Technical / Research

Graphene’ s quantum properties, such as superconductivity and other unique quantum behaviors, are known to arise when graphene atomic layers are stacked and twisted with precision to produce “ABC stacking domains.” Historically, achieving ABC stacking domains required exfoliating graphene and manually twisting and aligning layers with exact orientations—an intricate process that is difficult to scale for industrial applications.

Recently, researchers at NYU Tandon School of Engineering and Charles University in Prague, led by Elisa Riedo and Herman F. Mark, uncovered a new phenomenon in graphene research, observing growth-induced self-organized ABA and ABC stacking domains that could promote the development of advanced quantum technologies. The findings of their study demonstrate how specific stacking arrangements in three-layer epitaxial graphene systems emerge naturally — eliminating the need for complex, non-scalable techniques traditionally used in graphene twisting fabrication.

Researchers from the University of California, Harvard University, University of Manchester, UC Santa Cruz and the National Institute for Materials Science in Tsukuba, Japan have conducted an experiment that confirms a 40 year old theory that electrons confined in quantum space would move along common paths rather than producing a chaotic array of trajectories.

Electrons exhibit both particle and wave-like properties and behave in ways that are often counterintuitive, and under certain conditions, their waves can interfere with each other in a way that concentrates their movement into certain patterns. Physicists call these common paths “unique closed orbits.”

Researchers from North Carolina State University and Iowa State University have demonstrated a new technique for self-assembling electronic devices. The proof-of-concept work was used to create diodes and transistors, and could pave the way for self-assembling more complex electronic devices without relying on existing computer chip manufacturing techniques.

D-Met fabricated patterns produce components for potential use in microelectromechanical systems (MEMS). Image credit: Julia Chang and NCSU.

“Existing chip manufacturing techniques involve many steps and rely on extremely complex technologies, making the process costly and time consuming,” says Martin Thuo, corresponding author of a paper on the work and a professor of materials science and engineering at North Carolina State University. “Our self-assembling approach is significantly faster and less expensive. We’ve also demonstrated that we can use the process to tune the bandgap for semiconductor materials and to make the materials responsive to light – meaning this technique can be used to create optoelectronic devices. What’s more, current manufacturing techniques have low yield, meaning they produce a relatively large number of faulty chips that can’t be used. Our approach is high yield – meaning you get more consistent production of arrays and less waste.”

MIT researchers have gained new understanding of what leads electrons to split into fractions of themselves. Their solution sheds light on the conditions that give rise to exotic electronic states in graphene and other two-dimensional systems.

The recent work attempts to make sense of a discovery that was reported earlier this year by a different group of physicists at MIT, led by Assistant Professor Long Ju. Ju’s team found that electrons appear to exhibit “fractional charge” in pentalayer graphene — a configuration of five graphene layers that are stacked atop a similarly structured sheet of boron nitride.

Researchers from CNR-IOM, University of Milano-Bicocca, University of Trieste and University of Vienna have developed a method to create new materials that combine the extraordinary properties of single metal atoms with the robustness, flexibility, and versatility of graphene.

Co and Ni adatoms diffusing across the substrate surface before being incorporated in the growing edge of the Gr layer. Image from: Science Advances 

The method involves the controlled deposition of metal atoms, such as cobalt, during the formation of the graphene layer on a nickel surface. Some of these atoms are incorporated into the carbon network of graphene, creating a material with exceptional properties of robustness, reactivity, and stability even under critical conditions.

When two sheets of are stacked together and offset at a slight angle, the bilayer material can produce numerous intriguing effects, notably superconductivity. Cornell University researchers have gained new understanding on how twisted bilayer graphene achieves this state, by identifying its highest achievable superconducting temperature – 60 Kelvin. The finding is said to be mathematically exact, a rare feat in the field, and is spurring new insights into the factors that fundamentally control superconductivity. 

“Looking ahead, this paves the way for understanding what are the possible degrees of freedom that one should try to control and optimize in order to enhance the tendency towards superconductivity in these two-dimensional material platforms,” said Debanjan Chowdhury, who co-authored the recent study.

Researchers at the University of Virginia, Ajou University and Soongsil University have developed an AI-powered system that mimics the human sense of smell to detect and track toxic gases in real time. Using advanced artificial neural networks combined with a network of sensors, the system quickly identifies the source of harmful gases like nitrogen dioxide (NO₂) that poses severe respiratory health risks.

Schematic of biological and artificial olfactory receptor. Biological receptors interact with odor molecules through specific binding, whereas artificial receptors use catalytic dissociation by Pd nano-islands for selective gas molecule adsorption on graphene surfaces. Image credit: Science Advances

The artificial olfactory receptor features nano-islands of metal-based catalysts that cover a graphene surface on the heterostructure of an AlGaN/GaN two-dimensional electron gas (2DEG) channel. Catalytically dissociated NO₂ molecules bind to graphene, thereby modulating the conductivity of the 2DEG channel and allowing the system to detect gas leaks with extreme sensitivity.

Researchers from ISMN-CNR have introduced GrapheNet, a deep learning framework based on an Inception-Resnet architecture using image-like encoding of structural features for the prediction of the properties of nanographenes.

Scheme of the GrapheNet framework. Image from Scientific Reports

By exploiting the planarity of quasi-bidimensional systems and through encoding structures into images, and leveraging the flexibility and power of deep learning in image processing, Graphenet is said to achieve significant accuracy in predicting the physicochemical properties of nanographenes. 

A research team from the University of Córdoba (UCO) has developed a new prototype that could lead opens the door to the large-scale production of graphene. This new method, which has already been registered for evaluation as a patent and is based on a previous patent by the same team, increases the production of graphene by more than 22%, with the process maintaining the high quality that characterizes graphene synthesized with this technology.

The work is based on plasma technology, a partially ionized gas often referred to as the fourth state of matter. One of its great advantages, highlighted the study's lead author, Francisco Javier Morales, is that "it is a highly energetic medium that is capable of breaking down organic molecules very easily." Specifically, the team used this plasma torch to break down ethanol and rearrange the molecule's carbon atoms, resulting in the creation of graphene.

An international group of scientists, including ones from the UK's University of Bath, Friedrich Schiller University Jena in Germany and the University of Pisa in Italy, recently set out to investigate the ultrafast opto-electronic and thermal tuning of nonlinear optics in graphene.

Opto-electronic modulation of third harmonic generation in a graphene field-effect transistor. The illustration includes a sketch and a microscopic optical image of the device. Image credit: University of Bath

Nonlinear optics explores how powerful light (e.g. lasers) interacts with materials, resulting in the output light changing color (i.e. frequency) or behaving differently based on the intensity of the incoming light. This field is important for developing advanced technologies such as high-speed communication systems and laser-based applications. Nonlinear optical phenomena enable the manipulation of light in novel ways, leading to breakthroughs in fields like telecommunications, medical imaging, and quantum computing. Graphene's exceptional electronic properties, related to relativistic-like Dirac electrons and strong light-matter interactions, make it promising for nonlinear optical applications, including ultrafast photonics, optical modulators, saturable absorbers in ultrafast lasers, and quantum optics.