Results 81 to 90 of about 23,653 (255)

A Future with Quantum Machine Learning

Computer, 2018
Could combining quantum computing and machine learning with Moore’s law produce a true “rebooted computer”? This article posits that a three-technology hybrid-computing approach might yield sufficiently improved answers to a broad class of problems such that energy efficiency will no longer be the dominant concern.
openaire   +2 more sources

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

Quantum machine learning for electronic structure calculations

Nature Communications, 2018
With the rapid development of quantum computers, quantum machine learning approaches are emerging as powerful tools to perform electronic structure calculations.
Rongxin Xia, Sabre Kais
doaj   +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

Zc(3900) observation at BESIII with QSVM method [PDF]

EPJ Web of Conferences
In recent years, quantum computing shows significant potentials in many areas. In this proceeding, we revisit the observation of the Zc(3900) resonance with quantum machine learning techniques, specifically quantum support vector machine (QSVM ...
Ding Biao, Meng Zhaoxia, Zou Jiaheng, Li Teng, Lin Tao   +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

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

Advanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald, Hiroki Tomita, Giacomo Cotelli, Louka L. Brüll, Nanno G. de Rooij, Lucas R.L. Norg, Milo Clément, Reinder Coehoorn   +7 more
wiley   +1 more source

Investigating the potential of Quantum Inspired Machine Learning approaches for mental health detection of young adults

ITEGAM-JETIA
Medical Health Informatics has envisaged quantum computing as flurry of promising solutions to deal with mental health related issues of young adults in recent times.
Mrutyunjaya Panda, Saumya Ranjan Mahanta
doaj   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

VQE-generated quantum circuit dataset for machine learning

Physical Review Research
Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical problems.
Akimoto Nakayama, Kosuke Mitarai, Leonardo Placidi, Takanori Sugimoto, Keisuke Fujii   +4 more
doaj   +1 more source