Results 131 to 140 of about 8,744,702 (255)

Evaluating the Effectiveness of Large Language Models (LLMs) Versus Machine Learning (ML) in Identifying and Detecting Phishing Email Attempts

Phishing emails remain a significant concern and a growing cybersecurity threat in online communication. They often bypass traditional filters due to their increasing sophistication.
Saed Tarapiah, Yassine Himeur, Linda Abbas, Oula Mardawi, Shadi Atalla, Wathiq Mansoor   +5 more
core   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

ML-NIC: accelerating machine learning inference using smart network interface cards

Frontiers in Computer Science
Low-latency inference for machine learning models is increasingly becoming a necessary requirement, as these models are used in mission-critical applications such as autonomous driving, military defense (e.g., target recognition), and network traffic ...
Raghav Kapoor, David C. Anastasiu, Sean Choi   +2 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley   +1 more source

P2MAT: A machine learning (ML) driven software for Property Prediction of MATerial

Journal of Cheminformatics
Accurate prediction of melting points for pure molecules remains a significant challenge in predictive chemistry, with implications across various scientific fields, including materials science, drug discovery, and separations chemistry.
Methun Kamruzzaman, Alexander Landera, Nalini Menon, Mark D. Allendorf, Kunal Poorey   +4 more
doaj   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

Artificial intelligence (AI) and machine learning (ML) for beyond 5G/6G communications

EURASIP Journal on Wireless Communications and Networking, 2023
Mohammad Abdul Matin, Sotirios K. Goudos, Shaohua Wan, Panagiotis Sarigiannidis, Emmanouil M. Tentzeris   +4 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Recent Progress in the Phase‐Controlled Synthesis of Ruthenium Nanocrystals for Catalytic Applications

Advanced Materials, EarlyView.
Template effect and kinetic control enable crystal‐phase engineering of Ru nanocrystals, granting access to either metastable fcc‐Ru or stable hcp‐Ru with distinct surface structures, thermal stabilities, and catalytic behaviors. Moreover, the hcp‐Ru can further serve as an epitaxial template to direct Pd and Rh nanocrystals into the metastable hcp ...
Jianlong He, Zhiqi Wang, Jiaqi Guan, Younan Xia   +3 more
wiley   +1 more source