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We present a novel heterostructured approach to disentangle the mechanism of electrical transport of the strongly correlated PrNiO3, by placing the nickelate under the photoconductor CdS. This enables the injection of carriers into PrNiO3 in a controlled way, which can be used to interrogate its intrinsic transport mechanism. We find a nonvolatile resistance decrease when illuminating the system at temperatures below the PrNiO3 metal-insulator transition. The photoinduced change becomes more volatile as the temperature increases. These data help understand the intrinsic transport properties of the nickelate-CdS bilayer. Together with data from a bare PrNiO3 film, we find that the transport mechanism includes a combination of mechanisms, including both thermal activation and variable range hopping. At low temperatures without photoinduced carriers, the transport is governed by hopping, while at higher temperatures and intense illumination the activation mechanism becomes relevant. This work shows a new way to control optically control the low-temperature resistance of PrNiO3. 

In-memory computing with emerging non-volatile memory devices (eNVMs) has shown promising results in accelerating matrix-vector multiplications. However, activation function calculations are still being implemented with general processors or large and complex neuron peripheral circuits. Here, we present the integration of Ag-based conductive bridge random access memory (Ag-CBRAM) crossbar arrays with Mott rectified linear unit (ReLU) activation neurons for scalable, energy and area-efficient hardware (HW) implementation of deep neural networks. We develop Ag-CBRAM devices that can achieve a high ON/OFF ratio and multi-level programmability. Compact and energy-efficient Mott ReLU neuron devices implementing ReLU activation function are directly connected to the columns of Ag-CBRAM crossbars to compute the output from the weighted sum current. We implement convolution filters and activations for VGG-16 using our integrated HW and demonstrate the successful generation of feature maps for CIFAR-10 images in HW. Our approach paves a new way toward building a highly compact and energy-efficient eNVMs-based in-memory computing system.

 

Fast and sensitive phase transition detection is one of the most important requirements for new material synthesis and characterization. For solid-state samples, microwave absorption techniques can be employed for detecting phase transitions because it simultaneously monitors changes in electronic and magnetic properties. However, microwave absorption techniques require expensive high-frequency microwave equipment and bulky hollow cavities. Due to size limitations in conventional instruments, it is challenging to implement these cavities inside a laboratory cryostat. In this work, we designed and built a susceptometer that consists of a small helical cavity embedded into a custom insert of a commercial cryostat. This cavity resonator operated at sub-GHz frequencies is extremely sensitive to changes in material parameters, such as electrical conductivity, magnetization, and electric and magnetic susceptibilities. To demonstrate its operation, we detected superconducting phase transition in Nb and YBa2Cu3O7−δ, metal–insulator transitions in V2O3, ferromagnetic transition in Gd, and magnetic field induced transformation in meta magnetic NiCoMnIn single crystals. This high sensitivity apparatus allows the detection of trace amounts of materials (10−9-cc) undergoing an electromagnetic transition in a very broad temperature (2–400 K) and magnetic field (up to 90 kOe) ranges. 

Recently, evidence for a conducting surface state (CSS) below 19 K was reported for the correlatedd-electron small gap semiconductor FeSi. In the work reported herein, the CSS and the bulk phase of FeSi were probed via electrical resistivity ρ measurements as a function of temperatureT, magnetic fieldBto 60 T, and pressurePto 7.6 GPa, and by means of a magnetic field-modulated microwave spectroscopy (MFMMS) technique. The properties of FeSi were also compared with those of the Kondo insulator SmB₆to address the question of whether FeSi is ad-electron analogue of anf-electron Kondo insulator and, in addition, a “topological Kondo insulator” (TKI). The overall behavior of the magnetoresistance of FeSi at temperatures above and below the onset temperatureT_S= 19 K of the CSS is similar to that of SmB₆. The two energy gaps, inferred from the ρ(T) data in the semiconducting regime, increase with pressure up to about 7 GPa, followed by a drop which coincides with a sharp suppression ofT_S. Several studies of ρ(T) under pressure on SmB₆reveal behavior similar to that of FeSi in which the two energy gaps vanish at a critical pressure near the pressure at whichT_Svanishes, although the energy gaps in SmB₆initially decrease with pressure, whereas in FeSi they increase with pressure. The MFMMS measurements showed a sharp feature atT_S≈ 19 K for FeSi, which could be due to ferromagnetic ordering of the CSS. However, no such feature was observed atT_S≈ 4.5 K for SmB₆.

 

The low temperature monoclinic, insulating phase of vanadium dioxide is ordinarily considered nonmagnetic, with dimerized vanadium atoms forming spin singlets, though paramagnetic response is seen at low temperatures. We find a nonlocal spin Seebeck signal in VO2 films that appears below 30 K and that increases with a decrease in temperature. The spin Seebeck response has a nonhysteretic dependence on the in-plane external magnetic field. This paramagnetic spin Seebeck response is discussed in terms of prior findings on paramagnetic spin Seebeck effects and expected magnetic excitations of the monoclinic ground state.

 

Synchronization of electrical oscillators is a crucial step toward practical implementation of oscillator-based and bio-inspired computing. Here, we report the emergence of an unusual stochastic pattern in coupled spiking Mott nanodevices. Although a moderate capacitive coupling results in a deterministic alternating spiking, increasing the coupling strength leads counterintuitively to stochastic disruptions of the alternating spiking sequence. The disruptions of the deterministic spiking sequence are a direct consequence of the small intrinsic stochasticity in electrical triggering of the insulator–metal transition. Although the stochasticity is subtle in individual nanodevices, it becomes dramatically enhanced just in a single pair of coupled oscillators and, thus, dominates the synchronization. This is different from the stochasticity and multimodal coupling, appearing due to collective effects in large oscillator networks. The stochastic spiking pattern in Mott nanodevices results in a discrete inter-spike interval distribution resembling those in biological neurons. Our results advance the understanding of the emergent synchronization properties in spiking oscillators and provide a platform for hardware-level implementation of probabilistic computing and biologically plausible electronic devices.