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At least 181 records · Page 10

Capture efficiency and bias from the defect dynamics near grain boundaries in BCC Fe using mesoscale simulations

The capture efficiency describes the capability of a sink, such as a grain boundary (GB), dislocation, and void, to absorb point defects (PDs). The bias defines the difference in capture efficiency between the absorption of a vacancy and dumbbell at a sink. Complete kinetic information on PDs, including diffusion barriers and diffusion orientations, as well as accurate saddle points, are needed to determine the capture efficiency and bias at a sink accurately, which is computationally demanding. Here, in the present study, the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method was used to investigate the defect dynamics of PDs near different types of grain boundaries (GBs) (with both $\langle$100$\rangle$ and $\langle$110$\rangle$ families) accurately in body-centered cubic (BCC) iron (Fe). The capture efficiency, sink strength, and bias factor of different types of GBs were determined in Fe, which, different from traditional rate theory estimation, showed a distinct capture efficiency, sink strength, and bias in different GBs. The results demonstrate a strong positive correlation between the capture efficiency and the GB strain width, instead of the GB misorientation, GB energy, or GB-PD binding energy, which have been investigated previously. This work provides valuable insight into the radiation-induced microstructural evolution of GBs.

36 MATERIALS SCIENCE↗

Atomic-Scale Insights into the Lateral and Vertical Epitaxial Growth in Two-Dimensional Pd 2 Se 3 –MoS 2 Heterostructures

Two-dimensional (2D) materials form heterostructures in both the lateral and vertical directions when two different materials are interfaced, but with totally different bonding mechanisms of covalent in-plane to van der Waal’s layered interactions. Understanding how the competition between lateral and vertical forces influences the epitaxial growth is important for future materials development of complex mixed layered heterostructures. In this study, we use atomic-resolution annular dark-field scanning transmission electron microscopy to study the detailed atomic arrangements at mixed 2D heterostructure interfaces composed of two semiconductors with distinctly different crystal symmetry and elemental composition, Pd 2 Se 3 :MoS 2 , in order to understand the role of different chemical bonds on the resultant epitaxy. Pd 2 Se 3 is grown off the step edge in bilayer MoS 2 , and the vertical and lateral epitaxial relationships of the Pd 2 Se 3 –MoS 2 heterostructures are investigated. We find that the similarity of geometry at the interface with one metal (Pd or Mo) atoms bonded with two chalcogens (S or Se) are the crucial factors to make the atomically stitched lateral junction of 2D heterostructures. In addition, the vertical van der Waal interactions that are normally dominant in layered materials can be overcome by in-plane forces if the interfacial atomic stitching is high in quality and low in defect density. This knowledge should help guide the approaches for improving the epitaxy in mixed 2D heterostructures and seamless stitching of in-plane 2D heterostructures with various complex monolayer structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of Solute Segregation at Metal/Oxide Interfaces Using Machine Learning Approaches

The atomic structure and chemistry at metal/oxide interfaces play a crucial role in determining their properties. However, studying semi-coherent metal/oxide interfaces that include misfit dislocations through density functional theory (DFT) is often computationally expensive due to the large number of atoms involved, ranging from hundreds to thousands. In this study, we explore solute segregation behavior at the Fe/Y 2 O 3 interface—an important model interface for cladding applications in nuclear fission reactors—by combining DFT calculations with a machine learning (ML) approach. ML models are trained using DFT-calculated segregation energies (𝐸 𝑆𝑒𝑔 ) to identify the key chemical and geometric factors influencing solute segregation at metal/oxide interfaces, revealing the competition between these features in determining 𝐸 𝑆𝑒𝑔 . Moreover, the segregation behavior at a specific Fe/Y 2 O 3 interface is predicted with high accuracy using ML models trained on data from this interface. Furthermore, it is found that the ML models could also predict solute segregation at a different Fe/Y 2 O 3 interface with a new orientation relationship (OR), at a computational cost of less than 1/45 of that required for similar DFT calculations.

36 - MATERIALS SCIENCE↗

A Frequency-Programmable Miniaturized Radio Frequency Transmitter for Animal Tracking

In animal tracking applications, smaller transmitters can reduce the impact of the transmitter on the tagged animal and thus provide more accurate data about animal behavior. By combining a novel circuit design and a newly developed micro-battery, we developed frequency-programmable and more powerful radio frequency transmitters that are about 40% smaller and lighter in weight than the smallest commercial counterpart for animal monitoring at the time of development. The new radio frequency transmitter has a miniaturized form factor for studying small animals. Designs of two coding schemes were developed: one transmits unmodulated signals (weight: 152 mg; dimensions: Ø 2.95 mm × 11.22 mm), and the other transmits modulated signals (weight: 160 mg; dimensions: Ø 2.95 mm × 11.85 mm). To accommodate different transmitter life requirements, each design can be configured to transmit in high or low signal strength. Prototypes of these transmitters were evaluated in the laboratory and exhibited comparable or longer service life and higher signal strength compared to their smallest commercial counterparts.

47 OTHER INSTRUMENTATION↗

RbB 3 Si 3 : An Alkali Metal Borosilicide that is Metastable and Superconducting at 1 atm

The stability, electronic structure and potential superconductivity in AB 3 Si 3 (A = Na, K, Rb, and Cs) compounds that assume the clathrate-based sodalite structure whose frameworks consists of covalent B-Si bonds is investigated via first-principles calculations. This structure type has recently been predicted in a number of high temperature superconducting hydrides, but these are only stable under megabar pressures. Herein, we predict a novel superconducting phase, RbB 3 Si 3 , that could be synthesized under pressures that are a factor of ten smaller, ~10 GPa, and quenched to atmospheric conditions. Electron-phonon coupling calculations predict that RbB 3 Si 3 possesses a superconducting critical temperature, T c , of 14 K at 1 atm. Here, the dynamic stability of RbB 3 Si 3 and CsB 3 Si 3 at ambient pressure can be explained by considering the chemical pressure exerted on the B-Si framework that is caused by the size effect of the alkali metal atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Techno-economic analysis of non-aqueous hybrid redox flow batteries

Renewable energy has become indispensable to improving human life, but its growth is hampered by a lack of cost-effective energy storage systems to solve the intermittency problem. Non-aqueous hybrid redox flow batteries (NAqHRFBs), based on lithium metal anode and organic redox molecules (redoxmers), have been investigated as an attractive energy storage option because of their high cell voltages and energy densities compared to other redox flow battery candidates. However, little is known about the economic potential of NAqHRFBs, as well as the operational and materials impacts. This research establishes a techno-economic model to analyze the capital costs of NAqHRFBs with selected organic redoxmers, including 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO). Sensitivity analyses for current density, area-specific resistance, cell voltage, electrolyte composition, redoxmer price, and equivalent molecular weight indicate the key factors in controlling NAqHRFB capital cost. To make the current NAqHRFB cost-effective, the first priority is to increase the operation current density over 10 times of those used in lab-scale tests, followed by adjusting redoxmer-related characteristics to afford more cost reduction space such as decreasing the unit price by ~20 fold. The results have shed light on potential material development and system engineering directions to make NAqHRFBs viable for renewable energy storage.

25 ENERGY STORAGE↗

Sequential surface synthesis of dispersed sub-nanometer iridium on titanium nitride for acidic water oxidation

Maximizing iridium utilization while maintaining high oxygen evolution reaction (OER) performance remains a persistent challenge in acidic water electrolysis. Immobilizing Ir on conductive, acid-stable supports is promising, yet simultaneously achieving sub-nanometer size, high area coverage, and strong electronic coupling is difficult. Here, we report a sequential surface synthesis on titanium nitride (TiN) that yields uniformly distributed sub-nanometer Ir arrays (∼0.7 nm). Our method uses ethylenediaminetetraacetic acid (EDTA) as a temporal scaffold: it chemisorbs to TiN to install dense chelating sites, captures Ir 3+ ions, and confines Ir cluster growth. A subsequent thermal treatment at 500 °C in a reducing atmosphere removes the ligand shell, while preserving ultrasmall particle size and establishing direct Ir–TiN electronic coupling. The optimized catalyst exhibits mixed Ir 0 /Ir x+ coordination with low charge-transfer resistance (R ct = 19.2 Ω), delivering a mass activity of 342 A g Ir −1 at 1.54 V in acidic electrolyte. In situ X-ray absorption spectroscopy reveals irreversible surface oxidation as the primary stability-limiting factor. This stepwise strategy provides a general framework for supported catalysts that maximize precious metal utilization via sub-nanometer dispersion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data

Scientific simulations in high-performance computing (HPC) environments generate vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for postanalysis. Unlike traditional data reduction schemes such as deduplication or lossless compression, not only can error-controlled lossy compression significantly reduce the data size but it also holds the promise to satisfy user demand on error control. Pointwise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications with lossy compression since error control can adapt to the error bound in the dataset automatically. Pointwise relative-error-bounded compression is complicated and time consuming. In this article, we develop efficient precomputation-based mechanisms based on the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error-bounded compression with excellent compression ratios. In addition, we reduce traversing operations for Huffman decoding, significantly accelerating the decompression process in SZ. Experiments with eight well-known real-world scientific simulation datasets show that our solution can improve the compression and decompression rates (i.e., the speed) by about 40 and 80 p, respectively, in most of cases, making our designed lossy compression strategy the best-in-class solution in most cases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Association of Serum Bile Acid and Unsaturated Fatty Acid Profiles with the Risk of Diabetic Retinopathy in Type 2 Diabetic Patients

Aim: We aimed to identify the ability of serum bile acids (BAs) and unsaturated fatty acids (UFAs) profiles to predict the development of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) patients. Methods: We first used univariate and multivariate analysis to compare 15 serum BA and 11 UFA levels in healthy control (HC) group (n = 82), T2DM patients with DR (n = 58) and T2DM patients without DR (n = 60). Forty T2DM patients were considered for validation. Then, the receiver operating characteristic curve (ROC) and decision curve analysis were used to assess the diagnostic value and clinical benefit of serum biomarkers alone, clinical variables alone or in combination, and the area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to further assess whether the addition of biomarkers significantly improved the predictive ability of the model. Results: Orthogonal partial least squares-discriminant analysis (OPLS-DA) of serum BAs and UFAs separated the three cohorts including HC, T2DM patients with or without DR. The difference in serum BA and UFA profiles of T2DM patients with or without DR was mainly manifested in the three metabolites of taurolithocholic acid (TLCA), tauroursodeoxycholic acid (TUDCA) and arachidonic acid (AA). Together, they had an AUC of 0.785 (0.918 for validation cohort) for predicting DR in T2DM patients. After adjusting for numerous confounding factors, TLCA, TUDCA, and AA were independent predictors that differentiated T2DM with or without DR. The results of AUC, IDI, and NRI demonstrated that adding these three biomarkers to a model with clinical variables statistically increased their predictive value and were replicated in our independent validation cohort. Conclusion: These findings highlight the association of three metabolites, TLCA, TUDCA and AA, with DR and may indicate their potential value in the pathogenesis of DR.

60 APPLIED LIFE SCIENCES↗

Chiral Perovskite Nanoplatelets with Tunable Circularly Polarized Luminescence in the Strong Confinement Regime

Chiral perovskite nanocrystals have emerged as an interesting chiral excitonic platform that combines both structural flexibility and superior optoelectronic properties. Despite several recent demonstrations of optical activity in various chiral perovskite nanocrystals, efficient circularly polarized luminescence (CPL) with tunable energies remains a challenge. The chirality imprinting mechanism as a function of perovskite nanocrystal dimensionality remains elusive. Here, in this study, atomically thin inorganic perovskite nanoplatelets (NPLs) are synthesized with precise control of layer thickness and are functionalized by chiral surface ligands, serving as a unique platform to probe the chirality transfer mechanism at the organic/perovskite interface. It is found that chirality is successfully imprinted into mono-, bi-, and tri-layer inorganic perovskite NPLs, exhibiting tunable circular dichroism (CD) and CPL responses. However, chirality transfer decreases in thicker NPLs, resulting in decreased CD and CPL dissymmetry factors for thicker NPLs. Aided by large-scale first-principles calculations, it is proposed that chirality transfer is mainly mediated through a surface distortion rather than a hybridization of electronic states, giving rise to symmetry breaking in the perovskite lattice and spin-split conduction bands. The findings described here provide an in-depth understanding of chirality transfer and design principles for distorted-surface perovskites for chiral photonic applications.

36 MATERIALS SCIENCE↗

Controlling the corrosion resistance of multi-principal element alloys

Multi-principal element alloys (MPEAs) offer the possibility of many degrees of freedom in the choice of alloying elements to produce either single phase solid solutions or more complex multiphase microstructures. Large ranges of material properties have been observed for MPEAs and mastery of the selection of elements and their compositions can enable novel combinations of properties not possible in traditional alloys. From the aqueous corrosion perspective, optimization of phase stability, control of heterogeneities, passive film identity and its protectiveness, as well as substrate properties such as metal-metal bond strength and activation energy associated with dissolution, can all be controlling factors governed by alloy composition and structure. These factors can mediate the electrochemical reactions controlling spontaneous corrosion. The quest for superior properties based on well-informed element choice is suggested as a path forward guiding MPEA formulations for corrosion performance. However, gaps in fundamental knowledge exist regarding (a) the specific functions of each element, (b) the behavior of elements in unusual combinations, and (c) the formation of complex protective oxides. These issues currently hold back progress in optimization of corrosion properties.

Scully, John R.↗

Water treatment based on atomically engineered materials: Atomic layer deposition and beyond

Global water stress and challenges for producing sufficient supplies of fit-for-purpose water are amplifying. Atomically engineered interfaces are emerging as a powerful tool in the fabrication of advanced water treatment materials. Atomic layer deposition (ALD) and recently developed related methods, such as sequential infiltration synthesis (SIS), offer a tremendously diverse library of chemistries for interface functionalization. Thickness, stoichiometry, and physicochemical properties can be manipulated with precision. We review their fundamental physical chemistry and processing factors. ALD/SIS engineering strategies, including direct deposition, growth with intermediate layers, and secondary treatment are presented with realization of efficient water treatment. We lay out a pathway to establishing an ALD/SIS-based universal functionalization platform for water treatment, including sensitization strategies, in situ regulation, secondary reactions, and simulation/machine learning. Furthermore, we also provide a perspective on ALD/SIS-based interface engineering via synergy with other widely used interface engineering techniques to develop facile, versatile, and energy-efficient strategies for tackling increasingly complex water challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aberrant FBXW7-mediated ubiquitination and degradation of ZMYND8 enhances tumor progression and stemness in bladder cancer

ZMYND8, an epigenetic regulator, was identified as a common oncogene across various tumors. However, little was reported about the association between ZMYND8 and bladder cancer. Besides, aberrant mechanisms that contribute to abnormal ZMYND8 expressions still remain unclear. In the current study, we first found that ZMYND8 protein levels were significantly elevated in Bca samples versus normal tissues, but not the mRNA levels. We then utilized the Cell Counting Kit-8 (CCK-8) assay, clone formation assay and transwell analysis to confirm that ZMYND8 could remarkably promote the tumor progression in vitro, including growth capacity and migration. Bioinformatic predictive analysis revealed that E3 ubiquitin ligase FBXW7 interacts directly with ZMYND8 and degrades ZMYND8 in a polyubiquitination manner. Low FBXW7 was a hazard factor for promoting and depending on accumulated ZMYND8 proteins to promote Bca progression. Gene set enrichment analysis (GSEA) further indicated that ZMYND8 was notably associated with stemness process, which was well functionally validated. Lastly, ZMYND8 deficiency was observed to inhibit tumor growth of Bca in vivo, revealing a promising translational significance in Bca treatment. In conclusion, our study for the first time provided evidence for a novel mechanism of FBXW7/ZMYND8 axis in Bca, providing therapeutic vulnerability for individualized cancer treatment.

60 APPLIED LIFE SCIENCES↗

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗

An analytic theory for the degree of Arctic Amplification

Arctic Amplification (AA), the amplified surface warming in the Arctic relative to the global mean, is a robust and impactful feature of climate change. While the basic physical picture of AA has been depicted, a clear understanding of how the degree of AA is determined has not been established. Here, by deciphering the intricate role of atmospheric heat transport (AHT), we build a two-box energy-balance model of AA and derive that the degree of AA is a simple nonlinear function of the Arctic and global feedbacks, the meridional heterogeneity in radiative forcing, and the partial sensitivities of AHT to global mean warming and meridional warming gradient. The formula captures the varying degree of AA in individual climate models and attributes the variation to specific physical factors. It further conveys a concise picture of how essential physics mutually determine the degree of AA and limit the range within 1.5~3.5. Our results articulate AHT as both forcing and feedback to AA, highlighting its partial sensitivities instead of total change as the key parameters for understanding AA. We also find that the effect of lapse rate feedback, a widely-recognized major contributor to AA, is fully offset by the effect of water vapor feedback.

54 ENVIRONMENTAL SCIENCES↗

Orientation-Controlled Large-Area Epitaxial PbI 2 Thin Films with Tunable Optical Properties

Lead iodide (PbI 2 ) as a layered material has emerged as an excellent candidate for optoelectronics in the visible and ultraviolet regime. Micrometer-sized flakes synthesized by mechanical exfoliation from bulk crystals or by physical vapor deposition have shown a plethora of applications from low-threshold lasing at room temperature to high-performance photodetectors with large responsivity and faster response. However, large-area centimeter-sized growth of epitaxial thin films of PbI 2 with well-controlled orientation has been challenging. Additionally, the nature of grain boundaries in epitaxial thin films of PbI 2 remains elusive. Here, we use mica as a model substrate to unravel the growth mechanism of large-area epitaxial PbI 2 thin films. The partial growth leading to uncoalesced domains reveals the existence of inversion domain boundaries in epitaxial PbI 2 thin films on mica. Combining the experimental results with first-principles calculations, we also develop an understanding of the thermodynamic and kinetic factors that govern the growth mechanism, which paves the way for the synthesis of high-quality large-area PbI 2 on other substrates and heterostructures of PbI 2 on single-crystalline graphene. Here, the ability to reproducibly synthesize high-quality large-area thin films with precise control over orientation and tunable optical properties could open up unique and hitherto unavailable opportunities for the use of PbI 2 and its heterostructures in optoelectronics, twistronics, substrate engineering, and strain engineering.

2D materials↗

Crash Risks Evaluation of Urban Expressways: A Case Study in Shanghai

We report that proactive traffic safety management systems can reduce crashes by identifying crash precursors, evaluating real-time crash risks, and implementing suitable interventions. The basic prerequisite for developing such a system is to propose a reliable crash risk evaluation model that takes real-time traffic flow data as input. Previous studies have primarily focused on real-time crash prediction using some statistical or machine-learning methods. However, further quantitative evaluation and classification of crash risks have been ignored. In this study, we conduct a systematic crash risk evaluation workflow, including crash risk prediction, crash risk quantification, and crash risk classification. Specifically, the crash risk prediction using an extended logit model is proposed, from which CAS, CSD, UAS, DAS, DTV are identified to be contributing factors of crash risks. Then a crash risk quantification model based on the parameter evaluation of the extended logit model is developed. The crash risks of urban expressways and their spatial-temporal evolution trends are quantified. Finally, the crash risks are classified into high crash risk level, moderate crash risk level, and low crash risk level by the k-means cluster algorithm. Then the threshold boundaries of different crash risk levels are determined. The research results provide a proactive guidance for traffic safety management of urban expressways.

33 ADVANCED PROPULSION SYSTEMS↗

Correlating Electronic Structure and Device Physics with Mixing Region Morphology in High-Efficiency Organic Solar Cells

The donor/acceptor interaction in non-fullerene organic photovoltaics leads to the mixing domain that dictates the morphology and electronic structure of the blended thin film. Initiative effort is paid to understand how these domain properties affect the device performances on high-efficiency PM6:Y6 blends. Different fullerenes acceptors are used to manipulate the feature of mixing domain. It is seen that a tight packing in the mixing region is critical, which could effectively enhance the hole transfer and lead to the enlarged and narrow electron density of state (DOS). As a result, short-circuit current (J SC ) and fill factor (FF) are improved. The distribution of DOS and energy levels strongly influences open-circuit voltage (V OC ). The raised filling state of electron Fermi level is seen to be key in determining device V OC . Energy disorder is found to be a key factor to energy loss, which is highly correlated with the intermolecular distance in the mixing region. A 17.53% efficiency is obtained for optimized ternary devices, which is the highest value for similar systems. The current results indicate that a delicate optimization of the mixing domain property is an effective route to improve the V OC , J SC , and FF simultaneously, which provides new guidelines for morphology control toward high-performance organic solar cells.

36 MATERIALS SCIENCE↗