Results 111 to 120 of about 137,793 (228)
Toward structure-preserving quantum encodings
Harnessing the potential computational advantage of quantum computers for machine learning tasks relies on the uploading of classical data onto quantum computers through what are commonly referred to as quantum encodings. The choice of such encodings may
Arthur J. Parzygnat +3 more
doaj +1 more source
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
Quantum machine learning and quantum biomimetics: A perspective
AbstractQuantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to employ machine learning techniques to better control quantum systems.
openaire +4 more sources
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 +7 more
wiley +1 more source
Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
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 +7 more
wiley +1 more source
Nanomaterial Integration at Liquid–Liquid Interfaces for Green Catalysis
Functional nanomaterials assembled at liquid–liquid interfaces create dual‐role platforms serving as emulsion stabilizers and catalytic sites, offering enhanced reaction kinetics with improved catalyst recovery and recyclability. This review examines design strategies, structure‐performance relationships, and industrial implementation prospects of ...
Bokgi Seo +6 more
wiley +1 more source
Hands-On Introduction to Quantum Machine Learning
This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement).
Muhammad Ismail +2 more
doaj +1 more source
Zero‐dimensional carbon nanomaterials are presented as multifunctional platforms linking structure, property, and sensing performance. Surface engineering and heteroatom doping modulate electron‐transfer and luminescent behavior, enabling electrochemical, photoluminescent, and electrochemiluminescent detection. Fundamental design principles, analytical
Gustavo Martins +8 more
wiley +1 more source
Guided quantum compression for high dimensional data classification
Quantum machine learning provides a fundamentally different approach to analyzing data. However, many interesting datasets are too complex for currently available quantum computers.
Vasilis Belis +5 more
doaj +1 more source
Nanozymes (NZs) have emerged as versatile artificial enzymes with tunable catalytic properties driven by atomic coordination, defect engineering, and surface chemistry. This review presents a bio–nano interface framework linking synthesis strategies, structural design, and catalytic behavior within complex biological microenvironments.
Karen Guadalupe Quintero‐Garrido +6 more
wiley +1 more source

