolution frequency α eigenproblems. The physical study of these relations led to analysis of their first-order relative difference near the criticality condition α=0. Finally, numerical solutions are provided to a benchmark problem constituted of the first resonance of 239 Pu, the 6.67-eV resonance of 238 U, and a scattering isotope with a flat cross section, allowing for the computational verification of the energy resolution of current neutron transport criticality codes. Through these novel results, this analytic benchmark can serve as a reference to verify the energy resolution and sensitivity analysis of neutron transport criticality calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Design and Analysis of the Open-Surface Slow Li Flow Divertor and Comparison to the Fast Li Flow Divertor

In the ongoing U.S. project, “Liquid Metal Plasma Facing Components,” sponsored by the U.S. Department of Energy, efforts have been taken to develop two open-surface divertor designs for the Fusion Nuclear Science Facility using liquid lithium (Li) as a heat and particle flux removal media. The main focus of this study is the design and analysis of a slow (~1 mm/s) and thin (<1 mm) open-surface Li flow divertor with a Li-cooled substrate, which is then compared with an earlier design of a fast (up to 10 m/s) and thick (~0.5 cm) Li flow divertor with the substrate cooled with helium. The slow Li flow divertor design is based on the original LiWall concept developed at the Princeton Plasma Physics Laboratory. Such a thin and slow Li layer can remove the particle flux by reducing the recycling flux, while the heat flux is removed mainly through the heat sink located beneath. In the present study, the heat sink is provided through a Li cooling flow inside the substrate of reduced activation ferritic/martensitic steel. By performing a multiphysics analysis with COMSOL that included liquid-metal magnetohydrodynamics (MHD), heat transfer, and structural mechanics, the impact of various factors on the divertor heat removal capability, such as Li flow velocity, MHD effects, and inlet velocity boundary condition, were examined. Based on comparisons of the two divertor designs, it was shown that the fast-flow divertor significantly outperformed the slow-flow design, whose heat removal capability was limited to ~1 to 2 MW/m2.

Jiang, Yuchen [ORNL] (ORCID:0000000283280284)↗

Recent developments in 3D-printed membranes for water desalination

The recognition of membrane separations as a vital technology platform for enhancing the efficiency of separation processes has been steadily increasing. Concurrently, 3D printing has emerged as an innovative approach to fabricating reverse osmosis membranes for water desalination and treatment purposes. This method provides a high degree of control over membrane chemistry and structural properties. In particular, when compared to traditional manufacturing techniques, 3D printing holds the potential to expedite customization, a feat that is typically achieved through conventional manufacturing methods but often involves numerous processes and significant costs. This review aims to present the current advancements in membrane manufacturing technology specifically tailored for water desalination purposes, with a particular focus on the development of 3D-printed membranes. A comprehensive analysis of recent progress in 3D-printed membranes is provided. However, conducting experimental work to investigate various influential factors while ensuring consistent results poses a significant challenge. To address this, we explore how membrane manufacturing processes and performance can be effectively pre-designed and guided through the use of molecular dynamics simulations. Finally, this review outlines the challenges faced and presents future perspectives to shed light on research directions for optimizing membrane manufacturing processes and achieving optimal membrane performance.

3D printing membranes↗