Publications by authors named "Jiayang Hu"

Emerging neuromorphic hardware promises energy-efficient computing by colocating multiple essential functions at the individual component level. The implementation is challenging due to mismatch between the characteristics of multifunctional devices and neural networks. Here, we demonstrate an artificial synapse based on a 2D α-phase indium selenide that exhibits integrated perception-and-computing-in-memory functions in a single-transistor setup, serving as a basic building block for reservoir computing.

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Article Synopsis
  • Biological neurons process information in complex ways, outperforming traditional models in neuromorphic computing, especially in Boolean algebra operations.
  • A single-transistor neuron utilizing graphene's properties can execute multiple Boolean operations efficiently, unlike conventional circuits that need many transistors for certain tasks.
  • This research lays the groundwork for advanced computations at the transistor level, aiming for more scalable and efficient neural networks that mimic brain functions.
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Microbial communities are closely related to the overall health and quality of soil, but studies on microbial ecology in apple pear orchard soils are limited. In the current study, 28 soil samples were collected from three apple pear orchards, and the composition and structure of fungal and bacterial communities were investigated by high-throughput sequencing. The molecular ecological network showed that the keystone taxa of bacterial communities were , , , , , and , and the keystone taxon of fungal communities was .

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The Boltzmann Tyranny, set by thermionic statistics, dictates the lower limit of switching slope (SS) of a MOSFET to be 60 mV/dec, the fundamental barrier for low-dissipative electronics. The large SS leads to nonscalable voltage, significant leakage, and power consumption, particularly at short channels, making transistor scaling an intimidating challenge. In recent decades, an array of steep-slope transistors has been proposed; none is close to an ideal switch with ultimately abrupt switching (SS ∼ 0 mV/dec) between the binary logic states.

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Article Synopsis
  • - Reconfigurable neuromorphic computing aims to enhance energy-efficient neural networks and offers versatility by allowing devices to perform multiple functions, not just specific neural tasks.
  • - The proposed device uses an all 2D material-based heterostructure that can emulate key components of neural function (synapses, neurons, dendrites) by modifying output terminals in response to stimuli.
  • - As a proof of concept, the device has been shown to execute basic Boolean logic functions, indicating its potential for solving complex problems in neural networks and paving the way for low-power neuromorphic hardware.
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Background: Inflammatory myofibroblastic tumors (IMTs) are characterized by myofibroblast proliferation and an inflammatory cell infiltrate. Our previous study on IMTs reveals that disrupt NMD pathway causes to lower the threshold for triggering the immune cell infiltration, thereby resulting in inappropriate immune activation. However, myofibroblast differentiation and proliferation is not yet known.

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The recently unfolded ferroionic phenomena in 2D van der Waals (vdW) copper-indium-thiophosphate (CuInP S or CIPS) have received widespread interest as they allow for dynamic control of conductive switching properties, which are appealing in the paradigm-shift computing. The intricate couplings between ferroelectric polarization and ionic conduction in 2D vdW CIPS facilitate the manipulation and dynamic control of conductive behaviors. However, the complex interplays and underlying mechanisms are not yet fully explored and understood.

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Two-dimensional (2D) materials with the atomically thin thickness have attracted great interest in the post-Moore's Law era because of their tremendous potential to continue transistor downscaling and offered advances in device performance at the atomic limit. However, the metal-semiconductor contact is the bottleneck in field-effect transistors (FETs) integrating 2D semiconductors as channel materials. A robust and tunable doping method at the source and drain region of 2D transistors to minimize the contact resistance is highly sought after.

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Brain-inspired neuromorphic computing systems with the potential to drive the next wave of artificial intelligence demand a spectrum of critical components beyond simple characteristics. An emerging research trend is to achieve advanced functions with ultracompact neuromorphic devices. In this work, a single-transistor neuron is demonstrated that implements excitatory-inhibitory (E-I) spatiotemporal integration and a series of essential neuron behaviors.

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Brain-inspired intelligent systems demand diverse neuromorphic devices beyond simple functionalities. Merging biomimetic sensing with weight-updating capabilities in artificial synaptic devices represents one of the key research focuses. Here, we report a multiresponsive synapse device that integrates synaptic and optical-sensing functions.

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Background: Pancreatic ductal adenocarcinomas (PDACs) is a malignant disorder and is the most common pancreatic cancer type. The malignant cells depend on the uptake of asparagine (Asn) for growth. The synthesis of Asn occurs through the enzyme asparagine synthetase (ASNS).

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Chemical vapor deposition (CVD)-grown flakes of high-quality monolayers of WS can be stabilized at elevated temperatures by encapsulation with several layer hexagonal boron nitride (BN), but to different degrees in the presence of ambient air, flowing N, and flowing forming gas (95% N, 5% H). The best passivation of WS at elevated temperature occurs for -BN-covered samples with flowing N (after heating to 873 K), as judged by optical microscopy and photoluminescence (PL) intensity after a heating/cooling cycle. Stability is worse for uncovered samples, but best with flowing forming gas.

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One standard way of forming monolayers (MLs) of nanoparticles (NPs) is to drop-cast a NP dispersion made using one solvent onto a second, immiscible solvent; after this upper solvent evaporates, the NP ML can be transferred to a solid substrate by liftoff. We show that this previously universal use of only immiscible solvent pairs can be relaxed and close-packed, hexagonally ordered NP monolayers can self-assemble at liquid-air interfaces when some miscible solvent pairs are used instead. We demonstrate this by drop-casting an iron oxide NP dispersion in toluene on a dimethyl sulfoxide (DMSO) liquid substrate.

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