Results 41 to 50 of about 75,579 (226)

SOC Mismatch–Driven Inter‐Particle Synchronization via Internal Li‐Ion Transfer: An Unrecognized Electrode‐Emergent Degradation Pathway in Ni‐Rich Composite Cathodes

Advanced Energy Materials, EarlyView.
Composite cathode degradation is not merely the sum of its particles. Kinetically mismatched populations develop state‐of‐charge differences that drive spontaneous internal Li‐ion transfer; the accompanying transient currents accelerate surface degradation.
Seheon Oh, Suyoung Kim, Inho Kim, Kangwoo Ahn, Min Wook Pin, Minkyu Kim   +5 more
wiley   +1 more source

Survey of Bio-inspired Computing for Information Hiding

, 2016
In this paper, we performed surveys of bio-inspired techniques for information hiding. The applications of bio-inspired optimization for information hiding or watermarking have emerged in early 2000's.
Huang, Hsiang-Cheh;Chang, Feng-Cheng;Chen, Yueh-Hong;Chu, Shu-Chuan
core   +1 more source

Characterizing Biopolymer Electrolytes in Zinc–Air Batteries: Challenges, Best Practices, and a Robust Workflow Guiding Future Research Paths

Advanced Energy Materials, EarlyView.
Bio‐based gel polymer electrolytes promise sustainable, mechanically adaptable zinc–air batteries, yet their progress is constrained by inconsistent characterization. This review critically links formulation, structure, interfaces, and cell performance, identifies methodological gaps under alkaline operating conditions, and proposes application ...
Matteo Milanesi, Hiba Ali, Barbara Belza, Mattia F. Palermo, Claudio Gerbaldi, Giuseppe Antonio Elia, Nagore Ortiz‐Vitoriano   +6 more
wiley   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Trust Me Not: How Ostracism and Job Tension Drive Employees to Hide What They Know

Jurnal Manajemen Teori dan Terapan
Objective: This study aims to investigate the indirect relationship between interpersonal distrust and knowledge hiding behaviors through two mediating mechanisms, namely workplace ostracism and job tension. By combining social identity, social exchange,
Halizah Azzahroh Nur Syifa, Jovi Sulistiawan, Pie-Kuan Lin   +2 more
doaj   +1 more source

The dual effects of job design on knowledge hiding: expanding job demands–resources theory to employee rational-choice behaviour

The International Journal of Human Resource Management
Abstract.
Shujahat, Muhammad, Wang, Minhong, Ali, Murad, Zhu, Qinghua, Škerlavaj, Miha   +4 more
openaire   +3 more sources

Demystifying knowledge hiding in academic roles in higher education

, 2021
This paper presents a novel conceptual map of how knowledge hiding is understood and practiced in the higher education context. Building on a review of the knowledge management literature, we first discuss the nature of knowledge, the conceptualization ...
Bhattacharya, Ananya, Bavik, Yuen Lam, Sohal, Amrik, Zutshi, Ambika, Bavik, Ali, Creed, Andrew   +5 more
core   +1 more source

Leader's envy and knowledge hiding in universities in Pakistan [PDF]

, 2021
The present study examines the role of the leader's envy in knowledge hiding. Based on 28 semi-structured interviews from the faculty members of different Universities in Pakistan, we explain that how leader's perception of relative power as compare to ...
Ali, Moazzam, Pham, Tan Nhat, Usman, Muhammad   +2 more
core   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source