119092 research outputs found
Sort by
Battery aging assessment: from critical insights to enhanced diagnosis
No full textReliable battery health diagnosis and cycle life prediction remain a central challenge for energy storage systems. This work first provides a systematic analysis of key factors for battery health diagnosis, highlighting previously overlooked yet critical elements that affect health assessments. Building on these insights, a rate-adaptive transformation model converts high C-rate features into low C-rate equivalents, enabling rapid diagnostics of battery aging modes without time-consuming testing using a low C-rate. To address fitting inaccuracies caused by aging, blended materials, and kinetic effects, an interpretable residual learning model corrects voltage mismatches, which also enables low C-rate fitting by using high C-rate data. Leveraging mechanistic-informed features, early cycle life prediction achieves mean errors of less than 70 cycles using data from fewer than 30 equivalent full cycles across complex and unseen aging conditions. This interpretable and generalizable framework bridges electrochemical understanding with practical diagnosis and offers a fast and reliable path toward mechanism-informed battery prognostics
Unternehmenskomplexität und Split Ratings
No full textSplit Ratings, bei denen sich verschiedene Ratingagenturen uneins sind in der Bonitätseinstufung eines Schuldners, erschweren Investoren die Bewertung von Fremdkapitaltiteln und können die Kreditkosten erhöhen. Deshalb ist ein Verständnis für die Ursachen von Split Ratings bedeutsam für das Verständnis der Preisbildung an Kreditmärkten. Die Studie untersucht, ob die Unternehmenskomplexität des Schuldners mit dem Auftreten und der Ausprägung von Split Ratings zusammenhängt. Auf Basis eines Datensatzes US-börsennotierter Unternehmen (1996 – 2021) werden Kreditratings der Agenturen S&P, Moody’s und Fitch mit dem textbasierten Komplexitätsmaß nach Loughran und McDonald (2024) sowie unternehmensspezifischen Kennzahlen verknüpft. Methodisch kommen logistische und ordinale Regressionsmodelle zum Einsatz, in denen vier Hypothesen (Auftreten, Differenz in Notches, Überschreiten der Investment-/Speculative-Grade-Schwelle, Zusammenhang mit zurückgezogenen Ratings) geprüft werden.
Die Ergebnisse zeigen zwar keinen signifikanten Einfluss der Komplexität in den 10-K-Berichten auf das Auftreten, die Höhe oder die Relevanzschwelle von Split Ratings. Aber die Nettodateigröße der 10-K-Berichte ist ein relevanter Prädiktor: Sie erhöht sowohl die Wahrscheinlichkeit von Split Ratings als auch deren Differenz. Je umfangreicher zentrale Unternehmensdokumente sind, desto eher kommen die bedeutendsten Ratingagenturen der Welt also zu unterschiedlichen Bonitätseinstufungen
Iterative design of a NAND hybrid riboswitch by deep batch Bayesian optimization
No full textThe design of large genetic circuits requires genetic regulatory devices capable of performing complex logic operations that place no excessive metabolic burden on the host cell. Hybrid riboswitches, synthetically enhanced compact RNA elements (<100 nucleotides) that form a tertiary structure with the ability to specifically bind two different target molecules, can be used to design genetic regulators that emulate Boolean logic. When inserted into the 5′ UTR of a messenger RNA, these devices can regulate translation initiation upon specific binding of one or both ligands without the need for additional auxiliary factors. The goal of this study is to design hybrid riboswitches that emulate Boolean NAND logic in yeast. We propose a novel machine learning-based design framework combining high-throughput in vivo screening and deep Bayesian optimization. Through an initial screening, we discovered a hybrid riboswitch with NAND behavior. Using batch Bayesian optimization with an ensemble neural network as surrogate, we improved the NAND functionality of our hybrid riboswitch with respect to a performance score, thereby achieving near-digital NAND behavior. With its focus on model-based and score-driven design, our proposed method can complement experiment-driven approaches by allowing fine grained adaptation of functionality, including constructs sensitive to single nucleotide changes
High-throughput screening of spin hall conductivity in two-dimensional materials
No full textTwo-dimensional (2D) materials with a large spin Hall effect (SHE) have attracted significant attention due to their potential applications in next-generation spintronic devices. In this work, we perform high-throughput (HTP) calculations to obtain spin Hall conductivity (SHC) of 4486 nonmagnetic compounds in the 2Dmatpedia database and identify 6 materials with SHC exceeding 7.0 e/4π, surpassing those of the known materials. Detailed analysis reveals that the significant SHC can be attributed to spin–orbit coupling (SOC)-induced gap openings at Dirac-like band crossings. Additionally, the presence of mirror symmetry can also enhance the SHC. Beyond the high SHC materials, 57 topological insulators with quantized SHCs have been identified. Our work enables rapid screening and paves the way for experimental validation, potentially accelerating the discovery of novel 2D materials optimized for spintronics applications
Tailoring the structural and transport properties of Ba 2 In 2 O 5 through Cr 6+ substitution for enhanced oxygen permeation
No full textThis work reveals the structural evolution and transport behavior of chromium-substituted Ba2In2O5 (BIO) as a mixed ionic electronic conductor for oxygen transport membranes. Controlled substitution of In3+ by Cr6+ induces a transition from an orthorhombic brownmillerite to an on average cubic defect-perovskite (ABO3−δ) phase while suppressing the high-temperature phase transformations typical of undoped BIO. A comprehensive set of structural and spectroscopic techniques confirms the stabilization of Cr6+ in the lattice and its function as a donor dopant. The aliovalent substitution introduces additional electrons while reducing the oxygen-vacancy concentration in the lattice, resulting in increased electronic and decreased ionic conductivities. The composition with x = 0.1 achieves a well-balanced contribution from ionic and electronic carriers, yielding the highest ambipolar conductivity and oxygen permeation flux among the studied samples. At higher substitution levels (e.g., x = 0.2), where In3+ and Cr6+ coexist on the B-site of the perovskite framework, a coupled donor/acceptor system (Cr6+/In3+) is formed, giving rise to complex charge compensation mechanisms and mixed electronic conduction. These findings provide fundamental insights into the crystal structure, defect chemistry, and charge transport mechanisms in Cr-substituted BIO, offering a rational design strategy for efficient oxygen transport membranes
New Hires, New Worlds: Metaverse Onboarding and Its Impact on Organizational Socialization
No full textFrequent job changes and remote work have made effective onboarding more important—and more challenging—than ever before. As newcomers must quickly internalize organizational values, build relationships, and navigate unfamiliar roles, socialization becomes a critical factor in employee retention and performance. Traditional digital tools like videoconferencing often fall short in replicating key elements of in-person interaction, such as nonverbal cues, shared spatial context, and informal communication. In response, organizations are beginning to explore immersive technologies like the metaverse to bridge this gap. However, despite growing managerial interest, little is known about whether metaverse-based onboarding can meaningfully support newcomer socialization. Therefore, this study compares onboarding experiences in Zoom and a metaverse platform (Glue) through lab and online experiments. By investigating how immersive environments shape socialization processes, we offer theoretical and practical insights into designing more effective remote onboarding strategies for the future of work
Experimental and simulation-based characterization of the elastic material behavior of powder metallurgically produced AlSi10Mg foams
No full textConstruction of a medium-deep geothermal storage system: case study of the SKEWS MD-BTES demosite
No full textIs this chart lying to me? Automating the detection of misleading visualizations
No full textMisleading visualizations are a potent driver of misinformation on social media and the web. By violating chart design principles, they distort data and lead readers to draw inaccurate conclusions. Prior work has shown that both humans and multimodal large language models (MLLMs) are frequently deceived by such visualizations. Automatically detecting misleading visualizations and identifying the specific design rules they violate could help protect readers and reduce the spread of misinformation. However, the training and evaluation of AI models has been limited by the absence of large, diverse, and openly available datasets. In this work, we introduce Misviz, a benchmark of 2,604 real-world visualizations annotated with 12 types of misleaders. To support model training, we also create Misviz-synth, a synthetic dataset of 57,665 visualizations generated using Matplotlib and based on real-world data tables. We perform a comprehensive evaluation on both datasets using state-of-the-art MLLMs, rule-based systems, and image-axis classifiers. Our results reveal that the task remains highly challenging. We release Misviz, Misviz-synth, and the accompanying code
Is Peer Review Really in Decline? Analyzing Review Quality across Venues and Time
No full textPeer review is at the heart of modern science. As submission numbers rise and research communities grow, the decline in review quality is a popular narrative and a common concern. Yet, is it true? Review quality is difficult to measure, and the ongoing evolution of reviewing practices makes it hard to compare reviews across venues and time. To address this, we introduce a new framework for evidence-based comparative study of review quality and apply it to major AI and machine learning conferences: ICLR, NeurIPS and *ACL. We document the diversity of review formats and introduce a new approach to review standardization. We propose a multi-dimensional schema for quantifying review quality as utility to editors and authors, coupled with both LLM-based and lightweight measurements. We study the relationships between measurements of review quality, and its evolution over time. Contradicting the popular narrative, our cross-temporal analysis reveals no consistent decline in median review quality across venues and years. We propose alternative explanations, and outline recommendations to facilitate future empirical studies of review quality