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At least 127 records · Page 7

Theoretical Investigations on the Plasmon-Mediated Dissociation of Small Molecules in the Presence of Silver Atomic Wires

Plasmonic nanoparticles can promote bond activation in adsorbed molecules under relatively benign conditions via excitation of the nanoparticle’s plasmon resonance. As the plasmon resonance often falls within the visible light region, plasmonic nanomaterials are a promising class of catalysts. However, the exact mechanisms through which plasmonic nanoparticles activate the bonds of nearby molecules are still unclear. Herein, we evaluate Ag 8 –X 2 (X = N, H) model systems via real-time time-dependent density functional theory (RT-TDDFT), linear response time-dependent density functional theory (LR-TDDFT), and Ehrenfest dynamics in order to better understand the bond activation processes of N 2 and H 2 facilitated by the presence of the atomic silver wire under excitation at the plasmon resonance energies. We find that dissociation is possible for both small molecules at high electric field strength. Activation of each adsorbate is symmetry- and electric field-dependent, and H 2 activates at lower electric field strengths than N 2 . Furthermore, this work serves as a step toward understanding the complex time-dependent electron and electron–nuclear dynamics between plasmonic nanowires and adsorbed small molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tale of Three Molecular Nitrides: Mononuclear Vanadium (V) and (IV) Nitrides As Well As a Mixed-Valence Trivanadium Nitride Having a V 3 N 4 Double-Diamond Core

Here, transmetallation of [VCl 3 (THF) 3 ] and [TlTp tBu,Me ] afforded [(Tp tBu,Me )VCl 2 ] (1, Tp tBu,Me = hydro-tris(3-tert-butyl-5-methylpyrazol-1-yl)borate), which was reduced with KC 8 to form a $C_{3v}$ symmetric V II complex, [(Tp tBu,Me )VCl] (2). Complex 1 has a high-spin ($\textit{S}$ = 1) ground state and displays rhombic high-frequency and -field electron paramagnetic resonance (HFEPR) spectra, while complex 2 has an $\textit{S}$ = 3/2 4 A 2 ground state observable by conventional EPR spectroscopy. Complex 1 reacts with NaN 3 to form the V V nitride-azide complex [(Tp tBu,Me )V≡N(N 3 )] (3). A likely V III azide intermediate en route to 3, [(Tp tBu,Me )VCl(N 3 )] (4), was isolated by reacting 1 with N 3 SiMe 3 . Complex 4 is thermally stable but reacts with NaN3 to form 3, implying a bis-azide intermediate, [(Tp tBu,Me )V(N 3 ) 2 ] (A), leading to 3. Reduction of 3 with KC 8 furnishes a trinuclear and mixed-valent nitride, [{(Tp tBu,Me )V} 2 ($μ_{4-}$VN 4 )] (5), conforming to a Robin–Day class I description. Complex 5 features a central vanadium ion supported only by bridging nitride ligands. Contrary to 1, complex 2 reacts with NaN 3 to produce an azide-bridged dimer, [{(Tp tBu,Me )V} 2 (1,3-$μ_2$-N 3 ) 2 ] (6), with two antiferromagnetically coupled high-spin V II ions. Complex 5 could be independently produced along with [($κ_2$-Tp tBu,Me ) 2 V] upon photolysis of 6 in arene solvents. The putative {V IV ≡N} intermediate, [(Tp tBu,Me )V≡N] (B), was intercepted by photolyzing 6 in a coordinating solvent, such as tetrahydrofuran (THF), yielding [(Tp tBu,Me )V≡N(THF)] (B-THF). In arene solvents, B-THF expels THF to afford 5 and [($κ_2$-Tp tBu,Me ) 2 V]. A more stable adduct (B-OPPh 3 ) was prepared by reacting B-THF with OPPh 3 . These adducts of B are the first neutral and mononuclear V IV nitride complexes to be isolated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CLASS: Coronal Line Activity Spectroscopic Survey

We conduct the first systematic survey of a comprehensive set of the twenty optical coronal lines in the spectra of nearly 1 million galaxies observed by the Sloan Digital Sky Survey (SDSS) Data Release 8 catalog. This includes often overlooked high ionization potential lines such as [Ar x] λ5533, [S XII ] λ7609, [Fe XI ] λ7892, and [Fe XIV ] λ5303. We find that, given the limited sensitivity of SDSS, strong coronal line emission is extremely rare, with only ~0.03% of the sample showing at least one coronal line, significantly lower than the fraction of galaxies showing optical narrow line ratios (~17%) or mid-infrared colors (~2%) indicative of nuclear activity. The coronal line luminosities exhibit a large dynamic range, with values ranging from ~10 34 to 10 42 erg s –1 . We find that a vast majority (~80%) of coronal line emitters in dwarf galaxies (M $\star$ < 9.6 × 10 9 M ⊙ ) do not display optical narrow line ratios indicative of nuclear activity, in contrast to higher mass galaxies (~17%). Moreover, we find that the highest ionization potential lines are preferentially found in lower mass galaxies. These findings are consistent with the theory that lower mass black holes found in lower mass galaxies produce a hotter accretion disk, which in turn enhances the higher ionization coronal line spectrum. Future coronal line searches with 30 m class telescopes or JWST may provide a pathway into uncovering the intermediate mass black hole population.

79 ASTRONOMY AND ASTROPHYSICS↗

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

42 ENGINEERING↗

The Subchalcogenides Ir 2 In 8 Q (Q = S, Se, Te): Dirac Semimetal Candidates with Re-entrant Structural Modulation

Subchalcogenides are uncommon compounds where the metal atoms are in unusually low formal oxidation states. They bridge the gap between intermetallics and semiconductors and can have unexpected structures and properties because of the exotic nature of their chemical bonding as they contain both metal–metal and metal–main group (e.g., halide, chalcogenide) interactions. Finding new members of this class of materials presents synthetic challenges as attempts to make them often result in phase separation into binary compounds. We overcome this difficulty by utilizing indium as a metal flux to synthesize large (millimeter scale) single crystals of novel subchalcogenide materials. Herein, we report two new compounds Ir 2 In 8 Q (Q = Se, Te) and compare their structural and electrical properties to the previously reported Ir 2 In 8 S analogue. Ir 2 In 8 Se and Ir 2 In 8 Te crystallize in the $P_{4_2}$/mnm space group and are isostructural to Ir2In8S, but also have commensurately modulated (with q vectors q = 1/6a* + 1/6b* and q = 1/10a* + 1/10b* for Ir 2 In 8 Se and Ir 2 In 8 Te, respectively) low-temperature phase transitions, where the chalcogenide anions in the channels experience a distortion in the form of In–Q bond alternation along the ab plane. Both compounds display re-entrant structural behavior, where the supercells appear on cooling but revert to the original subcell below 100 K, suggesting competing structural and electronic interactions dictate the overall structure. Notably, these materials are topological semimetal candidates with symmetry-protected Dirac crossings near the Fermi level and exhibit high electron mobilities (~1500 cm 2 V –1 s –1 at 1.8 K) and moderate carrier concentrations (~10 20 cm –3 ) from charge transport measurements. This work highlights metal flux as a synthetic route to high quality single crystals of novel intermetallic subchalcogenides with Dirac semimetal behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial I ntelligence Applications t o Autonomous Cybersecurity (AI ATAC) prize challenges, funded by / completed in service of the US Navy. The experiment employed 100K files (50/50% benign/malicious) with a stratified distribution of file types, including ~1K zero-day program executables (increasing experiment size two orders of magnitude over previous work). We present an evaluation process of delivering a file to a fresh virtual machine donning the detection technology, waiting 90s to allow static detection, then executing the file and waiting another period for dynamic detection; this allows greater fidelity in the observational data than previous experiments, in particular, resource and time-to-detection statistics. To execute all 800K trials (100K files × 8 tools), a software framework is designed to choreograph the experiment into an automated, time-synced, and reproducible workflow with substantial parallelization. Software with base classes for this framework are provided. A cost-benefit model was configured to integrate the tools’ detection statistics into a comparable quantity by simulating costs of use. This provides a ranking methodology for cyber competitions and a lens for reasoning about the varied statistical results. The results provide insights on state of commercial malware detection.

Bridges, Robert↗

Quantification of gas concentrations in NO/NO 2 /C 3 H 8 /NH 3 mixtures using machine learning

We employ machine learning to decode the composition of unknown gas mixtures from the output of an array of four electrochemical sensors. The sensors use metal oxide electrodes paired with a ceramic electrolyte, yttria-stabilized zirconia (YSZ), to produce voltage responses to the presence of gases in complex mixtures. The voltages from the sensor array serve as inputs to a machine learning pipeline which first carries out multi-class classification of mixtures into types based on which gases are present at non-zero concentrations, and subsequently predicts gas concentrations given the mixture type. Thus, our model is able to take a single reading from the sensor array in response to gas mixtures involving NO, NO 2 , C 3 H 8 , and NH 3 , and output a highly accurate prediction of which gases are present in the mixture, along with the concentrations of each constituent gas. Of note, our computational framework can be easily expanded to include additional gases and additional mixture types, allowing it to be used in numerous automotive, industrial and environmental monitoring settings.

47 OTHER INSTRUMENTATION↗

Side-Chain and Ring-Size Effects on Permeability in Artificial Water Channels

Artificial water channels (AWCs) have emerged as a promising framework for stable water permeation, with water transport rates comparable to aquaporins (3.4–40.3 × 10 8 H 2 O/channel/s). In this study, we probe the influence of ring-size and side-chain length on the water permeability observed within a class of AWCs termed ligand-appended pillar[n]arenes (LAPs) that have an adjustable ring-size (m) and side-chain length (n). Through all-atom molecular dynamics simulations, we calculate the permeability of these channels using the collective diffusion model and find their permeabilities. We characterize the mechanistic influence of pillar[n]arene ring-size and side-chain length on the channel water permeability by analyzing the characteristics of the internal permeating water-wire and the surrounding channel structure. We observe that water permeability decreases as a function of increasing ring-size due to increases in hydrophilic contacts between the permeating water-wire and the oxygen groups on the channel wall. Further, we observe an increase in water permeability as a function of side-chain length due to increased partitioning of the channel terminal groups into the hydrophilic blocks of the surrounding bilayer. For the LAP6 channel, with increase in side-chain length, the distance between terminal groups increases and leads to an increase in pore size, thereby enhancing water permeability. In the case of LAP5, as side-chain length increases, the channel displays a compensatory effect between tilt and bend angle due to the flexible side-chains. Such flexibility leads to higher terminal group partitioning in the hydrophilic blocks of the bilayer and extends the permeating water-wire. Furthermore, this increase in water-wire length and hydrophilic block access overcomes the nonmonotonic pore size trend in pillar[5]arene channels.

36 MATERIALS SCIENCE↗

An Aluminum-Based Metal–Organic Cage for Cesium Capture

Metal–organic cages are a class of supramolecular structures that often require the careful selection of organic linkers and metal nodes. Of this class, few examples of metal–organic cages exist where the nodes are composed of main group metals. Herein, we have prepared an aluminum-based metal–organic cage, H 8 [Al 8 (pdc) 8 (OAc) 8 O 4 ] (Al-pdc-AA), using inexpensive and commercially available materials. The cage formation was achieved via solvothermal self-assembly of solvated aluminum and pyridine-dicarboxylic linkers in the presence of a capping agent, acetic acid. The obtained supramolecular structure was characterized by single-crystal X-ray diffraction (SCXRD), thermogravimetric analysis, and NMR spectroscopy. Based on crystal structure and computational analyses, the cage has a 3.7 Å diameter electron-rich cavity suitable for the binding of cations such as cesium (ionic radius of 1.69 Å). Here, the host–guest interactions were probed with 1 H and 133 Cs NMR spectroscopy in DMSO, where at low concentrations, Cs + binds to Al-pdc-AA in a 1:1 ratio. The binding site was identified from the crystal structure of CsH 7 [Al 8 (pdc) 8 (OAc) 8 O 4 ] (Cs + Al-pdc-AA), and a binding affinity of ~10 6 –10 7 M –1 was determined from NMR titration experiments. The Al-pdc-AA showed improved selectivity for cesium binding over alkali metal cations (Cs + > Rb + > K + >> Na + ~ Li + ). Collectively, the study reports a novel aluminum cage that can serve as a promising host for efficient and selective cesium removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic study of nuclear effects in p + Al , p + Au , d + Au , and He 3 + Au collisions at s N N = 200 GeV using π 0 production

The PHENIX Collaboration presents a systematic study of inclusive π 0 production from p + p , p + Al , p + Au , d + Au , and He 3 + Au collisions at s N N = 200 GeV . Measurements were performed with different centrality selections as well as the total inelastic, 0–100%, selection for all collision systems. For 0–100% collisions, the nuclear-modification factors, R x A , are consistent with unity for p T above 8 GeV / c , but exhibit an enhancement in peripheral collisions and a suppression in central collisions. The enhancement and suppression characteristics are similar for all systems for the same centrality class. It is shown that for high- p T - π 0 production, the nucleons in the d and He 3 interact mostly independently with the Au nucleus and that the counterintuitive centrality dependence is likely due to a physical correlation between multiplicity and the presence of a hard scattering process. These observations disfavor models where parton energy loss has a significant contribution to nuclear modifications in small systems. Nuclear modifications at lower p T resemble the Cronin effect—an increase followed by a peak in central or inelastic collisions and a plateau in peripheral collisions. The peak height has a characteristic ordering by system size as p + Au > d + Au > He 3 + Au > p + Al . For collisions with Au ions, current calculations based on initial-state cold nuclear matter effects result in the opposite order, suggesting the presence of other contributions to nuclear modifications, in particular at lower p T .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dynamical Classification of Trans-Neptunian Objects Detected by the Dark Energy Survey

The outer solar system contains a large number of small bodies (known as trans-Neptunian objects or TNOs) that exhibit diverse types of dynamical behavior. The classification of bodies in this distant region into dynamical classes—subpopulations that experience similar orbital evolution—aids in our understanding of the structure and formation of the solar system. In this work, we propose an updated dynamical classification scheme for the outer solar system. This approach includes the construction of a new (automated) method for identifying mean motion resonances. We apply this algorithm to the current data set of TNOs observed by the Dark Energy Survey (DES) and present a working classification for all of the DES TNOs detected to date. Our classification scheme yields 1 inner centaur, 19 outer centaurs, 21 scattering disk objects, 47 detached TNOs, 48 securely resonant objects, 7 resonant candidates, and 97 classical belt objects. Among the scattering and detached objects, we detect 8 TNOs with semimajor axes greater than 150 au.

79 ASTRONOMY AND ASTROPHYSICS↗

HydraGNN 2.0

HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission. New or improved capabilities included in v2.0.0 release are as follows: 1) Enhancement in message passing layers through class inheritance 2) Adding transformation to ensure translation and rotation invariance 3) Supporting various optimizers 4) Atomic descriptors 5) Integration with continuous CI test 6) Distributed printouts and timers 7) Profiling 8) Support of ADIOS2 for scalable data loading 9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Underwater Target Detection Software Demonstration on the RivGen Turbine

This repository contains data and processing scripts necessary to train the object detection models utilized in the underwater target detection software demonstration on the RivGen turbine project and to produce performance metrics (precision, recall, mAP50, mAP50-95). - Contents - Data consist of "images" and "labels". Each image has an associated label, both share the same time string in its file name (e.g., 2024_05_25_09_01_57.98.jpg and 2024_05_25_09_01_57.98.txt). Time strings have the format %yyyy_%mm_%dd_%HH_%MM_%SS.%3f. Images and labels were curated from 2021 and 2024 smolt outmigration periods at the project site in Igiugig, AK. Images are monochrome 8-bit images of objects (smolt, debris, and other) passing through the field of view of the deployed cameras during various operational stages of the RivGen turbine. Labels are text files indicating the class and bounding polygon of each object in an image. The provided labels use the "YOLO" label format. - Requirements - Python3.8+ is required to install and run the train and validation script. The README.md provides instruction for installing the requirements from the requirements.py file. - Instructions - The "example_train.py" file ingests the provided data, trains a model, and produces model performance metrics at completion. NOTE: model performance metrics will vary from run to run as a consequence of the random selection of training and validation data.

16 TIDAL AND WAVE POWER↗

EHS Health Assessment & Health Action Plan Report (CY 2020)

Sandia National Laboratories (SNL) Employee Health Services (EHS) program believes that good health is essential to getting the most out of life, which is why we offer a variety of worksite wellness programs that put employees in control of their own health. These programs are based on current research and strategies that are proven to minimize risk and decrease the impact of illness through early detection and treatment. Services includes Health Assessments, the Virgin Pulse (VP) online wellness platform, and Health Action Plans (HAP) which include one-on-one education, organizational health initiatives, a video library, an events calendar, onsite fitness facilities, and group fitness classes. Participation in these programs help employees and their spouses earn funding for their Health Reimbursement Accounts (HRAs). The EHS Health Action Plan (HAP) initiative targets the key health risks identified through the 8-15-80 model by engaging employees to change their own healthcare story. EHS identified the most prevalent of the health risks amongst our population through Health Risk Assessment (HRA) and used that data to build Health Action Plans (HAPs). The 2020 Health Action Plans addressed improving upon inadequate sleep, lack of energy, stress, weight, physical inactivity, cardiometabolic issues (hypertension, high cholesterol, diabetes), low back pain, allergies, asthma, digestive health, tobacco use, and living well to maintaining low risk for those individuals who do not have a chronic condition to manage. These plans connect employees with our onsite registered dietitians, fitness professionals, health coaches, physical therapists, and physicians as appropriate. In addition to addressing the physical aspects of health, the plans also emphasized pre/post-assessments to encourage building behavioral and emotional skills that promote health and facilitate lifestyle changes over a minimum of three months. Just one risk reduction or behavior change can make an impact on the health of the participant’s Division as well as Sandia’s overall risk levels and ultimately its healthcare costs. Sandia employees achieved an Overall Wellness Score of 69 based on the WellSource Health Assessment (the same as last year). A score of 70-100 is considered “Doing Well”, and a score of 40-69 is in the “Caution” category. Overall in CY 2019, Sandia saw a 34% participation rate in Health Action Plan (HAP) programs (up from 33% in CY 2019) with an 89% completion rate (4% lower than CY 2019). Overall, 5,039 (347 more than CY 2019) individuals participated in 8,329 HAPs, which is 1,005 more than the last calendar year (7,324).

59 BASIC BIOLOGICAL SCIENCES↗

Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗

Anisotropic flow of identified hadrons in $\mathrm{X}$e-$\mathrm{X}$e collisions at $\sqrt{s_{NN}}$ = 5.44 $\mathrm{T}$e$\mathrm{V}$

Measurements of elliptic (v 2 ) and triangular (v 3 ) flow coefficients of π ± , K ± , $p+\bar{p}$, $K$$^{0}_{S}$, and $Λ+\bar{Λ}$ obtained with the scalar product method in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV are presented. The results are obtained in the rapidity range |y| < 0.5 and reported as a function of transverse momentum, p T , for several collision centrality classes. The flow coefficients exhibit a particle mass dependence for p T < 3 GeV/c, while a grouping according to particle type (i.e., meson and baryon) is found at intermediate transverse momenta (3 < p T < 8 GeV/c). The magnitude of the baryon v 2 is larger than that of mesons up to p T = 6 GeV/c. The centrality dependence of the shape evolution of the p T -differential v 2 is studied for the various hadron species. The v 2 coefficients of π ± , K ± , and $p+\bar{p}$ are reproduced by MUSIC hydrodynamic calculations coupled to a hadronic cascade model (UrQMD) for p T < 1 GeV/c. A comparison with v n measurements in the corresponding centrality intervals in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV yields an enhanced v 2 in central collisions and diminished value in semicentral collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Intrachain Electron Transport in a Naphthalene Diimide–Bithiophene Copolymer: A Mixed-Valence Approach

The mechanism of electron transport in the polymer P(NDI2OD-T2) (poly(N,N'-bis-2-octyldodecylnaphthalene-1,4,5,8-bis-dicarboximide-2,6-diyl-alt-2,2'-bithiophene-5,5'-diyl), N2200) is investigated. Here, we use spectroelectrochemical measurements on P(NDI2OD-T2), spectroscopic studies of a chemically reduced model compound, 2,2'-(2,2'-bithiophene-5,5'-diyl)-bis(N,N'-di-n-hexylnaphthalene-1,8:4,5-bis(dicarboximide)) (NDI-T2-NDI), and electronic structure calculations to evaluate the microscopic charge-transport parameters. Experimental and computational data suggest that NDI-T2-NDI•– is a class-II mixed-valence compound, strongly supporting the small-polaron hopping model as a charge-transport mechanism for electrons along polymer chains in P(NDI2OD-T2). The electronic coupling between the NDI redox units is at least 21 meV, while the reorganization energy is between 0.45 and 0.56 eV. Using a hopping model, we estimated the mobility and activation energy for electron transport along P(NDI2OD-T2) polymer chains to be 0.15 cm 2 V –1 s –1 and 60 meV, respectively. Our study elucidates a long-standing issue of explaining the coexistence in P(NDI2OD-T2) of localized redox sites with relatively large electron mobilities more usually achieved only in highly conjugated polymers.

36 MATERIALS SCIENCE↗

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗