Results 111 to 120 of about 1,694,516 (244)

Degradation Mechanism of Phosphate‐Based Li‐NASICON Conductors in Alkaline Environment

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
The presence of water in the cathode of a Li‐air battery shifts reactions to produce LiOH, creating a corrosive, alkaline environment. This study investigates the alkaline stability of the common Li‐NASICON solid‐state conductor chemistries through a systematic experimental study combined with computational modeling to understand the degradation ...
Benjamin X. Lam, Zhuohan Li, Tara P. Mishra, Gerbrand Ceder   +3 more
wiley   +1 more source

Assessment the quality of removal the smear layer using by rotary tool with zero taper

Эндодонтия Today, 2020
Smear layer is created by rotary and hand instrumentation. This layer closes dentin tubules and reduces the effect of irrigating solutions, the quality of obturation and outcome of endodontic treatment.

doaj  

Decoding Gas Evolution Pathways and Interfacial Chemistry in Layered Oxide Cathodes for Safer Sodium‐Ion Batteries

Advanced Energy Materials, EarlyView.
Gas evolution behaviors of sodium layered oxide cathodes with varying compositions, cutoff voltages, dopants, and particle sizes/morphologies have been systematically investigated by online electrochemical mass spectrometry. The fundamental outgassing mechanisms of sodium‐based cathodes compared to lithium‐based cathodes have been elucidated.
Chen Liu, Zehao Cui, Arumugam Manthiram
wiley   +1 more source

Evaluation of the efficiency of smear layer removal during endodontic treatment using scanning electron microscopy: an in vitro study

BMC Oral Health
Background The smear layer formed during root canal instrumentation negatively affects root canal irrigation activity, which in turn can affect the treatment prognosis of endodontic treatment.
Svetlana Razumova, Anzhela Brago, Anzhelika Kryuchkova, Vasiliy Troitskiy, Ruzanna Bragunova, Haydar Barakat   +5 more
doaj   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Simultaneous Electronic and Crystallographic Modulation of Cs3Bi2Br9 by Single‐Element Sn Substitution for Enhanced CO2 Photoreduction

Advanced Energy Materials, EarlyView.
Aliovalent B‐site substitution with Sn2+ in lead‐free perovskite, Cs3Bi2Br9, is employed to simultaneously induce lattice contraction and bromine vacancy through charge imbalance and ionic radius mismatch. The resulting structural distortion modulates the electronic structure and improves charge separation, leading to enhanced visible‐light‐driven CO2 ...
Justin Khor, Jiale Lee, Xin Ying Kong, Qixin Zhou, Yongfa Zhu, Jingxiang Low, Siang‐Piao Chai, Lling‐Lling Tan   +7 more
wiley   +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

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
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