Computational Discovery of New 2D Materials Using Deep Learning Generative Models.

The isolation of graphene has sparked an unprecedented world wide research activity on the topic of two-dimensional (2D) materials. However, even though graphene has a high potential for various applications, its metallic character is a significant limitation for a large variety of electron devices, starting with the conventional field effect transistor. This limitation could be overcome in the near future by the use of layered van der Waals crystals such as black phosphorus (i.e., phosphorene, which is one to few layers of black phosphorus) and also by other semiconducting 2D materials such as transition metal dichalcogenides (TMDCs) of general formula MX2, where M is the metal and X the chalcogen (S, Se and Te). For instance, phosphorene exhibits a direct band gap varying between ~ 0.3 eV for bulk crystals to ~ 2 eV for a monolayer. In layered TMDC structures, each layer typically comprises 3 atomic planes (corresponding to a thickness below 8 Å), and consists of an hexagonally-organized atomic layer of metal atoms sandwiched between two planes of chalcogen atoms, also in hexagonal configurations. M–X bonds inside each layer are covalent; however, the sandwiching chalcogen layers are linked by weak van der Waals bonds, so that a bulk crystal is easy to cleave along the chalcogen planes. As with phosphorene, most semiconducting TMDC materials also see their band gap increasing as thickness decreases and they switch from indirect to direct band gap for a monolayer. To date, the most studied semiconductor TMDCs are MoS2 and WS2. Because they are atomically thin, 2D materials are particularly well suited for flexible electronics applications. After a brief description of the major features of phosphorene and TMDCs (crystal structures, relevant electronic properties as a function of thickness …), the talk will highlight recent results concerning field effect transistor characteristics. In particular, carrier mobility values as high as 5000 cm2/Vs have been measured in phosphorene films. Since local substitutional-type doping cannot be used in 2D materials, there is a general contacting problem (Schottky barrier formation), which is of paramount importance for device applications. In particular, two types of contacts can be formed: the top contact and the edge contact, which behave differently. Generally speaking, the semiconductor thickness is much smaller than the depletion length at the contact, which is an intriguing and novel situation. In the second part of the talk, various synthesis methods will be presented and discussed, particularly in view of their possible use in the field of large area electronics. For most devices fabricated so far, the 2D layers were obtained by exfoliation of bulk crystals. However, recent progress in synthesis include molecular beam epitaxy, controlled chemical vapour deposition and vapour phase transport. Those various approaches will be discussed, as well as the newly-introduced atomic layer deposition (ALD) process. As most 2D materials are grown on a separate substrate, the transfer problem will be highlighted, particularly concerning phosphorene which is highly hygroscopic, and sensitive to the presence of light. The presentation will be concluded by some perspectives concerning the industrialization of 2D materials.

Unconventional antiferromagnetism dubbed as altermagnetism was first discovered in rutile structured magnets, which is featured by spin splitting even without the spin–orbital coupling effect. This interesting phenomenon has been discovered in more altermagnetic materials. In this work, we explore two-dimensional altermagnetic materials by studying two series of two-dimensional magnets, including MF4 with M covering all 3d and 4d transition metal elements, as well as TS2 with T = V, Cr, Mn, Fe. Through the magnetic symmetry operation of RuF4 and MnS2, it is verified that breaking the time inversion is a necessary condition for spin splitting. Based on symmetry analysis and first-principles calculations, we find that the electronic bands and magnon dispersion experience alternating spin splitting along the same path. This work paves the way for exploring altermagnetism in two-dimensional materials.

The strong advantage of two-dimensional (2D) materials is that they exhibit interesting physical properties down to the single unit layer (typically less than 1 nm). Such emergent properties are highly dependent on thickness and can be tunable via external parameters such as electric field, pressure, and/or chemical treatment. In addition, most 2D materials have hexagonal crystal structures; thus, it is possible to stack with other 2D materials to enrich the properties. This tunability and compatibility makes 2D materials and their heterostructures promising candidates for optoelectronic devices.

Thermal-protective and oxygen-resistant nanocoating using silica-nanocomposites for laser thinning of polymorphic molybdenum ditellurides

The development of two-dimensional (2D) materials for biomedical applications has accelerated exponentially. Contrary to their bulk counterparts, the exceptional properties of 2D materials make them highly prospective for contrast agents for bioimage, drug, and heat delivery in biomedical treatment. Nevertheless, empty space in the integration and utilisation of 2D materials in living biological systems, potential toxicity, as well as required complicated synthesis and high-cost production limit the real application of 2D materials in those advance medical treatments. On the other hand, green technology appears to be one of strategy to shed a light on the blurred employment of 2D in medical applications, thus, with the increasing reports of green technology that promote advanced technologies, here, we compile, summarise, and synthesise information on the biomedical technology of 2D materials through green technology point of view. Beginning with a fundamental understanding, of crystal structures, the working mechanism, and novel properties, this article examines the recent development of 2D materials. As well as 2D materials made from natural and biogenic resources, a recent development in green-related synthesis was also discussed. The biotechnology and biomedical-related application constraints are also discussed. The challenges, solutions, and prospects of the so-called green 2D materials are outlined.

Top-down exfoliation of layered solids has revolutionized materials innovation by enabling unprecedented access to atomically thin architectures. To expand the frontier of two-dimensional (2D) materials, it is imperative to systematically identify non-van der Waals (non-vdW) layered systems with strong interlayer bonding. While conventional atomic distance-based algorithms effectively identify vdW materials, they are considerably limited when applied to chemically bonded non-vdW systems due to their inherent bonding complexity. Here, we introduce a structural modularity paradigm that resolves dimensional identification challenges by removing specific elements from strongly bonded crystals to construct artificial substructures from residual atoms. Coupled with the appropriate layer-recognition algorithms for vdW lattices, this approach reveals 8,889 hidden 2D modules across 30,147 ternary compounds, of which 80.6% are undetectable by traditional layer-detection approaches. These findings show that non-vdW layered solids significantly outnumber vdW counterparts (1,383), highlighting a vast chemical space for 2D materials exploration. High-throughput thermodynamic screening of 15,312 ternary oxides identifies 1,083 chemically stable 2D modules exfoliable via a proton exchange-assisted method. Validation against 15 experimentally reported 2D oxide nanosheets, along with the first synthesis of ultrathin HxRuO3 nanosheets from non-vdW Na2RuO3 crystal, confirms the reliability and predictive strength of this method for both known and previously unexplored systems.

Janus transition metal dichalcogenides (JTMDs) have garnered significant interest from the scientific community owing to their remarkable physical and chemical features. The existence of intrinsic dipoles makes them different from conventional transition metal dichalcogenides. These properties are useful in various potential applications, including energy storage, energy generation, and other electronic devices. The JTMDs are considered a hot topic in two dimensional (2D) materials research, making it necessary to understand their fundamental properties and potential use in various applications. This review covers the fundamental difference between Janus and conventional transition metal dichalcogenide‐based 2D materials. This discussion encompasses the characteristics of monolayer, bilayer, and multilayer materials, focusing on their structural stability, electronics properties, optical properties, piezoelectricity, and Rashba effects. The impact of external stimuli such as strain and electric field toward engineering the ground state properties of monolayer JTMDs is discussed. Additionally, various potential applications of Janus monolayers, including gas sensors, catalysis, electrochemical energy storage, thermoelectric, solar cells, and field effect transistors, are highlighted, emphasizing enhancing their performance. Finally, the prospects of Janus 2D materials for next‐generation electronic devices are highlighted.

Automated design synthesis has the potential to revolutionize the modern engineering design process and improve access to highly optimized and customized products across countless industries. Successfully adapting generative machine learning to design engineering may enable such automated design synthesis and is a research subject of great importance. We present a review and analysis of deep generative machine learning models in engineering design. Deep generative models (DGMs) typically leverage deep networks to learn from an input dataset and synthesize new designs. Recently, DGMs such as feedforward neural networks (NNs), generative adversarial networks (GANs), variational autoencoders (VAEs), and certain deep reinforcement learning (DRL) frameworks have shown promising results in design applications like structural optimization, materials design, and shape synthesis. The prevalence of DGMs in engineering design has skyrocketed since 2016. Anticipating the continued growth, we conduct a review of recent advances to benefit researchers interested in DGMs for design. We structure our review as an exposition of the algorithms, datasets, representation methods, and applications commonly used in the current literature. In particular, we discuss key works that have introduced new techniques and methods in DGMs, successfully applied DGMs to a design-related domain, or directly supported the development of DGMs through datasets or auxiliary methods. We further identify key challenges and limitations currently seen in DGMs across design fields, such as design creativity, handling constraints and objectives, and modeling both form and functional performance simultaneously. In our discussion, we identify possible solution pathways as key areas on which to target the future work.

Computational synthesis of 2D materials: A high-throughput approach to materials design

Sliding ferroelectricity (FE) in two-dimensional (2D) materials offers a promising route to ultrathin, low-power, nonvolatile devices, yet in pristine homobilayers it is typically weak and confined to a small subset of known 2D materials. This limitation prompts a central question: Can sliding FE be reliably induced and substantially enhanced in otherwise nonferroelectric homobilayers through a controllable, experimentally feasible intervention? Here, we combine high-throughput first-principles calculations with machine learning to establish atomic intercalation as a versatile strategy for activating and amplifying sliding FE. Notably, we identify pristine InP and GaP as record performers, exhibiting out-of-plane polarizations up to 21.0 pC/m, approximately ten times greater than experimentally synthesized BN and over 45 times higher than $\mathrm{Mo}{\mathrm{S}}_{2}$, while maintaining moderate switching barriers of just 13.6 and 32.0 meV/f.u. Intercalation with Cu, Ag, and Au expands the pool from 106 pristine sliding FE systems to 591, including 212 activated from initially nonferroelectric states. To accelerate exploration of this enlarged configurational space, we develop a descriptor-free graph neural network incorporating message passing and global attention, enabling direct polarization prediction from atomic configurations. This integrated computational--machine learning framework delivers a robust and tunable pathway for designing high-performance sliding ferroelectrics and a blueprint for targeted discovery of functional 2D materials.

Phase-changeable two-dimensional materials: Classification, mechanisms, and applications

Determining lattice parameters in two-dimensional (2D) materials is essential for materials characterization and discovery. In this work, we propose a deep-learning-driven pipeline that addresses the regression task of estimating the lattice constants a and b and the angle γ directly from 2D images using computer vision. We evaluate our approach on three different 2D material data sets: JARVIS-2D (JV2D) and Computational 2D Materials Database (C2DB), and a newly created data set derived from the Alexandria database. Multiple architectures are compared, including DenseNet121, Vision Transformers (ViT-L/14) paired with Multi Layer Perceptron (MLP) heads, and GoogleNet. DenseNet121 achieves accurate performance, with mean absolute errors as low as 0.18 Å for the Alexandria-based data set and 0.17 Å for C2DB and 0.59 Å for JV2D, as well as up to 96% accuracy in classifying Bravais lattice types for the Alexandria-based data set.

The omnipresence of polarized light on the surface of the earth, a result of atmospheric scattering, underscores the significance of detecting this light and extracting valuable information regarding the phase and polarization angle. In recent years, there has been a surge in research on polarization-sensitive photodetectors that utilize anisotropic two-dimensional (2D) materials. The essence of these 2D polarization-sensitive photodetectors is rooted in the anisotropic characteristics that arise from the asymmetric crystal lattice of the 2D materials in question. This anisotropy is manifested in both optical and electrical behaviors due to the asymmetrical nature of the crystal structure. This article systematically categorizes anisotropic 2D materials and offers an insightful overview of their crystal structures. It also introduces various optical and electrical characterization techniques designed to elucidate the anisotropic properties of these materials. The focus of the article then shifts to detailing the current state of research in the realm of anisotropic 2D material-based polarization-sensitive photodetectors. It provides a comprehensive description of the working principles behind polarization-sensitive photodetectors with different structural designs, shedding light on the underlying mechanisms that enable their polarization sensitivity. In conclusion, the article summarizes the findings of this review, highlighting the advancements and challenges in the field. Additionally, this review proposes several forward-looking recommendations to guide the future trajectory of research and development in the domain of 2D material-based polarization-sensitive photodetectors.

Recent advances in two-dimensional (2D) materials have led to the renewed interest in intercalation as a powerful fabrication and processing tool. Intercalation is an effective method of modifying the interlayer interactions, doping 2D materials, modifying their electronic structure or even converting them into starkly different new structures or phases. Herein, we discuss different methods of intercalation and provide a comprehensive review of various roles and applications of intercalation in next‐generation energy storage, optoelectronics, thermoelectrics, catalysis, etc. The recent progress in intercalation effects on crystal structure and structural phase transitions, including the emergence of quantum phases are also reviewed.

Monolayer chromium dichloride: An anti-ferromagnetic semiconductor with a high Néel temperature above room temperature