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Recent breakthroughs in brain-inspired computing promise to address a wide range of problems from security to healthcare. However, the current strategy of implementing artificial intelligence algorithms using conventional silicon hardware is leading to unsustainable energy consumption. Neuromorphic hardware based on electronic devices mimicking biological systems is emerging as a low-energy alternative, although further progress requires materials that can mimic biological function while maintaining scalability and speed. As a result of their diverse unique properties, atomically thin two-dimensional (2D) materials are promising building blocks for next-generation electronics including nonvolatile memory, in-memory and neuromorphic computing, and flexible edge-computing systems. Furthermore, 2D materials achieve biorealistic synaptic and neuronal responses that extend beyond conventional logic and memory systems. Here, we provide a comprehensive review of the growth, fabrication, and integration of 2D materials and van der Waals heterojunctions for neuromorphic electronic and optoelectronic devices, circuits, and systems. For each case, the relationship between physical properties and device responses is emphasized followed by a critical comparison of technologies for different applications. We conclude with a forward-looking perspective on the key remaining challenges and opportunities for neuromorphic applications that leverage the fundamental properties of 2D materials and heterojunctions. 

We discuss how a dual-gated memtransistor crossbar can accelerate the extraction of the Transformer’s attention scores. A memtransistor is a novel two-dimensional material-based device that offers non-volatile programmability and gate tunability. Leveraging these attributes, we demonstrate the extraction of quadratic-order products on a single memtransistor and the single-step extraction of attention scores without inferring intermediate query/key vectors. The query/key-free processing of memtransistor-based attention scoring results in 2.37× lower energy with less than half crossbar cells. 

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of aRhizosoleniasp. bloom, the initiation and complete bloom cycle ofChaetoceros socialis(8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms. 

The growth of layered 2D compounds is a key ingredient in finding new phenomena in quantum materials, optoelectronics, and energy conversion. Here, we report SnP₂Se₆, a van der Waals chiral (R3 space group) semiconductor with an indirect bandgap of 1.36 to 1.41 electron volts. Exfoliated SnP₂Se₆flakes are integrated into high-performance field-effect transistors with electron mobilities >100 cm²/Vs and on/off ratios >10⁶at room temperature. Upon excitation at a wavelength of 515.6 nanometer, SnP₂Se₆phototransistors show high gain (>4 × 10⁴) at low intensity (≈10⁻⁶W/cm²) and fast photoresponse (< 5 microsecond) with concurrent gain of ≈52.9 at high intensity (≈56.6 mW/cm²) at a gate voltage of 60 V across 300-nm-thick SiO₂dielectric layer. The combination of high carrier mobility and the non-centrosymmetric crystal structure results in a strong intrinsic bulk photovoltaic effect; under local excitation at normal incidence at 532 nm, short circuit currents exceed 8 mA/cm²at 20.6 W/cm². 

Abstract Previous observational studies have shown that the intensification rate (IR) of a tropical cyclone (TC) is often correlated with its real-time size. However, no any size parameter explicitly appears in the recent time-dependent theory of TC intensification, while the theory can still well capture the intensity evolution of simulated TCs. This study provides a detailed analysis to address how TC real-time size affects its intensification and why no size parameter explicitly appears in the theory based on the results from axisymmetric numerical simulations. The results show that the overall correlation between the TC IR and real-time size as reported in previous observational studies, in terms of both the radius of maximum wind (RMW) and the radius of 17 m s⁻¹wind (R17), is largely related to the correlation between the IR and intensity because the size and intensity are highly interrelated. As a result, the correlation between the TC IR and size for a given intensity is rather weak. Diagnostic analysis shows that the TC real-time size (RMW and R17) has two opposing effects on intensification. A larger TC size tends to result in a higher steady-state intensity but reduce the conversion efficiency of thermodynamic energy to inner-core kinetic energy or the degree of moist neutrality of the eyewall ascent for a given intensity. The former is favorable, while the latter is unfavorable for intensification. The two effects are implicitly included in the theory and largely offset, resulting in the weak dependence of the IR on TC size for a given intensity. 

ABSTRACT We present six whole community shotgun metagenomic sequencing data sets of two types of biological soil crusts sampled at the ecotone of the Mojave Desert and Colorado Desert in California. These data will help us understand the diversity and function of biocrust microbial communities, which are essential for desert ecosystems. 

The Diels–Alder (DA) reaction, a classic cycloaddition reaction involving a diene and a dienophile to form a cyclohexene, is among the most versatile organic reactions. Theories have predicted thermodynamically unfavorable DA reactions on pristine graphene owing to its low chemical reactivity. We hypothesized that metals like Ni could enhance the reactivity of graphene towards DA reactions through charge transfer. The results indeed showed that metal substrates enhanced the reactivity of graphene in the DA reactions with a diene, 2,3-dimethoxy butadiene (DMBD), and a dienophile, maleic anhydride (MAH), with the activity enhancement in the order of Ni > Cu, and both are more reactive than graphene supported on silicon wafer. The rate constants were estimated to be two times higher for graphene supported on Ni than on silicon wafer. The computational results support the experimentally obtained rate trend of Ni > Cu, both predicted to be greater than unsupported graphene, which is explained by the enhanced graphene–substrate interaction reflected in charge transfer effects with the strongly interacting Ni. This study opens up a new avenue for enhancing the chemical reactivity of pristine graphene through substrate selection. 

This paper reports the fabrication and mechanical properties of macroscale graphene fibers (diameters of 10 to 100 μm with lengths upwards of 2 cm) prepared from a single sheet of single-layer graphene grown via chemical vapor deposition (CVD). The breaking strength of these graphene fibers increased with consecutive tensile test measurements on a single fiber, where fiber fragments produced from a prior test exhibited larger breaking strengths. Additionally, we observed an overall reduction of surface folds and wrinkles, and an increase in their alignment parallel to the tensile direction. We propose that a foundation of this property is the plastic deformations within the fiber that accumulate through sequential tensile testing. Through this cyclic method, our best fiber produced a strength of 2.67 GPa with a 1 mm gauge length.