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At least 235 records · Page 13

Bifurcation Analysis Reveals Solution Structures of Phase Field Models

The phase field method is playing an increasingly important role in understanding and predicting morphological evolution in materials and biological systems. Here, in this study, we develop a new analytical approach based on the bifurcation analysis to explore the mathematical solution structure of phase field models. Revealing such solution structures not only is of great mathematical interest but also may provide guidance to experimentally or computationally uncover new morphological evolution phenomena in materials undergoing electronic and structural phase transitions. To elucidate the idea, we apply this analytical approach to three representative phase field equations: the Allen-Cahn equation, the Cahn-Hilliard equation, and the Allen-Cahn-Ohta-Kawasaki system. The solution structures of these three phase field equations are also verified numerically by the homotopy continuation method.

97 MATHEMATICS AND COMPUTING↗

The application of synchrotron micro-computed tomography to characterize the three-dimensional microstructure in irradiated nuclear fuel

This research demonstrated the first time that synchrotron X-ray micro-computed tomography (μ-CT) was utilized to analyze the three-dimensional (3-D) morphology of the microstructure of irradiated nuclear fuel. Both absorption contrast and propagation-based phase contrast enhanced μ-CT techniques were evaluated. Porosity and phase region volumes were determined in neutron irradiated uranium 10 wt.% zirconium (U-10Zr) using propagation-based phase contrast enhanced μ-CT. Volumes were determined by image processing software and algorithms, with the porosity volume subsequently compared to the ASTM E562 method. The 3-D porosity of a small region (~ 8 x 10 5 µm 3 ) located in the intermediate fuel redistribution zone that was removed via a focused ion beam was determined to be 7.2% via image processing. A detailed 3-D analysis of the porosity with respect to volume and morphology was provided. Five growth stages of pore evolution were observed including: nucleation, growth, coalescence, interconnected porosity, and extended/interconnected porosity. Four distinct phase regions were identified, including the pores, via both absorption contrast and propagation-based phase contrast enhanced μ-CT. A quantitative comparison of fuel swelling between this localized microscopic U-10Zr fuel region, previously irradiated in the Fast Flux Test Facility, and historic U-10Zr fuels irradiated in the Experimental Breeder Reactor-II (EBR-II) was conducted. It was determined that for similar burnups, the localized swelling in this microscopic fuel region was 7.7%, which was approximately one-half of the value of the macroscopic swelling reported in EBR-II irradiated fuel. With the advent of new specimen preparation tools for irradiated materials, as well as advances in characterization techniques, researchers can now obtain previously inaccessible microstructural insight into irradiated fuels. This possibility naturally lends itself to improved fuel performance models for the nuclear community.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sputter coating of Nb₃Sn into SRF cavity using stoichiometric target

Nb₃Sn has emerged as a leading alternative material due to its higher superconducting critical temperature (Tc) and superheating field (Hsh), promising a viable solution to the intrinsic performance limit currently faced by Nb superconducting radiofrequency (SRF) cavities. We sputter-coated Nb₃Sn inside Nb SRF cavity using a stoichiometric Nb₃Sn tube target in a DC cylindrical magnetron sputter coater. The target was fabricated by growing an estimated >20 μm thick Nb₃Sn layer on a Nb tube via Sn vapor diffusion using Jefferson Lab’s coating system. Approximately 150 nm thick Nb-Sn films were sputter-deposited onto flat Nb samples at positions representing the beam tubes and equator of a 2.6 GHz Nb cavity. Post-deposition annealing at 950 °C for 3 h resulted in the formation of Nb₃Sn. Microstructural analysis of the annealed films was carried out to investigate the morphology and structure of the Nb₃Sn films. Later, a 2.6 GHz Nb SRF cavity was coated with a ~1.2 μm thick sputtered Nb-Sn film using a stoichiometric Nb₃Sn target, followed by annealing. Cryogenic RF testing of the annealed cavity demonstrated a Tc of 17.8 K, indicating the formation of Nb₃Sn. After a light Sn recoating treatment, the cavity achieved a quality factor (Q0) of 6.7E+08 at lower field at 2.0 K.

Accelerator Physics↗

Alternate InP synthesis with aminophosphines: solution–liquid–solid nanowire growth

Indium phosphide nanowires are important components in high-speed electronics and optoelectronics, including photodetectors and photovoltaics. However, most syntheses either use high-temperature and costly vapor-phase methodology or highly toxic and pyrophoric tris(trimethylsilyl)phosphine. To expand on the success of the aminophosphine-based InP colloidal quantum dot synthesis, we developed a synthesis for thin (~11 nm) zinc blende InP nanowires at 180 °C using indium tris(trifluoroacetate) and tris(diethylamino)phosphine. A flat nanoribbon morphology was identified by transmission electron and atomic force microscopy analysis, with the stoichiometric (110) lattice plane exposed. Nanowire growth proceeded through a solution–liquid–solid mechanism from in situ-formed indium metal nanoparticles. Molecular byproducts of tris(oleylamino)phosphine oxide and N-oleyltrifluoroacetamide observed by 31 P and 19 F NMR spectroscopy inform a proposed mechanism of indium reduction by the aminophosphine. Morphological control over the nanowire product was achieved by varying the phosphorus injection to control the aspect ratio, the In : P ratio to toggle between nanowires and multipods, and the pre-hot injection evacuation step to favor a quantum dot product. Furthermore, replacing the indium precursor with indium tris(trifluoromethanesulfonate) was found to make bulk zinc blende InP nanowires with an average diameter of >250 nm and tens of microns in length.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Fraction of broad absorption line quasars in different radio morphologies

ABSTRACT In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample of sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalogue and Very Large Array (VLA)-Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey. Using the radio cut-out images from the FIRST survey, we first designed a deep-learning model using convolutional neural networks (CNN) to classify the quasar radio morphologies into the core-only, young jet, single lobe, or triples. These radio morphologies are further sub-classified into core-dominated and lobe-dominated sources. The CNN models can classify the sources with a high precision of >98 ${{\ \rm per\ cent}}$ for all the morphological sub-classes. The average BAL fraction in the resolved core, core-dominated, and lobe-dominated quasars are consistent with the BAL fraction inferred from radio and infrared surveys. We also present the distribution of BAL quasars as a function of quasar orientation by using the radio core-dominance as an orientation indicator. A similar analysis is performed for HiBALs, LoBALs, and FeLoBALs. All the radio morphological sub-classes and BAL sub-classes show an increase in BAL fraction at high orientation angles of the jets with respect to the line of sight. Our analysis suggests that BAL quasars are more likely to be found in viewing angles close to the equatorial plane of the quasar. However, a pure orientation model is inadequate, and a combination of orientation and evolution is probably the best way to explain the complete BAL phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗

A Simple Approach for the Synthesis of Cellulose Nanofiber Reinforced Chitosan/PVP Bio Nanocomposite Film for Packaging

The development of chitosan-based food packaging film has been increasing due to its wider availability, biodegradability, low-cost, and renewability. The purpose of this study was to develop cellulose nanofibers (CNFs) reinforced Chitosan/PVP(CHP) green bio nanocomposite film by solvent casting method with enhanced barrier and mechanical property. CNFs of dimension 9–11 nm and 100–200 nm were extracted from jute fibers by directly treating it with HNO{sub 3}–NaNO{sub 2} mixture. Bio nanocomposite films were synthesized with various concentrations of CNFs and evaluated using SEM, TGA/DTG and XRD to analyze the morphology, thermal behavior and crystallinity of bio nanocomposite films. SEM analysis revealed the uniform dispersion of CNFs in CHP matrix. Thermal stability of prepared bio nanocomposite films was improved with the loading of 5 wt% of cellulose nanofibers. ATR(FT-IR) spectra shows physical interaction between all the components of bio nanocomposite film. The bio nanocomposite films were also characterized for physical property like thickness, mechanical testing and barrier properties. The addition of CNFs significantly enhanced the mechanical property of bio nanocomposite films. Furthermore, water and oxygen transmission rate of bio nanocomposite film decreased with the increase in CNFs concentration. Overall the performed studies confirmed, the use of CNFs in polymer matrix makes it possible to produce a flexible, transparent, thermally stable bio nanocomposite film with enhanced mechanical and barrier properties for food packaging applications.

36 MATERIALS SCIENCE↗

Microstructure and mechanical properties of friction stir weld performed on neutron-irradiated 304L steel with helium

As nuclear power plants (NPPs) approach or exceed 40–60 years of service, it may become necessary to repair damaged neutron-irradiated components to prolong longevity. However, fusion welding repair of irradiated steels and metallic materials is challenging because of helium-induced cracking. This study used friction stir welding (FSW) to address helium-related issues, such as helium bubble formation and grain boundary cracking. The microstructure, helium-induced degradation, and mechanical properties of a friction stir weld produced on neutron-irradiated 304L stainless steel with approximately 5.2 appm of helium were characterized. The analysis focused on variations in grain size, texture, and the morphology of helium-induced damage in the friction stir weld. Mechanical properties were characterized on the irradiated base metal (BM) and metallurgical zones of the friction stir weld: the stir zone (SZ), the thermo-mechanically affected zone (TMAZ), and the heat affected zone (HAZ). Only minor scattered porosity in the SZ and TMAZ and a few short microcracks (below 20 μm in length) in the TMAZ were observed, indicating limited helium-induced degradation. Tensile tests revealed good mechanical properties and fractography analysis demonstrated predominantly ductile fracture. In conclusion, the results highlight the immediate and substantial benefits of the FSW approach for repairing or joining helium-containing irradiated materials in NPPs.

36 MATERIALS SCIENCE↗

Stress-controlled fatigue of HfNbTaTiZr high-entropy alloy and associated deformation and fracture mechanisms

The stress-controlled fatigue tests are carried out at a stress ratio of 0.1 and a frequency of 10 Hz, and span both low-cycle and high-cycle regimes by varying the applied stress amplitudes. The high-cycle fatigue regime gives a fatigue strength of 497 MPa and a fatigue ratio of 0.44. At equivalent conditions, the alloy's fatigue strength is greater than all other high-entropy alloys (HEAs) with reported high-cycle fatigue data, dilute body-centered cubic alloys, and many structural alloys such as steels, titanium alloys, and aluminum alloys. Through in-depth analyses of crack-propagation trajectories, fracture-surface morphologies and deformation plasticity by means of various microstructural analysis techniques and theoretical frameworks, the alloy's remarkable fatigue resistance is attributed to delayed crack initiation in the high-cycle regime, which is achieved by retarding the formation of localized persistent slip bands, and its good resistance to crack propagation in the low-cycle regime, which is accomplished by intrinsic toughening backed up by extrinsic toughening. Additionally, the stochastic nature of the fatigue data is neatly captured with a 2-parameter Weibull model.

36 MATERIALS SCIENCE↗

Impact of electrode thick spot irregularities on polymer electrolyte membrane fuel cell initial performance

Polymer electrolyte membrane fuel cells have great potential for power generation in many applications, but to implement them on a larger scale, understanding of quality requirements, tolerances, and controls during manufacturing must improve. As part of this broad challenge, irregularities resulting from the membrane electrode assembly production process must be studied to determine if they impact the performance of the cell. One potential irregularity is a locally increased thickness of the coated or deposited electrode. In order to understand and provide insight into the impact of such irregularities, we intentionally created thick spots in the center of cathode electrodes. The thick spots fabricated by two different approaches were carefully characterized by optical microscopy, X-ray fluorescence spectroscopy and scanning electron microscopy (SEM). We found that the impact of the thick spots on the electrochemically active catalyst area and mass activity was minimal. However, specific electrode thick spot irregularities significantly impacted the mass transport properties of the cells. Based on SEM analysis, the likely cause of the performance drop is morphological changes associated with the creation of the thick spot irregularity. Spatial performance results obtained with a segmented cell system further indicated that the area of the performance impact exceeded that of the intentionally created thick spot.

25 ENERGY STORAGE↗

Grain subdivision and structural modifications by high-energy heavy ions in UO 2 with different initial grain size

Irradiation with 84 MeV Xe ions at peak fluence above 7 × 10 17 ions/cm 2 has been carried out on two UO 2 samples with different initial grain sizes at 300 °C and 500 °C. Characterization of both grain structure and bubble morphology has been performed using transmission electron microscopy, image analysis and precession electron diffraction. The bubble size in the large-grained sample was smaller than that in the standard-grain sample, confirming fission gas precipitation resistance in the former. The ion irradiation in the high electronic energy deposition range has caused formation of a large density of dislocations which resulted in grain polygonization for the sample with standard grain size, which was observed in multiple lamellas extracted next to each other at peak dose. The sample with large grains showed inconsistent behavior. In one case, dislocation pile-up occurred, but no sub-grain formation was observed. An adjacent location showed sub-grain formation, even if to less extent compared to the standard grain-size sample. Furthermore, these findings suggest a limited polygonization resistance in large-grained UO 2 compared to standard-grain UO 2 . Recrystallization of both sample surfaces was present, leaving unclear if this is a surface effect or a consequence of the highest energy deposition rate in this area.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SAF Combustion & Soot Processes [Slides]

The atomization, mixing, combustion and emissions characteristics of aviation fuels were measured using a novel approach based on a non-continuous injection scheme called the single-hole atomizer (SHA). High-speed microscopy revealed differences between fuels in terms of evaporation and mixing regimes over conditions relevant to modern and next generation aero-engine combustors. Measurements of liquid and vapor penetration, mixing fields, combustion and emissions metrics (ignition delay, lift-off length, PAH formation, soot mass) highlighted the effects of fuels and combustor conditions. The experimental results are being leveraged to adjust and validate chemical and CFD models. Detailed analysis of sampled soot showed subtle differences in soot morphology between fuels. The results revealed the presence of contaminants potentially affecting surface chemistry and the nucleation propensity of water droplets on particles. Chemical mechanisms for NJFCP A-2, C-1 and C-4 showed good performance over a large parameter space. Spray breakup at relight conditions is vastly different from the atomization observed at high pressure. CFD simulations of the SHA target conditions confirmed the good behavior of the C-1 kinetic mechanism. The simulations support the strong relationship between low and high temperature reactions. New altitude chamber facility to enable detailed characterization of the heterogeneous nucleation process of water on aerosol particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Urban morphology and urban water demand: a case study in the land constrained Los Angeles region using urban growth modeling

The interactions between population growth, urban morphology, and water demand have important implications for water resources and supply in urban regions. Water use for irrigation comprises a significant fraction of urban water demand, and is potentially influenced by long-term changes in urban morphology. To investigate this, we used spatially explicit projections of urban land development intensity (fraction impervious area) generated from a 30 m resolution urban growth model for the Los Angeles (LA) region. Recent historical data on water use and high resolution landcover were used to establish relationships between green area, urban development intensity, and outdoor water demand. These relationships were then used to project outdoor and total water demand in 2100 using the urban growth model outputs. We considered two different population scenarios informed by the shared socioeconomic pathway (SSP) projections for the region (SSP3 and SSP5), and three scenarios of urban development intensification. Our analysis is resolved for over 80 water providers in the region, from the urban core to suburban fringe, and highlights diverse demand responses influenced by initial urban form and water demand attributes. Assumptions about outdoor water use factors based on recent water supply data were found to be nearly as influential on future outdoor demand as the urban growth scenario settings. Compared to previous studies, our work is unique in coherently linking high resolution SSP population scenarios, urban land cover evolution, and urban water demand projections, demonstrating the approach for the LA region—the largest population center in the western United States.

54 ENVIRONMENTAL SCIENCES↗

Unveiling Morphology and Crystallinity Dynamics in Ni x Mn 1– x CO 3 Cathode Precursors through Batch-Mode Coprecipitation

This study delves into the synthesis and control of Ni x Mn 1–x CO 3 , a critical class of Mn-rich, Co-free precursors vital for cathode-oxide materials in energy storage and conversion technologies. Employing batch-mode coprecipitation, we systematically generated samples with varying Ni concentrations (x = 0, 0.1, 0.3, 0.5, 0.7, and 0.9) and conducted a comprehensive analysis of their compositions, crystallinities, transition-metal distributions, and particle morphologies through both experimental and computational methods. A significant variation in particle size and crystallinity was observed, contingent on the Ni content. Further, a pivotal transition emerged at Ni concentrations above x = ~0.5, transforming uniform morphologies, such as spherical, monodisperse, pseudo-single-crystalline particles, into bimodal, polycrystalline structures. Furthermore, the study highlights the role of Ni–ammonia complexes leading to Ni-deficient precipitates and underscores the importance of ammonia concentration in achieving precise Ni content control. This study unveils critical reaction conditions governing Mn-rich precursor properties that are vital for cathode-oxides, emphasizing the need for meticulous synthetic control and offering the potential for practical applications in advanced energy storage and conversion systems.

25 ENERGY STORAGE↗

Fractionation of Lignin for Selective Shape Memory Effects at Elevated Temperatures

We report a facile approach to control the shape memory effects and thermomechanical characteristics of a lignin-based multiphase polymer. Solvent fractionation of a syringylpropane-rich technical organosolv lignin resulted in selective lignin structures having excellent thermal stability coupled with high stiffness and melt-flow resistance. The fractionated lignins were reacted with rubber in melt-phase to form partially networked elastomer enabling selective programmability of the material shape either at 70 °C, a temperature that is high enough for rubbery matrix materials, or at an extremely high temperature, 150 °C. Utilizing appropriate functionalities in fractionated lignins, tunable shape fixity with high strain and stress recovery, particularly high-stress tolerance were maintained. Detailed studies of lignin structures and chemistries were correlated to molecular rigidity, morphology, and stress relaxation, as well as shape memory effects of the materials. The fractionation of lignin enabled enrichment of specific lignin properties for efficient shape memory effects that broaden the materials’ application window. Electron microscopy, melt-rheology, dynamic mechanical analysis and ultra-small angle neutron scattering were conducted to establish morphology of acrylonitrile butadiene rubber (NBR)-lignin elastomers from solvent fractionated lignins.

36 MATERIALS SCIENCE↗

Molecular phylogenetic analysis of the Paguristes tortugae Schmitt, 1933 complex and selected other Paguroidea (Crustacea: Decapoda: Anomura)

Morphological characters, as presently applied to describe members of the Paguristes tortugae Schmitt, 1933 species complex, appear to be of limited value in inferring phylogenetic relationships within the genus, and may have similarly misinformed understanding of relationships between members of this complex and those presently assigned to the related genera Areopaguristes Rahayu & McLaughlin, 2010 and Pseudopaguristes McLaughlin, 2002. Previously undocumented observations of similarities and differences in color patterns among populations additionally suggest genetic divergences within some species, or alternatively seem to support phylogenetic groupings of some species. In the present study, a Maximum Likelihood (ML) phylogenetic analysis was undertaken based on the H3, 12S mtDNA, and 16S mtDNA sequences of 148 individuals, primarily representatives of paguroid species from the western Atlantic. This molecular analysis supported a polyphyletic Diogenidae Ortmann, 1892, although incomplete taxonomic sampling among the genera of Diogenidae limits the utility of this finding for resolving family level relationships. Several hypotheses regarding the evolutionary relationships among hermit crab genera were refuted by the Kishino-Hasegawa (KH). ShimodairaHasegawa (SH) and Approximately Unbiased (AU) tree topology tests, among them the hypothesis that Areopaguristes is monophyletic. A lack of support for the monophyly of Areopaguristes calls into question the phylogenetic validity of gill number for the differentiation of Paguristes, Areopaguristes, and Pseudopaguristes. The study was inconclusive with regard to the relationships among these three genera, but previously unknown diversity within both Paguristes and Areopaguristes was demonstrated. Existence of an undescribed species confounded under the name Paguristes tortugae Schmitt, 1933 was supported by genetics, morphology, and coloration. A second undescribed species with remarkable similarity to Areopaguristes hummi Wass, 1955 was discovered based on genetics and coloration.

12S↗

Development of liquid cells for high resolution imaging and chemical analysis in situ with Transmission Electron Microscopy

The development of liquid cells for transmission electron microscopy (TEM) have enabled breakthroughs in the study of nanoscale structural, morphological, or chemical changes during materials growth and applications [1]. The challenges of achieving high resolution imaging and chemical analysis through liquids often arise from the liquid cells being too thick. Making ultra-thin freestanding membranes and controlling the liquid thickness are some of the key attributes to the recent liquid cell developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗