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Nano Futures is a peer-reviewed journal published by IOP Publishing, covering Graphene research and applications, Nanowire Synthesis and Applications, 2D Materials and Applications. Over its lifetime it has published 250 papers, which have received 3,478 citations.
| Publisher | IOP Publishing |
|---|---|
| Reference style | Numbered (IOP) Numbered — [1], [2] in the text [1] Smith A, Jones B and Lee C 2023 A representative article title Nano Futures 12 45–58
Formats any DOI in Nano Futures style. No sign-up. |
| Publishes research in | Graphene research and applications Nanowire Synthesis and Applications 2D Materials and Applications Advanced Sensor and Energy Harvesting Materials Machine Learning in Materials Science |
| ISSN | 2399-1984 |
| Citation impact (2-yr) | 4.86 |
| h-index | 29 |
| i10-index | 106 |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | iopscience.iop.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract Artificial photosynthesis via solar water splitting provides a promising approach to storing solar energy in the form of hydrogen on a global scale. However, an efficient and cost-effective solar hydrogen production system that can compete with traditional methods using fossil fuels is yet to be developed. A photoelectrochemical (PEC) tandem cell consisting of a…
Abstract We report multimodal scanning hard x-ray imaging with spatial resolution approaching 10 nm and its application to contemporary studies in the field of material science. The high spatial resolution is achieved by focusing hard x-rays with two crossed multilayer Laue lenses and raster-scanning a sample with respect to the nanofocusing optics. Various techniques are…
Synergistic antimicrobial therapy using nanoparticles and antibiotics for the treatment of multidrug-resistant bacterial infection, Gupta, Akash, Saleh, Neveen M, Das, Riddha, Landis, Ryan F, Bigdeli, Arafeh, Motamedchaboki, Khatereh, Rosa Campos, Alexandre, Pomeroy, Kenneth, Mahmoudi, Morteza, Rotello, Vincent M
Abstract Here we report a design approach for optimizing the toughness of nanocomposite materials using artificial intelligence (AI), implemented in a novel ‘AutoComp Designer’ algorithm. The algorithm consists of a machine learning predictor combined with an AI improved genetic algorithm, which is capable of discovering de novo materials designs in a vast space of possible…
Abstract In this review, we present an update on the methods for screening 2D materials suitable for valleytronic applications. We begin with an introduction to the field highlighting some of the latest findings and seminal works. Then we provide a brief background on the physics of valley- and layer- pseudospins in layered 2D materials such…
