Initial press release on this discovery
Advanced Intelligent Systems was launched in 2019 and rapidly became a top journal for the publication of interdisciplinary intelligent systems related research. The Editors’ Choice articles were handpicked by the editorial team of Advanced Intelligent Systems to showcase the very best that the journal has to offer. The articles represent the key topics that the journal publishes, including artificial intelligence and machine learning, robotics, automation and control, human-machine interface, neuromorphic engineering, quantum computing, smart sensing systems, and stimuli-responsive systems, and highlight work done by researchers from across the globe.
In the past 20 years, flat-optics has emerged as a promising light manipulation technology, surpassing bulk optics in performance, versatility, and miniaturization capabilities. As of today, however, this technology is yet to find widespread commercial applications. One of the challenges is obtaining scalable and highly efficient designs that can withstand the fabrication errors associated with nanoscale manufacturing techniques. This problem becomes more severe in flexible structures, in which deformations appear naturally when flat-optics structures are conformally applied to, for example, biocompatible substrates. Herein, an inverse design platform that enables the fast design of flexible flat-optics that maintain high performance under deformations of their original geometry is presented. The platform leverages on suitably designed evolutionary large-scale optimizers, equipped with fast-trained neural network predictors based on encoder decoder architectures. This approach supports the implementation of flexible flat-optics robust to both fabrication errors or user-defined perturbation stress. This method is validated by a series of experiments in which broadband flexible light polarizers, which maintain an average polarization efficiency of 80% over 200 nm bandwidths when measured under large mechanical deformations, are realized. These results could be helpful for the realization of a robust class of flexible flat-optics for biosensing, imaging, and biomedical devices.
Read more in Advanced Intellignet Systems 202100105 (2021)
While renewable power available worldwide costs increasingly less than the least expensive option based on fossil fuels, countries continue to increase their coal-fired capacity, which should conversely fall by 80% within a decade to limit global warming effects. To address the challenges to the implementation of such an aim, here, a path is explored that leverages on a previously unrecognized aspect of coal, opening to a new solar-driven carbon cycle that is environmentally friendly. By engineering the porosity matrix of coal into a suitably designed compressed volumetric structure, and by coupling it with a network of cotton fibers, it is possible to create a record performing device for freshwater production, with a desalination rate per raw material cost evaluated at 1.39 kg/h/$ at one sun intensity. This value is between two and three times higher than any other solar desalination device proposed to date. These results could envision a clean and socially sustainable cycle for carbon materials that, while enabling an enhanced water economy with global access to freshwater and sanitation, poses zero risks of reinjecting CO2 into the environment through competing economies in the fossil’s market.
Read more in Advanced Sustainable Systems 202100217 (2021)
Talking about carbon, one automatically thinks of carbon nanotubes and fullerenes. But there is much more to this broad subject area. Advances in graphene research, templating methods, and the emergence of nanodiamonds make this field a rich area of research.
The variety of recent breakthroughs indicates that carbon, in all its variations, is the material of the early 21st century. The 2010 Nobel Prize in Physics was awarded to A. Geim and K. S. Novoselov for their work on graphene.
Don’t miss the hottest results and newest trends—you’ll find the latest carbon research articles here.
Integrating conventional optics into compact nanostructured surfaces is the goal of flat optics. Despite the enormous progress in this technology, there are still critical challenges for real-world applications due to the limited operational efficiency in the visible region, on average lower than 60%, which originates from absorption losses in wavelength-thick (≈ 500 nm) structures. Another issue is the realization of on-demand optical components for controlling vectorial light at visible frequencies simultaneously in both reflection and transmission and with a predetermined wavefront shape. In this work, we developed an inverse design approach that allows the realization of highly efficient (up to 99%) ultrathin (down to 50 nm thick) optics for vectorial light control with broadband input–output responses in the visible and near-IR regions with a desired wavefront shape. The approach leverages suitably engineered semiconductor nanostructures, which behave as a neural network that can approximate a user-defined input–output function. Near-unity performance results from the ultrathin nature of these surfaces, which reduces absorption losses to near-negligible values. Experimentally, we discuss polarizing beam splitters, comparing their performance with the best results obtained from both direct and inverse design techniques, and new flat-optics components represented by dichroic mirrors and the basic unit of a flat-optics display that creates full colours by using only two subpixels, overcoming the limitations of conventional LCD/OLED technologies that require three subpixels for each composite colour. Our devices can be manufactured with a complementary metal-oxide-semiconductor (CMOS)-compatible process, making them scalable for mass production at low cost.
Read more in Light: Science & Applications volume 10, Article number: 47 (2021)
Not being able to accurately forecast sunny, cloudy, or rainy conditions isn’t great. But for one Saudi Arabia-based professor, our unpredictable weather sparked an idea for how to truly secure electronic communication.
Read the whole interview on WIRED here
An ultra-dark material developed in Saudi Arabia is no mere fashion statement: its ability to soak up the rays promises to boost solar-cell efficiency.
Silicon-based photovoltaic (PV) solar panels have a maximum theoretical absorption capacity of about 30 percent, while in practice it tops out at about 26 percent.
Fratalocchi is coy about progress, given the latest research has yet to be published, but suggested a solution was on its way. “It’s inexpensive; we just set up the process to manufacture it on large scales. It’s industry-ready,” he says.
The new material will be independently certified by a German agency, although the pandemic has slowed this process. “If this efficiency is higher than conventional solar material, it can become the standard for PV, because it’s already compatible with mass-production methods,” says Fratalocchi.
Enhancing solar panels is just one potential application for Fratalocchi’s nanomaterial. While he wouldn’t discuss others in detail due to confidentiality concerns, he did point to hydrogen as a possibility. If light could be more efficiently harvested and used to make hydrogen through hydrolysis, humanity could, at last, possess an inexpensive, abundant, and completely clean energy source. And, by then, the old black gold would be just a distant memory.
Read the whole interview on WIRED here
Physical unclonable functions (PUFs) are complex physical objects that aim at overcoming the vulnerabilities of traditional cryptographic keys, promising a robust class of security primitives for different applications. Optical PUFs present advantages over traditional electronic realizations, namely, a stronger unclonability, but suffer from problems of reliability and weak unpredictability of the key. We here develop a two-step PUF generation strategy based on deep learning, which associates reliable keys verified against the National Institute of Standards and Technology (NIST) certification standards of true random generators for cryptography. The idea explored in this work is to decouple the design of the PUFs from the key generation and train a neural architecture to learn the mapping algorithm between the key and the PUF. We report experimental results with all-optical PUFs realized in silica aerogels and analyzed a population of 100 generated keys, each of 10,000 bit length. The key generated passed all tests required by the NIST standard, with proportion outcomes well beyond the NIST’s recommended threshold. The two-step key generation strategy studied in this work can be generalized to any PUF based on either optical or electronic implementations. It can help the design of robust PUFs for both secure authentications and encrypted communications.
Read more here
We are delighted to announce that our article “Perfect secrecy cryptography via mixing of chaotic waves in irreversible time-varying silicon chips” was the most read Nature Communications physics articles in 2019, ranked No. 1.
The journal published more than 5,500 papers in 2019. You may access the full lists of Top 50 articles across the four main Nature Communications research areas by visiting https://www.nature.com/ncomms/top50.