α-MnTe is a prototypical altermagnet exhibiting a strong anomalous Hall effect (AHE), despite having a nearly vanishing magnetization. Lately, sample-to-sample variations of the amplitude of the AHE have raised concerns of a possible defect related origin, especially in thin films. Here, we study the AHE in α-MnTe films grown on SrF2 that have the crystal structure and m'm'm magnetic point group symmetry expected for bulk. By studying the scaling of the AHE with conductivity for those films and previously reported measurements in the literature, we find that sample-to-sample variations are well explained by a scaling law consistent with a hopping origin. Importantly, a comparison with other magnetic semiconductors reveals the colossal amplitude of the AHE of α-MnTe compared to its measured spontaneous magnetization from magnetometry and polarized neutron reflectivity. Our findings address the important fundamental question of the origin of the AHE of α-MnTe and further demonstrate the potential of altermagnets as promising spintronic materials.

MnSb is a metallic ferromagnet with a high Curie temperature (∼587 K) and strong spin–orbit coupling, making it attractive for room-temperature spintronic and magnetic sensing applications. We report heteroepitaxial growth of MnSb on GaAs (111) by molecular beam epitaxy, yielding locally epitaxial, strain-relaxed island structures with multiple dominant crystallographic orientations. Structural analysis reveals the coexistence of basal-plane- and pyramidal-plane-oriented domains, enabling investigation of magneto-crystalline anisotropy in an orientationally inhomogeneous ferromagnetic system. Room-temperature magnetic characterization using magnetic force microscopy, scanning nitrogen-vacancy center magnetometry, and angle-dependent ferromagnetic resonance demonstrates a strongly anisotropic, orientation-dependent magnetic response across multiple length scales. Correlating these magnetic responses with crystal structure and local stray fields reveals the role of structural inhomogeneity in governing magnetic anisotropy and spin dynamics in MnSb thin film. These results establish MnSb thin films as a promising platform for vector magnetic-field sensing and orientation-encoded spintronic device concepts.

Transition metal tellurides (TMT) form an exciting family of chalcogenides that offer a wide range of functionalities and tunability. Within this class of materials, two-dimensional (2D) TMTs are significantly more chemically stable compared to their analogous chalcogenides, e.g., 2D sulphides and selenides, making them attractive both for fundamental research and applications. This Review attempts to capture recent advances in 2D TMTs. The initial section provides an overview of potential properties offered by these low-dimensional materials. We then discuss recent and some of the most advanced synthesis techniques for producing 2D TMT at a large scale for industrial applications. We highlight how thickness-dependent magnetic modifications, strain-induced property-tuning and temperature impact both fabrication as well as properties of 2D TMTs. Focusing on these tunable physicochemical properties, a range of devices and functionalities are then presented. Properties influenced by long-range ordering such as ferromagnetism and/or superconductivity and propositions for overcoming fundamental and application challenges are discussed. The final section of the article describes advanced device application of these tunable properties.

The generation and manipulation of spin waves at the nanoscale via magnetic vortices are of considerable importance because of their broad applications across magnonic and quantum technologies. Previously, fixed nitrogen-vacancy (NV) centers in diamond have been used to locally characterize vortex dynamics, and scanning NV magnetometry (SNVM) has been used to image vortices' static stray fields. Here, we demonstrate SNVM imaging of both the static and microwave fields generated by vortices in mesoscopic permalloy structures with ∼50 nm spatial resolution, achieving excellent agreement with micromagnetic simulations, while revealing the effects of disorder. We further demonstrate a 40× microwave field enhancement near a vortex core and image the disorder-dependent, spatially varying, evanescent decay of these microwaves. Our ambient, tabletop technique surpasses diffraction-limited techniques' resolutions by at least 5×, with far greater accessibility and throughput than synchrotron radiation-based techniques, offering new opportunities in the study and development of magnonic devices.

Radiofrequency (RF) heating is a new, less invasive alternative to invasive heating methods that use nanoparticles for tumour therapy. But pinpoint local heating is still hard. Molecular interactions form a hybrid structure with unique electrical characteristics that enable RF heating in this work, which explores RF heating in a biological cell (yeast)-2D FeS2 system. Substantial processes have been uncovered via experimental investigations and density functional theory (DFT) computations. At 3 W and 50 MHz, RF heating reaches 54°C in 40 s, which is enough to kill yeast cells, while current-voltage measurements reveal ionic diode-like properties. Interactions between yeast lipid molecules and 2D FeSk, as shown by density-functional theory calculations, cause an imbalance in the distribution of charges and the creation of polar, conductive channels. Insights into biological heating applications based on radio frequency (RF) technology are offered by this work, which lays forth a framework for investigating 2D material-biomolecule interactions.

Miniaturization of electronic components has led to overheating, increased power consumption, and early circuit failures. Conventional heat dissipation methods are becoming inadequate due to limited surface area and higher short‐circuit risks. This study presents a fast, low‐cost, and scalable technique using 2D hexagonal boron nitride (hBN) coatings to enhance heat dissipation in commercial electronics. Inexpensive hBN layers, applied by drop casting or spray coating, boost thermal conductivity at IC surfaces from below 0.3 to 260 W m −1 K −1 , resulting in over double the heat flux and convective heat transfer. This significantly reduces operating temperatures and power consumption, as demonstrated by a 17.4% reduction in a coated audio amplifier circuit board. Density functional theory indicates enhanced interaction between 2D hBN and packaging materials as a key factor. This approach promises substantial energy and cost savings for large‐scale electronics without altering existing manufacturing processes.

This study addresses the complex challenge of identifying process parameters for optimal manufacturing outcomes in advanced manufacturing, where nonlinear and costly process-to-quality relationships prevail. We introduce a novel experimental design framework that energizes the optimization of process parameters and feasibility constraint learning with a significantly reduced number of trials as compared to traditional Design of Experiments methods. Our approach is grounded in two primary methodologies: (1) active multi-criteria sample for constraint estimation and (2) Bayesian optimization-based sample for optimal parameter identification. This integration facilitates the efficient discovery of globally optimal parameter settings and outperforms multiple benchmark models in constraint estimation accuracy. The framework's efficacy is demonstrated through application on both synthetic datasets and a real-world case study involving the synthesis of 2D materials, demonstrating its potential to enhance manufacturing efficiency and quality in complex manufacturing processes significantly.

With rapid advances in qubit technologies, techniques for localizing, modulating, and measuring RF fields and their impact on qubit performance are of the utmost importance. Here, we demonstrate that flux-channeling from a permalloy nanowire can be used to achieve localized spatial modulation of an RF field and that the modulated field can be mapped with high resolution by using the Rabi oscillations of an NV center. Rabi maps reveal ∼100 mm wavelength microwaves concentrated in sub-300 nm regions with up to ∼16× power enhancement. This modulation is robust over a 20 dBm power range and has no adverse impact on NV T2 coherence time. Micromagnetic simulations confirm that the modulated field results from the nanowire's stray field through its constructive/destructive interference with the incident RF field. Our findings provide a new pathway for controlling qubits, amplifying RF signals, and mapping local fields in various on-chip RF technologies.

Miniaturization of electronic components has led to overheating, increasing power consumption and causing early circuit failures. Conventional heat dissipation methods are becoming inadequate due to limited surface area and higher short-circuit risks. This study presents a fast, low-cost, and scalable technique using 2D hexagonal boron nitride (hBN) coatings to enhance heat dissipation in commercial electronics. Inexpensive hBN layers, applied by drop casting or spray coating, boost thermal conductivity at IC surfaces from below 0.3 W/m-K to 260 W/m-K, resulting in over double the heat flux and convective heat transfer. This significantly reduces operating temperatures and power consumption, as demonstrated by a 17.4

2D FeS2 has the potential to convert ambient radiofrequency electromagnetic radiation signals into usable energy, which can be utilized to power portable and wearable electronic devices.

The Materials Genome Initiative (MGI) has streamlined the materials discovery effort by leveraging generic traits of materials, with focus largely on perfect solids. Defects such as impurities and perturbations, however, drive many attractive functional properties of materials. The rich tapestry of charge, spin, and bonding states hosted by defects are not accessible to elements and perfect crystals, and defects can thus be viewed as another class of "elements" that lie beyond the periodic table. Accordingly, a Defect Genome Initiative (DGI) to accelerate functional defect discovery for energy, quantum information, and other applications is proposed. First, major advances made under the MGI are highlighted, followed by a delineation of pathways for accelerating the discovery and design of functional defects under the DGI. Near-term goals for the DGI are suggested. The construction of open defect platforms and design of data-driven functional defects, along with approaches for fabrication and characterization of defects, are discussed. The associated challenges and opportunities are considered and recent advances towards controlled introduction of functional defects at the atomic scale are reviewed. It is hoped this perspective will spur a community-wide interest in undertaking a DGI effort in recognition of the importance of defects in enabling unique functionalities in materials.

A machine learning (ML) guided approach is presented for the accelerated optimization of chemical vapor deposition (CVD) synthesis of 2D materials toward the highest quality, starting from low-quality or unsuccessful synthesis conditions. Using 26 sets of these synthesis conditions as the initial training dataset, our method systematically guides experimental synthesis towards optoelectronic-grade monolayer MoS2 flakes. A-exciton linewidth (sigma(A)) as narrow as 38 meV could be achieved in 2D MoS2 flakes after only an additional 35 trials (reflecting 15% of the full factorial design dataset for training purposes). In practical terms, this reflects a decrease of the possible experimental time to optimize the parameters from up to one year to about two months. This remarkable efficiency was achieved by formulating a constrained sequencing optimization problem solved via a combination of constraint learning and Bayesian Optimization with the narrowness of sigma(A) as the single target metric. By employing graph-based semi-supervised learning with data acquired through a multi-criteria sampling method, the constraint model effectively delineates and refines the feasible design space for monolayer flake production. Additionally, the Gaussian Process regression effectively captures the relationships between synthesis parameters and outcomes, offering high predictive capability along with a measure of prediction uncertainty. This method is scalable to a higher number of synthesis parameters and target metrics and is transferrable to other materials and types of reactors. This study envisions that this method will be fundamental for CVD and similar techniques in the future.

Two-dimensional (2D) material research is rapidly evolving to broaden the spectrum of emergent 2D systems. Here, we review recent advances in the theory, synthesis, characterization, device, and quantum physics of 2D materials and their heterostructures. First, we shed insight into modeling of defects and intercalants, focusing on their formation pathways and strategic functionalities. We also review machine learning for synthesis and sensing applications of 2D materials. In addition, we highlight important development in the synthesis, processing, and characterization of various 2D materials (e.g., MXnenes, magnetic compounds, epitaxial layers, low-symmetry crystals, etc.) and discuss oxidation and strain gradient engineering in 2D materials. Next, we discuss the optical and phonon properties of 2D materials controlled by material inhomogeneity and give examples of multidimensional imaging and biosensing equipped with machine learning analysis based on 2D platforms. We then provide updates on mix-dimensional heterostructures using 2D building blocks for next-generation logic/memory devices and the quantum anomalous Hall devices of high-quality magnetic topological insulators, followed by advances in small twist-angle homojunctions and their exciting quantum transport. Finally, we provide the perspectives and future work on several topics mentioned in this review.

Quantum technologies are poised to move the foundational principles of quantum physics to the forefront of applications. This roadmap identifies some of the key challenges and provides insights on material innovations underlying a range of exciting quantum technology frontiers. Over the past decades, hardware platforms enabling different quantum technologies have reached varying levels of maturity. This has allowed for first proof-of-principle demonstrations of quantum supremacy, for example quantum computers surpassing their classical counterparts, quantum communication with reliable security guaranteed by laws of quantum mechanics, and quantum sensors uniting the advantages of high sensitivity, high spatial resolution, and small footprints. In all cases, however, advancing these technologies to the next level of applications in relevant environments requires further development and innovations in the underlying materials. From a wealth of hardware platforms, we select representative and promising material systems in currently investigated quantum technologies. These include both the inherent quantum bit systems and materials playing supportive or enabling roles, and cover trapped ions, neutral atom arrays, rare earth ion systems, donors in silicon, color centers and defects in wide-band gap materials, two-dimensional materials and superconducting materials for single-photon detectors. Advancing these materials frontiers will require innovations from a diverse community of scientific expertise, and hence this roadmap will be of interest to a broad spectrum of disciplines.

This paper proposes a novel approach for optimizing the manufacturing process under unknown feasibility constraints. Due to the complex interdependencies among the numerous design of experiment parameters, a trial-and-error approach is impractical. Our approach combines a predictive modeling block that uses two machine learning models and an experimental design component employing multiple sampling strategies. We applied this method to the synthesis of 2D material via thermal chemical vapor deposition and achieved optimal material quality within only 7 batches of experiments, amounting to 61 samples. Additionally, we successfully identified the feasible region of synthesis parameters necessary for producing the desired material. These results not only highlight the effectiveness of our method but also its potential to guide engineers towards the most desirable outcome in manufacturing process optimization.

The advancements in 2D materials have opened a plethora of portable, wearable electronic devices. However, their charging methods still confine to plug and charge mode. Considerable efforts have been made in self-powered energy harvesting using piezoelectric, thermoelectric and photovoltaics. However, with the advent of wireless technology, there is a significant demand for wireless-powered devices such as the Internet of Things (IoT) sensors, cell phones and other low-power devices. Hence, radio frequency (RF) energy harvesting can be employed in such scenarios since they can deliver power wirelessly using ambient RF energy. This work demonstrates the synthesis of 2D FeS2 from naturally available earth-abundant pyrite and fabricates a crystal-radio device for RF energy harvesting. The device operated in the commercial FM broadband (88–108 MHz) and the very high frequency (VHF) band up to 170 MHz. A practical demonstration of RF energy harvesting was done by charging a supercapacitor to 1.5V in 20 seconds and illuminating an LED within a range of 1m. Density functional theory (DFT) calculations were performed to support the mechanism of 2D FeS2 for RF applications. The experimental and theoretical studies conclude that 2D FeS2 is a noteworthy material for RF energy-based devices.

N. R. Glavin,* P. M. Ajayan,* S. Kar*

Growing three-dimensional (3D) materials on two-dimensional (2D) van der Waals surface has shown its effectiveness in overcoming materials incompatibility for stacking transferrable membranes toward advanced device manufacturing. Herein, we demonstrate that the nucleation of hexagonal germanium (Ge) grains within a continuous crystalline film, which has been unfeasible through traditional epitaxy techniques, is realized by chemical vapor deposition on top of n-type monolayer molybdenum disulfide (MoS2) substrates. Suggested by quantum molecular dynamics calculation, the hexagonal Ge nucleation is thermodynamically preferable to cubic Ge when growing on monolayer MoS2 with sulfur vacancies. The strained hexagonal Ge grains have been confirmed by transmission electron microscopy analyses from both real space and reciprocal space. Scanning probe microscopy shows that the hexagonal Ge film possesses higher reflectivity in infrared spectral range, implying a higher carrier concentration resulted from the narrower band gap, as compared to cubic Ge.