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Wind–Wave Coupling Effect on the Dynamic Response of a Combined Wind–Wave Energy Converter

Jinghui Li, Wei Shi, Lixian Zhang, Constantine Michailides et al. • Journal of Marine Science and Engineering (2021)

There is a huge energy demand from offshore renewable energy resources. To maximize the use of various renewable energy sources, a combined floating energy system consisting of different types of energy devices is an ideal option to reduce ...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse9101101

Interpretable and Explainable Machine Learning for Materials Science and Chemistry

Felipe Oviedo, Juan Lavista Ferres, Tonio Buonassisi, Keith T. Butler • Accounts of Materials Research (2022)

High Resolution Image Download MS PowerPoint Slide Conspectus Machine learning has become a common and powerful tool in materials research. As more data become available, with the use of high-performance computing and high-throughput experi...

OPENALEX cc-by DOI: https://doi.org/10.1021/accountsmr.1c00244

Combinatorial Materials Science and Catalysis

Bernd Jandeleit, Dieter J. Schaefer, Timothy S. Powers, Howard W. Turner et al. • Angewandte Chemie International Edition (1999)

After forever changing the drug discovery process in the pharmaceutical industry, combinatorial chemistry methodologies are increasingly being applied to the discovery and optimization of more efficient catalysts and materials (see picture)...

OPENALEX DOI: https://doi.org/10.1002/(sici)1521-3773(19990903)38:17<2494::aid-anie2494>3.0.co;2-#

Phase prediction, microstructure and high hardness of novel light-weight high entropy alloys

Jon Mikel Sanchez, Iban Vicario, Joseba Albizuri, Teresa Guraya et al. • Journal of Materials Research and Technology (2019)

Guided by CALPHAD modeling, low-density and multiphase three novel High Entropy Alloys (HEAs), Al40Cu15Cr15Fe15Si15, Al65Cu5Cr5Si15Mn5Ti5 and Al60Cu10Fe10Cr5Mn5Ni5Mg5 were produced by large scale vacuum die casting. A mixture of simple and ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jmrt.2018.06.010

On the Challenges of Quantum Circuit Encoding Using Deep and Reinforcement Learning

Patrick Selig, Niall Murphy, David Redmond, Simon Caton • IEEE Access (2025)

Quantum computers may solve some computing tasks more efficiently than classical com- puters, but to do so requires the design of appropriate quantum circuits. However, it is hard to design even simple quantum programs. Recent results have ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3564392

Expressibility and trainability of parametrized analog quantum systems for machine learning applications

Jirawat Tangpanitanon, Supanut Thanasilp, Ninnat Dangniam, Marc-Antoine Lemonde et al. • Physical Review Research (2020)

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for near-term quantum devices. In digital quantum computing, it has been shown that random parametrized quantum circuits are able to express complex dis...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.2.043364

Cyclic order superpositions enable quantum information transmission through completely depolarizing channels

Yaxin Wang, Linxiang Zhou, Tianfeng Feng, Hanlin Nie et al. • Communications Physics (2026)

Abstract Noise fundamentally limits quantum communication capacity, completely preventing information transmission in fully depolarizing environments. While indefinite causal order theoretically circumvents this limitation, experimentally r...

DOAJ Open Access (DOAJ) DOI: 10.1038/s42005-026-02698-1

Present landscape of quantum computing

Vikas Hassija, Vinay Chamola, Vikas Saxena, Vaibhav Chanana et al. • IET Quantum Communication (2020)

Quantum computing is currently a topic of interest that harnesses the phenomena of quantum mechanics. It can address several scientific challenges and generate new business opportunities. Recently, for the first time in the history of quant...

OPENALEX cc-by-nc DOI: https://doi.org/10.1049/iet-qtc.2020.0027

The future of quantum computing with superconducting qubits

Sergey B. Bravyi, Oliver Dial, Jay Gambetta, Darı́o Gil et al. • Journal of Applied Physics (2022)

For the first time in history, we are seeing a branching point in computing paradigms with the emergence of quantum processing units (QPUs). Extracting the full potential of computation and realizing quantum algorithms with a super-polynomi...

OPENALEX Open Access DOI: https://doi.org/10.1063/5.0082975

Quantum Computability

Leonard M. Adleman, Jonathan DeMarrais, Ming-Deh A. Huang • SIAM Journal on Computing (1997)

In this paper some theoretical and (potentially) practical aspects of quantum computing are considered. Using the tools of transcendental number theory it is demonstrated that quantum Turing machines (QTM) with rational amplitudes are suffi...

OPENALEX DOI: https://doi.org/10.1137/s0097539795293639

ℤ<sub>2</sub> × ℤ<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks

Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale, Roy T. Forestano et al. • Axioms (2024)

This paper presents a comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNNs) and Quantum Neural Networks (QNNs), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENNs) and Deep Ne...

DOAJ Open Access (DOAJ) DOI: 10.3390/axioms13030188

Rarefied Reactive Gas Flows over Simple and Complex Geometries Using an Open-Source DSMC Solver

Rodrigo Cassineli Palharini, João Luiz F. Azevedo, Diego Vera Sepúlveda • Aerospace (2025)

During atmospheric reentry, a significant number of chemical reactions are produced inside the high-temperature shock wave formed upstream of the spacecraft. Chemical reactions can significantly alter the flowfield structure surrounding the...

DOAJ Open Access (DOAJ) DOI: 10.3390/aerospace12080651

A quantum fuzzy logic-enhanced evolutionary framework for energy-latency optimization in 6G Edge-IioT

Siavash Siavashian Rashidi, Ali Broumandnia, Abbas Mirzaei, Ramin Karimi • Scientific Reports (2026)

Abstract The transition toward 6G-enabled Industrial Internet of Things (IIoT) requires strict Ultra-Reliable Low-Latency Communication (URLLC), creating a fundamental trade-off with energy consumption. Orchestrating resources in dense, hyp...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-55177-6

Cosmic muon flux attenuation methods for superconducting qubit experiments

Elia Bertoldo, Victor Pérez Sánchez, Maria Martínez, Manel Martínez et al. • New Journal of Physics (2025)

We propose and demonstrate two practical mitigation methods to attenuate the cosmic muon flux, compatible with experiments involving superconducting qubits: shallow underground sites and device orientation. Using a specifically-built cosmic...

DOAJ Open Access (DOAJ) DOI: 10.1088/1367-2630/adaedc

Quantum Computing for Healthcare: A Review

Raihan Ur Rasool, Hafiz Farooq Ahmad, Wajid Rafique, Adnan Qayyum et al. • Future Internet (2023)

In recent years, the interdisciplinary field of quantum computing has rapidly developed and garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to ...

OPENALEX cc-by DOI: https://doi.org/10.3390/fi15030094

Coalition of explainable artificial intelligence and quantum computing in precision medicine

Soumyadeep Ray, Pronaya Bhattacharya, Ebrahim A. Mattar, Abhishek Mukhopadhyay • Computational and Structural Biotechnology Journal (2025)

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning model...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.csbj.2025.11.031

Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine learning approaches

Kamal Hossain Nahin, Jamal Hossain Nirob, Akil Ahmad Taki, Md Ashraful Haque et al. • Scientific Reports (2025)

Abstract This paper introduces the design and exploration of a compact, high-performance multiple-input multiple-output (MIMO) antenna for 6G applications operating in the terahertz (THz) frequency range. Leveraging a meta learner-based sta...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-88174-2