First-Principles Calculations of the Mechanical Properties of Doped Cu3P Alloys.

In the quest to enhance the mechanical properties of CuP alloys, particularly focusing on the Cu3P phase, this study introduces a comprehensive investigation into the effects of various alloying elements on the alloy's performance. In this paper, the first principle of density universal function theory and the projection-enhanced wave method under VASP 5.4.4 software are used to recalculate the lattice constants, evaluate the lattice stability, and explore the mechanical properties of selected doped elements such as In, Si, V, Al, Bi, Nb, Sc, Ta, Ti, Y and Zr, including shear, stiffness, compression, and plasticity. The investigation reveals that strategic doping with In and Si significantly enhances shear resistance and stiffness, while V addition notably augments compressive resistance. Furthermore, incorporating Al, Bi, Nb, Sc, Ta, Ti, V, Y, and Zr has substantially improved plasticity, indicating a broad spectrum of mechanical enhancement through precise alloying. Crucially, the validation of our computational models is demonstrated through hardness experiments on Si and Sn-doped specimens, corroborating the theoretical predictions. Additionally, a meticulous analysis of the states' density further confirms our computational approach's accuracy and reliability. This study highlights the potential of targeted alloying to tailor the mechanical properties of Cu3P alloys and establishes a robust theoretical framework for predicting the effects of doping in metallic alloys. The findings presented herein offer valuable insights and a novel perspective on material design and optimization, marking a significant stride toward developing advanced materials with customized mechanical properties.

Performance and mechanism of graphene oxide removal from aqueous solutions by calcite: adsorption isotherms, thermodynamics, and kinetics.

The flow of graphene oxide (GO) into natural water systems can adversely affect water environments and ecosystems. In this study, the adsorption effect of calcite on GO under different conditions was studied using calcite as adsorbent. Meanwhile, characterized by a combination of microscopic experiments, including SEM, TEM, XRD, FTIR, Raman, XPS, and AFM, additional research on the performance and the mechanism of GO sorption by calcite was conducted. The findings indicated that the highest adsorption efficiency was observed at a temperature of 303 K, pH 3, a mass of 90 mg of calcite, with an initial concentration of 60 mg L-1 GO, resulting in a 95% adsorption rate. The adsorption isotherm conformed to the model of Langmuir and Temkin, and it is a heat absorption process dominated by monolayer adsorption. The thermodynamic analysis showed that the adsorption was spontaneous and heat-absorbing. The adsorption kinetics conformed to the pseudo-second-order kinetic model, and the sorption procedure is chemisorption. In conclusion, calcite has a good sorption capacity for GO, which can provide a reference for the removal of GO in the aqueous environment.

Enhancing Wettability of Cu3P/Cu Systems through Doping with Si, Sn, and Zr Elements: Insights from First Principles Analysis.

Explaining the wetting mechanism of Cu-P brazing materials and Cu remains challenging. This fundamental research aims to reveal the wettability mechanism of Si, Sn, and Zr doping on the interfacial bond strength of the Cu3P/Cu system through the first principles study. We carried out several sets of calculations to test the validity of the result; included in the work are those used to establish the interfacial structure and to analyze the effect of doping on the wettability. Specific analysis was carried out in terms of three aspects: the work of adhesion (Wad), the charge density difference, and the density of states (DOS). The calculated results show that doping with Si, Sn, and Zr elements can effectively improve the wettability within the CuP/Cu interface with very high accuracy, and is particularly effective when doped with Zr. These results provide an insightful theoretical guide for enhancing the CuP/Cu system's wettability by adding active elements.

Sensory neuron-expressed TRPC3 mediates acute and chronic itch.

ABSTRACT: Chronic pruritus is a prominent symptom of allergic contact dermatitis (ACD) and represents a huge unmet health problem. However, its underlying cellular and molecular mechanisms remain largely unexplored. TRPC3 is highly expressed in primary sensory neurons and has been implicated in peripheral sensitization induced by proinflammatory mediators. Yet, the role of TRPC3 in acute and chronic itch is still not well defined. Here, we show that, among mouse trigeminal ganglion (TG) neurons, Trpc3 mRNA is predominantly expressed in nonpeptidergic small diameter TG neurons of mice. Moreover, Trpc3 mRNA signal was present in most presumptively itch sensing neurons. TRPC3 agonism induced TG neuronal activation and acute nonhistaminergic itch-like and pain-like behaviors in naive mice. In addition, genetic deletion of Trpc3 attenuated acute itch evoked by certain common nonhistaminergic pruritogens, including endothelin-1 and SLIGRL-NH2. In a murine model of contact hypersensitivity (CHS), the Trpc3 mRNA expression level and function were upregulated in the TG after CHS. Pharmacological inhibition and global knockout of Trpc3 significantly alleviated spontaneous scratching behaviors without affecting concurrent cutaneous inflammation in the CHS model. Furthermore, conditional deletion of Trpc3 in primary sensory neurons but not in keratinocytes produced similar antipruritic effects in this model. These findings suggest that TRPC3 expressed in primary sensory neurons may contribute to acute and chronic itch through a histamine independent mechanism and that targeting neuronal TRPC3 might benefit the treatment of chronic itch associated with ACD and other inflammatory skin disorders.

Remote Oxygen Scavenging of the Interfacial Oxide Layer in Ferroelectric Hafnium-Zirconium Oxide-Based Metal-Oxide-Semiconductor Structures.

Discovery of ferroelectricity in HfO2 has sparked a lot of interest in its use in memory and logic due to its CMOS compatibility and scalability. Devices that use ferroelectric HfO2 are being investigated; for example, the ferroelectric field-effect transistor (FEFET) is one of the leading candidates for next generation memory technology, due to its area, energy efficiency and fast operation. In an FEFET, a ferroelectric layer is deposited on Si, with an SiO2 layer of ∼1 nm thickness inevitably forming at the interface. This interfacial layer (IL) increases the gate voltage required to switch the polarization and write into the memory device, thereby increasing the energy required to operate FEFETs, and makes the technology incompatible with logic circuits. In this work, it is shown that a Pt/Ti/thin TiN gate electrode in a ferroelectric Hf0.5Zr0.5O2 based metal-oxide-semiconductor (MOS) structure can remotely scavenge oxygen from the IL, thinning it down to ∼0.5 nm. This IL reduction significantly reduces the ferroelectric polarization switching voltage with a ∼2× concomitant increase in the remnant polarization and a ∼3× increase in the abruptness of polarization switching consistent with density functional theory (DFT) calculations modeling the role of the IL layer in the gate stack electrostatics. The large increase in remnant polarization and abruptness of polarization switching are consistent with the oxygen diffusion in the scavenging process reducing oxygen vacancies in the HZO layer, thereby depinning the polarization of some of the HZO grains.

Local Epitaxial Templating Effects in Ferroelectric and Antiferroelectric ZrO2.

Nanoscale polycrystalline thin-film heterostructures are central to microelectronics, for example, metals used as interconnects and high-K oxides used in dynamic random-access memories (DRAMs). The polycrystalline microstructure and overall functional response therein are often dominated by the underlying substrate or layer, which, however, is poorly understood due to the difficulty of characterizing microstructural correlations at a statistically meaningful scale. Here, an automated, high-throughput method, based on the nanobeam electron diffraction technique, is introduced to investigate orientational relations and correlations between crystallinity of materials in polycrystalline heterostructures over a length scale of microns, containing several hundred individual grains. This technique is employed to perform an atomic-scale investigation of the prevalent near-coincident site epitaxy in nanocrystalline ZrO2 heterostructures, the workhorse system in DRAM technology. The power of this analysis is demonstrated by answering a puzzling question: why does polycrystalline ZrO2 transform dramatically from being antiferroelectric on polycrystalline TiN/Si to ferroelectric on amorphous SiO2/Si?

Antiferroelectric negative capacitance from a structural phase transition in zirconia.

Crystalline materials with broken inversion symmetry can exhibit a spontaneous electric polarization, which originates from a microscopic electric dipole moment. Long-range polar or anti-polar order of such permanent dipoles gives rise to ferroelectricity or antiferroelectricity, respectively. However, the recently discovered antiferroelectrics of fluorite structure (HfO2 and ZrO2) are different: A non-polar phase transforms into a polar phase by spontaneous inversion symmetry breaking upon the application of an electric field. Here, we show that this structural transition in antiferroelectric ZrO2 gives rise to a negative capacitance, which is promising for overcoming the fundamental limits of energy efficiency in electronics. Our findings provide insight into the thermodynamically forbidden region of the antiferroelectric transition in ZrO2 and extend the concept of negative capacitance beyond ferroelectricity. This shows that negative capacitance is a more general phenomenon than previously thought and can be expected in a much broader range of materials exhibiting structural phase transitions.

18F-FDG PET/CT helps rule out malignancy in lipomatous hypertrophy of the interatrial septum with atypical MRI manifestations, to avoid unnecessary surgical treatment.

Lipomatous hypertrophy of the interatrial septum (LHIS) is a rare benign heart disease characterized by excessive deposition of adipose tissue in the atrial septum with sparing fossa ovalis, which demonstrates a characteristic hourglass/dumbbell configuration. We reported a case of LHIS with inhomogenous characteristic on CMR and persistently no FDG uptake on 18F-FDG PET-CT, which is contrary to a few previous cases. This single case report suggests that in case LHIS present in-homogenous characteristic on CMR, metabolic PET imaging could be used as a complementary imaging model to decrease the concern of lipomatous neoplasms, thereby avoid unnecessary surgical therapy.

NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark.

Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with options of various mainstream and emerging memory technologies, architectures, and networks can be a great convenience for fast early-stage design space exploration of CIM hardware accelerators. DNN+NeuroSim is an integrated benchmark framework supporting flexible and hierarchical CIM array design options from a device level, to a circuit level and up to an algorithm level. In this study, we validate and calibrate the prediction of NeuroSim against a 40-nm RRAM-based CIM macro post-layout simulations. First, the parameters of a memory device and CMOS transistor are extracted from the foundry's process design kit (PDK) and employed in the NeuroSim settings; the peripheral modules and operating dataflow are also configured to be the same as the actual chip implementation. Next, the area, critical path, and energy consumption values from the SPICE simulations at the module level are compared with those from NeuroSim. Some adjustment factors are introduced to account for transistor sizing and wiring area in the layout, gate switching activity, post-layout performance drop, etc. We show that the prediction from NeuroSim is precise with chip-level error under 1% after the calibration. Finally, the system-level performance benchmark is conducted with various device technologies and compared with the results before the validation. The general conclusions stay the same after the validation, but the performance degrades slightly due to the post-layout calibration.

Extraction of Preisach model parameters for fluorite-structure ferroelectrics and antiferroelectrics.

Flourite-structure ferroelectrics (FEs) and antiferroelectrics (AFEs) such as HfO2 and its variants have gained copious attention from the semiconductor community, because they enable complementary metal-oxide-semiconductor (CMOS)-compatible platforms for high-density, high-performance non-volatile and volatile memory technologies. While many individual experiments have been conducted to characterize and understand fluorite-structure FEs and AFEs, there has been little effort to aggregate the information needed to benchmark and provide insights into their properties. We present a fast and robust modeling framework that automatically fits the Preisach model to the experimental polarization ([Formula: see text]) versus electric field ([Formula: see text]) hysteresis characterizations of fluorite-structure FEs. The modifications to the original Preisach model allow the double hysteresis loops in fluorite-structure antiferroelectrics to be captured as well. By fitting the measured data reported in the literature, we observe that ferroelectric polarization and dielectric constant decrease as the coercive field rises in general.

Direct comparison of ferroelectric properties in Hf0.5Zr0.5O2 between thermal and plasma-enhanced atomic layer deposition.

Since the discovery of ferroelectricity in doped/alloyed HfO2 and ZrO2 thin film, many device engineers have been attracted to its sustainable ferroelectricity at the thickness of a few nanometer. While most of the previous studies have mainly focused on the ferroelectric properties of the thermally atomic layer deposited (THALD) Hf0.5Zr0.5O2 (HZO), the plasma-enhanced ALD (PEALD) HZO has not received much attention. In this work, a direct comparison between the two types of HZO thin films is carried out, where we found that a tradeoff exists between these two fabrication methods. While the THALD HZO was able to maintain a higher cycling endurance, the PEALD HZO showed more stable characteristics over the cycling with reduced wake-up and fatigue effects, in addition to better tolerance against breakdown under high electric field. Furthermore, the PEALD HZO could be crystallized with post deposition annealing at 350 °C, which is of great interest for the back-end-of-line compatibility with silicon fabrication processes.

Optoelectronic resistive random access memory for neuromorphic vision sensors.

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.

Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.

Neuromorphic engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems. The brain has evolved over billions of years to solve difficult engineering problems by using efficient, parallel, low-power computation. The goal of NE is to design systems capable of brain-like computation. Numerous large-scale neuromorphic projects have emerged recently. This interdisciplinary field was listed among the top 10 technology breakthroughs of 2014 by the MIT Technology Review and among the top 10 emerging technologies of 2015 by the World Economic Forum. NE has two-way goals: one, a scientific goal to understand the computational properties of biological neural systems by using models implemented in integrated circuits (ICs); second, an engineering goal to exploit the known properties of biological systems to design and implement efficient devices for engineering applications. Building hardware neural emulators can be extremely useful for simulating large-scale neural models to explain how intelligent behavior arises in the brain. The principal advantages of neuromorphic emulators are that they are highly energy efficient, parallel and distributed, and require a small silicon area. Thus, compared to conventional CPUs, these neuromorphic emulators are beneficial in many engineering applications such as for the porting of deep learning algorithms for various recognitions tasks. In this review article, we describe some of the most significant neuromorphic spiking emulators, compare the different architectures and approaches used by them, illustrate their advantages and drawbacks, and highlight the capabilities that each can deliver to neural modelers. This article focuses on the discussion of large-scale emulators and is a continuation of a previous review of various neural and synapse circuits (Indiveri et al., 2011). We also explore applications where these emulators have been used and discuss some of their promising future applications.

Reduced Graphene Oxide-Anchored Manganese Hexacyanoferrate with Low Interstitial H2O for Superior Sodium-Ion Batteries.

Low-cost manganese hexacyanoferrate (NMHCF) possesses many favorable advantages including high theoretical capacity, ease of preparation, and robust open channels that enable faster Na+ diffusion kinetics. However, high lattice water and low electronic conductivity are the main bottlenecks to their pragmatic realization. Here, we present a strategy by anchoring NMHCF on reduced graphene oxide (RGO) to alleviate these problems, featuring a specific discharge capacity of 161/121 mA h g-1 at a current density of 20/200 mA g-1. Moreover, the sodiation process is well revealed by ex situ X-ray diffraction, EIS and Car-Parrinello molecular dynamics simulations. At a rate of 20 mA g-1, the hard carbon//NMHCF/RGO full cell affords a stable discharge capacity of 84 mA h g-1 (based on the weights of cathode mass) over 50 cycles, thus highlighting NMHCF/RGO an alternative cathode for sodium-ion batteries.

SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations.

Although several types of architecture combining memory cells and transistors have been used to demonstrate artificial synaptic arrays, they usually present limited scalability and high power consumption. Transistor-free analog switching devices may overcome these limitations, yet the typical switching process they rely on-formation of filaments in an amorphous medium-is not easily controlled and hence hampers the spatial and temporal reproducibility of the performance. Here, we demonstrate analog resistive switching devices that possess desired characteristics for neuromorphic computing networks with minimal performance variations using a single-crystalline SiGe layer epitaxially grown on Si as a switching medium. Such epitaxial random access memories utilize threading dislocations in SiGe to confine metal filaments in a defined, one-dimensional channel. This confinement results in drastically enhanced switching uniformity and long retention/high endurance with a high analog on/off ratio. Simulations using the MNIST handwritten recognition data set prove that epitaxial random access memories can operate with an online learning accuracy of 95.1%.

N-doped carbon dots from phenol derivatives for excellent colour rendering WLEDs.

To achieve competitive fluorescence carbon dots (CDs), studies on regulating fluorescence of CDs under controlled, comparable conditions are in great demand. Herein, by changing the functional groups and nitrogenous existence forms in the precursors, three efficient yellow-green emissive N-doped CDs which have the same fluorescence peak wavelength but different photoluminescence quantum yields were realized through a facile hydrothermal method. The as-prepared CDs exhibit not only excited-independent emissions but also similar surface states. The best-performing CDs among the three products exhibits photoluminescence quantum yields of up to 24.4% in water and 53.3% in ethanol, abundant surface functional groups and its high N-doping degree would be the reason for its excellent performances. By washing and reduction processes, the emission evolution of the CDs was studied linking the changes of surface states. The fluorescence can certainly be attributed to the surface of the carbon dots, and the surface states control the photoluminescence features. Serving as a yellow-green colour conversion layer, the best CDs in the three products was used to fabricate a white light-emitting diode. The white light-emitting diode shows an excellent colour rendering index up to 93.3, suggesting broad application prospects of the CDs in lighting and display fields.

Three-dimensional architecture hybrid perovskite solar cells using CdS nanorod arrays as an electron transport layer.

Three-dimensional (3D) architecture perovskite solar cells (PSCs) using CdS nanorod (NR) arrays as an electron transport layer were designed and prepared layer-by-layer via a physical-chemical vapor deposition (P-CVD) process. The CdS NRs not only provided a scaffold to the perovskite film, but also increased the interfacial contact between the perovskite film and electron transport layer. As an optimized result, a high power conversion efficiency of 12.46% with a short-circuit current density of 19.88 mA cm-2, an open-circuit voltage of 1.01 V and a fill factor of 62.06% was obtained after 12 h growth of CdS NRs. It was four times the efficiency of contrast planar structure with a similar thickness. The P-CVD method assisted in achieving flat and voidless CH3NH3PbI3-x Cl x perovskite film and binding the CdS NRs and perovskite film together. The different density of CdS NRs had obvious effects on light transmittance of 350-550 nm, the interfacial area and the difficulty of combining layers. Moreover, the efficient 1D transport paths for electrons and multiple absorption of light, which are generated in 3D architecture, were beneficial to realize a decent power conversion efficiency.

Corrigendum: Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.

[This corrects the article DOI: 10.3389/fnins.2018.00891.].

Disturbance characteristics of half-selected cells in a cross-point resistive switching memory array.

Disturbance characteristics of cross-point resistive random access memory (RRAM) arrays are comprehensively studied in this paper. An analytical model is developed to quantify the number of pulses (#Pulse) the cell can bear before disturbance occurs under various sub-switching voltage stresses based on physical understanding. An evaluation methodology is proposed to assess the disturb behavior of half-selected (HS) cells in cross-point RRAM arrays by combining the analytical model and SPICE simulation. The characteristics of cross-point RRAM arrays such as energy consumption, reliable operating cycles and total error bits are evaluated by the methodology. A possible solution to mitigate disturbance is proposed.