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At least 775 records · Page 43

Photovoltaic Cable Jackets: A Comparison of Representative Products Using Combined-Accelerated Stress Testing [Slides]

Photovoltaic (PV) cables facilitate the distribution of electricity collected from modules to the energy grid. Durable cabling enables continuous operation of PV installations, whereas cables with a lifetime less than the modules must be replaced - reducing electricity generation and adding to the operating expense. This study primarily focusses on the aging of the key cable types using the combined-accelerated stress testing (C-AST) protocol. Representative cables for utility, building, and control/auxiliary applications were examined. Cable jacket materials examined include: polyolefin, polyethylene, polyamide, poly(vinyl chloride), chlorinated polyethylene, thermoplastic elastomer, and ethylene propylene diene monomer rubber. Specimen characterizations applied include: optical microscopy, mechanical profilometry, instrumented indentation, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). A variety of performance and durability characteristics were observed, depending on the base material, polymer formulation, and jacket color. The results from C-AST are analyzed and discussed relative to a recent industry survey on electronic balance of system components in addition to a recent study where similar cables were aged using steady state ultraviolet weathering (International Electrotechnical Commission Technical Specification 62788-7-2). Recommendations are made for the screening, industry qualification, and service life prediction of PV cable jackets.

24 POWER TRANSMISSION AND DISTRIBUTION

Reaching quantum critical point by adding nonmagnetic disorder in single crystals of superconductor (Ca 𝑥 ⁢Sr 1−𝑥 ) 3 ⁢Rh 4 ⁢Sn 13

The Remeika series superconductor, (Ca 𝑥 ⁢Sr 1−𝑥 ) 3 ⁢Rh 4 ⁢Sn 13 , shows a rare nonmagnetic quantum critical point (QCP) associated with the continuous charge-density wave (CDW) and structural transition under the “dome” of superconductivity achieved by tuning composition and applying pressure. Here, we use a nonmagnetic pointlike disorder induced by 2.5 MeV electron irradiation to suppress the CDW and drive the system to and even beyond the QCP. This conclusion is based on a clear evolution of temperature-dependent resistivity, 𝜌⁡(𝑇), from the Fermi liquid to the non-Fermi liquid regime with increasing amount of disorder. Starting on the CDW side, below the suggested QCP concentration of 𝑥 𝑐 =0.9, added disorder resulted in a progressively larger linear term and a reduced quadratic term in 𝜌⁡(𝑇). Nearly perfect 𝑇−linear dependence is observed at the dose at which long-range CDW order is suppressed to 𝑇=0, consistent with the expectations. We refine the QCP location in this system and place it in the interval between 𝑥=0.75 and 0.85. Our results strongly support the concept that the disorder can tune the system to the quantum critical regime and even beyond. It follows from the argument by Imry and Ma that any ordered phase is unstable toward quenched disorder. Introduced in a controlled way, this disorder becomes a nonthermal tuning parameter likely applicable to a variety of different systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN

B‐Staging and Crosslinking of Polycarbosilane at Room Temperature: Cure Mechanism and Properties

The viscosity of polycarbosilane (PCS) polymers is not advantageous for free forming. Various fillers and heat are used to obtain a formable paste. Due to the low yield stress, structures and preforms tend to slump or resin will flow out, especially during the curing of the polymer. B-staging of PCS allows for a more stable structure from room temperature until the full cure of the allyl groups occurs with heat. Additionally, hydrosilation is an effective means of crosslinking at room temperature and controlling viscosity. A network structure was formed in SMP-10 using silane and a vinyl-based crosslinker to bridge each polymer chain. Pt addition catalysts were added to enhance the increase in viscosity to make a lightly crosslinked gel to aid in thickening and forming and to improve the ceramic yield at 1000°C. In conclusion, this enables several options for controlling rheology and improving the properties of preceramic polymers to avoid slumping during curing.

inorganic polymers

Transferable predictions of energetic and structural properties for refractory solid solution alloys across chemical compositions

We present a data-efficient approach to train graph neural networks (GNNs) on density functional theory (DFT) data for accurate and transferable predictions of energetic and structural properties of refractory solid solution alloys in the niobium-tantalum-vanadium (Nb-Ta-V) chemical space. We start by training the GNN model only on DFT data that describes refractory binary alloys niobium-tantalum (Nb-Ta), niobium-vanadium (Nb-V), and tantalum-vanadium (Ta-V) to predict formation enthalpy and root mean squared displacement. Once trained, the GNN predictions are tested on DFT data describing refractory ternary alloys Nb-Ta-V. While, unsurprisingly, direct transferability from binary to ternary is not sufficiently accurate, augmenting the training with only 1% of the available ternary data (uniformly distributed across the entire range of chemical compositions) improves significantly the quality of the GNN predictions. For comparison, we assess the transferability in the opposite direction by training GNN models on ternary Nb-Ta-V data and making predictions on binaries Nb-Ta, Nb-V, and Ta-V, which exhibits notably higher predictive errors. The proposed methodology, which favors transferability from lower-component to higher-component alloys, offers an efficient path towards avoiding the curse of dimensionality incurred when collecting DFT data for discovery and design of multi-component disordered alloys.

Density functional theory calculations

Unveiling Atomistic Mechanisms Governing Additive Manufacturing Processability and Mechanical Behavior of a Refractory Complex Concentrated Alloy

Extending the concept of complex concentrated alloys (CCAs) to the refractory alloys (solidus temperature over 2000 °C) space potentially facilitates the design of lightweight structural alloys with service temperatures that exceed those of Ni and Co‐based alloys. However, the room and elevated temperature tensile properties of the current refractory‐CCAs (R‐CCAs) are inferior to those of the Ni/Co‐based alloys. Furthermore, the manufacturing scalability of R‐CCAs remains challenging, in that cracks are prevalent in all R‐CCAs when processed using near‐net shape manufacturing processes, such as fusion‐based additive manufacturing (F‐BAM). Still, mechanisms governing the poor F‐BAM processability of R‐CCAs remain unexplored. Here, to this end, this work unveils the atomistic mechanisms underlying F‐BAM process‐induced cracking in a NbTiTaMoHfZrC R‐CCA. The implications of light elements’ presence for intrinsic ductility and grain boundary cohesion, and subsequently for F‐BAM processability and mechanical behavior, are revealed. Leveraging the insights, we accomplish what is, to the best of the knowledge, the first instance of crack‐free F‐BAM processing of any R‐CCA. Additionally, the R‐CCA exhibits over 20% tensile ductility and ≈160 MPa tensile yield strength at 1200 °C. In addition to facilitating the design of lightweight R‐CCAs, findings enable scalable manufacturing of these ultra‐high temperature alloys for structural applications.

Refractory alloys

Superheating gold beyond the predicted entropy catastrophe threshold

In their landmark study, Fecht and Johnson unveiled a phenomenon that they termed the ‘entropy catastrophe’, a critical point where the entropy of superheated crystals equates to that of their liquid counterparts. This point marks the uppermost stability boundary for solids at temperatures typically around three times their melting point. Despite the theoretical prediction of this ultimate stability threshold, its practical exploration has been prevented by numerous intermediate destabilizing events, colloquially known as a hierarchy of catastrophes, which occur at far lower temperatures. Here we experimentally test this limit under ultrafast heating conditions, directly tracking the lattice temperature by using high-resolution inelastic X-ray scattering. Our gold samples are heated to temperatures over 14 times their melting point while retaining their crystalline structure, far surpassing the predicted threshold and suggesting a substantially higher or potentially no limit for superheating. We point to the inability of our samples to expand on these very short timescales as an important difference from previous estimates. These observations provide insights into the dynamics of melting under extreme conditions.

Laser-produced plasmas

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville,

A statistical representation of bond coating oxidation under environmental barrier coatings

Environmental barrier coatings (EBCs) protect SiC-based ceramic matrix composites (CMCs) in turbine hot sections from high-temperature volatilization in combustion gases. The formation of a SiO 2 thermally grown oxide (TGO) is expected under the EBC after long-term operation. The oxidation resistance of the EBC is understood as a life-limiting factor for the CMC, and this work predicts long-term oxidation behavior under EBCs through a simple statistical approach. Specimens were exposed to 1350°C isothermal conditions for 100-h thermal cycles in flowing steam for up to 1000 h. The EBC morphology, SiO 2 thickness, and SiO 2 cracking behavior were assessed. Using thousands of SiO 2 thickness measurements across many millimeters of the interface, a realistic representation of the entire TGO was captured via a lognormal distribution. The lognormal fit parameters were extrapolated out to 25 000 h to assess the degree of SiO 2 growth, the spread of SiO 2 thicknesses related to the rough oxidizing interface, and percentages of the intermediate bond coating consumed. In conclusion, local interfacial defects from the coating deposition process are identified as local failure points for EBC—CMC systems.

SiO 2

The Impact of Membrane Inactive Area on the Durability of Pt-Co Catalyst

Platinum (Pt) is the most active catalyst for oxygen reduction reaction; however, its activity still requires a significant increase to meet the demands of practical applications. To enhance the catalytic activity, alloy catalysts like platinum-cobalt (Pt-Co), are being extensively investigated. However, Co leaching from the Pt-Co alloy remains a significant concern. Evaluating the durability of Pt-Co alloy catalyst is further complicated by variations in Co leaching, which affects both the observed performance and durability. This variability often arises from an overlooked factor: choice of the inactive area of the membrane electrode assembly (MEA) used during the evaluation. This study examines the critical role of membrane inactive area on the performance loss observed during durability testing of Pt-Co alloys. Our findings indicate that a large membrane inactive area reduces the impact of Co leaching on performance and durability, up to 200 mA cm −2 difference in performance is observed between large and small inactive area MEA at 0.7 V for dry conditions, and more Co is retained in the active area of MEA for smaller inactive areas which is responsible for larger performance losses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Surface Nanostructure Control and Thermodynamic Stability Analysis of Femtosecond Laser-Ablated CuCoMn 1.75 NiFe 0.25 Nanoparticles

Surface nanostructure control is the key to functionalizing nanomaterials. This paper presents a characterization with thermodynamic stability analysis of CuCoMn 1.75 NiFe 0.25 high-entropy alloy (HEA) nanoparticles synthesized by femtosecond laser ablation in ethanol and liquid nitrogen (LN2). Using multimodal electron microscopy and spectroscopy, we examine phase, particle size, defect structure, chemical distribution, and surface composition and relate them to HEA stability. Elemental distributions are uniform in both media, but LN2 produces smaller particles with a narrower size distribution and mainly single- or few-domain interiors, whereas ethanol yields larger particles built from 2–4 nm crystallites with domain aggregation. Edge defects appear in both but energy-dispersive X-ray spectroscopy (EDS) is broadly uniform with local fluctuations in ethanol. X-ray photoelectron spectroscopy (XPS), supported by an attenuation model, indicates an ∼1 nm oxide overlayer that suppresses Mn 2p intensity; correcting for it returns Mn toward the bulk value. UV–NIR and photoluminescent spectra independently support a thin oxide shell. Composition-based thermodynamic descriptors place LN2 closer to bulk mixing parameters, while ethanol raises ΔH_mix and lowers Ω. Cooling simulations are consistent (LN2 ∼ 0.1 μs quench, ethanol ∼1 μs). In conclusion, these results connect solvent-controlled kinetics and thermodynamics to crystalline state and surface chemistry, informing surface control of HEA nanoparticles.

Femtosecond Laser Ablation

Pyrolyzed Parylene-N for in Vivo Electrochemical Detection of Neurotransmitters

Carbon electrodes are typically used for in vivo dopamine detection, and new types of electrodes and customized fabrication methods will facilitate new applications. Parylene is an insulator that can be deposited in a thin layer on a substrate and then pyrolyzed to carbon to enable its use as an electrode. However, pyrolyzed parylene has not been used for the real-time detection of neurochemicals by fast-scan cyclic voltammetry. In this work, we deposited thin layers of parylene-N (PN) on metal wires and then pyrolyzed them to carbon with high temperatures in a rapid thermal processor (RTP). Different masses of PN, 1, 6, and 12 g, were deposited to vary the thickness. RTP-PN (6 g) produced a 194 nm layer carbon thickness and had optimal electrochemical stability. Pyrolyzed parylene-N modified electrodes (PPNMEs) were characterized for electrochemical detection of dopamine, serotonin, and adenosine. Background-normalized currents at PPNMEs were about 2 times larger than those of carbon-fiber microelectrodes (CFMEs). Rich defect sites and oxygen functional groups promoted the neurochemical adsorption of cationic neurotransmitters. PPNMEs resisted fouling from serotonin polymer formation. PPNMEs were used in vivo to detect stimulated dopamine release and monitor spontaneous adenosine release. Pyrolyzed parylene is a sensitive and fouling-resistant thin-film carbon electrode that could be used in the future for making customized electrodes and devices.

25 ENERGY STORAGE

Basin-Size Mapping: Prediction of Metastable Polymorph Synthesizability Across TaC–TaN Alloys

The sizes of the basins of attraction on the potential energy surface are helpful indicators in determining the experimental synthesizability of metastable phases. In principle, these basins can be controlled with changes in thermodynamic conditions such as composition, pressure, and surface energy. Herein, we use random structure sampling to computationally study how alloying smoothly perturbs basin of attraction sizes. The TaC 1-x N x pseudobinary is an ideal test system given the structural and polymorphic contrast of its parent compounds and their technological relevance as epitaxial substrates for Al 1-x Ga x N. While we find limited thermodynamic stability across all computationally observed phases, random structure sampling shows a significant composition region where the rocksalt basin dominates. As such, we predict the potential for the nonequilibrium synthesis of metastable rocksalt TaC 1-x N x alloys as substrates for Al 1-x Ga x N. At higher nitrogen concentrations, other low-energy metastable polymorphs emerge that continue to retain the hexagonal close packing suitable for III-N growth. Confidence in these trends was established through uncertainty quantification of the basin sizes and energy distributions; such analysis utilized the Beta and Dirichlet distributions. In conclusion, we also find (a) polymorph basin sizes can be rationalized in terms of energetic preferences for different coordination environments; and (b) basin sizes universally shrink with increasing nitrogen content, making the system more prone to amorphous growth.

36 MATERIALS SCIENCE

Distribution of 7 Li implants in Nb films for a sterile neutrino search

The Beryllium-7 Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for sub-MeV sterile neutrinos by measuring the 7 Li recoil spectrum from 7 Be decay in Ta-based superconducting quantum sensors. Its sensitivity is limited by spectral broadening from interactions between 7 Be/ 7 Li and the Ta host material. This study investigates Nb as an alternative sensor material using scanning transmission electron microscopy (STEM) and atom probe tomography (APT) on 7 Li-implanted Nb films (∼0.5 at. %). STEM shows no 7 Li cluster formation and no implantation-induced microstructural degradation, while APT reveals some limited 7 Li segregation to grain boundaries. Although this segregation may slightly influence binding energies, it is unlikely to affect the broadening of the recoil spectrum significantly. These findings support Nb as a viable sensor material for future phases of the BeEST experiment.

36 MATERIALS SCIENCE

Carbonation of MgO Single Crystals: Implications for Direct Air Capture of CO 2

Direct air capture (DAC) may be feasible to remove carbon dioxide (CO 2 ) from the atmosphere at the gigaton scale, holding promise to become a major contributor to climate change mitigation. Mineral looping using magnesium oxide (MgO) is potentially an economical, efficient, and sustainable pathway to gigaton-scale DAC. The hydroxylation and carbonation of MgO determine the efficiency of the looping process, but their rates and mechanisms remain uncertain. Here, in this work, MgO single crystals were reacted in air or CO 2 at varying humidities and characterized by X-ray scattering, microscopy, and vibrational spectroscopy. Results show that the hydroxylation formed a brucite (Mg(OH) 2 )-like layer immediately after crystal cleaving. Concurrently, the carbonation formed hydrated magnesium carbonate phases, including barringtonite (MgCO 3 ·2H 2 O) and nesquehonite (MgCO 3 ·2H 2 O), in the layer. Rapid initial growth of the layer is also manifested in short-range bending/warping of nanocrystallites, resulting in multiple orientations of the same phases on the surface. The layer growth slowed down over time, indicating surface passivation. The formation of barringtonite and nesquehonite with 1:1 CO 3 /Mg ratio indicates an efficient carbonation when compared to other magnesium carbonate phases of lower ratio. Our results are essential for understanding surface passivation mechanisms and tackling the passivation issue of mineral looping DAC technology.

54 ENVIRONMENTAL SCIENCES