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Recent reports reveal that isothermal chemical doping of hydrogen in correlated complex oxides such as perovskite nickelates (e.g. NdNiO3) can induce a metal-to-insulator transition (MIT) without the need for temperature modulation. In this work, we interrogate the magnitude change in temperature dependence of thermal conductivity upon chemical doping of hydrogen, as any changes to the thermal properties upon doping offer a route to solid-state thermal switches as well as another potential signal to monitor in a diverse set of sensing, electronic, and optical applications. Using frequency-domain thermoreflectance, we demonstrate that a large concentration of hydrogen (~ 0.1 - 0.5 H/unit cell) completely suppresses the electronic contribution to thermal conductivity in NdNiO3 thin films and reduces the phononic contribution by a factor of 2. These results are critical for the design of next-generation solid-state thermal switches, sensors, extreme environment electronics and neuromorphic memory architectures., Comment: preprint

Electrically driven insulator-metal transitions in prototypical quantum materials such as VO2 offer a foundational platform for designing novel solid-state devices. Tuning the V: O stoichiometry offers a vast electronic phase space with non-trivial collective properties. Here, we report the discovery of discrete threshold switching voltages with constant threshold voltage difference between cycles in vanadium oxide crystals. The observed threshold fields over 10000 cycles are ~100X lower than that noted for stoichiometric VO2 and show unique discrete behaviour. We correlate the observed discrete memristor behaviour with the valence change mechanism and fluctuations in the chemical composition of spatially distributed VO2-VnO2n-1 complex oxide phases. Design of chemical heterogeneity in Mott insulators, therefore, offers an intriguing path to realizing low-energy neuromorphic devices., Comment: 21 pages, 4 figures

RF radiation spectrum is central to wireless and radar systems among numerous high-frequency device technologies. Here, we demonstrate sensing of RF signals in the technologically relevant 2.4 GHz range utilizing vanadium dioxide (VO2), a quantum material that has garnered significant interest for its insulator-to-metal transition. We find the electrical resistance of both stoichiometric as well as off-stoichiometric vanadium oxide films can be modulated with RF wave exposures from a distance. The response of the materials to the RF waves can be enhanced by either increasing the power received by the sample or reducing channel separation. We report a significant ~73% drop in resistance with a 5 {\mu}m channel gap of the VO2 film at a characteristic response time of 16 microseconds. The peak sensitivity is proximal to the phase transition temperature boundary that can be engineered via doping and crystal chemistry. Dynamic sensing measurements highlight the films' rapid response and broad-spectrum sensitivity. Engineering electronic phase boundaries in correlated electron systems could offer new capabilities in emerging communication technologies., Comment: 16 pages, 5 figures

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing novel ferroelectric materials and electrets using light-ion doping., Comment: 13 pages, 5 figures

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient artificial intelligence and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing phase transitions. Here we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically-relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to 4 fold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials, and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning., Comment: 37 pages, 5 figures, 6 supplementary figures

Solid-state devices made from correlated oxides such as perovskite nickelates are promising for neuromorphic computing by mimicking biological synaptic function. However, comprehending dopant action at the nanoscale poses a formidable challenge to understanding the elementary mechanisms involved. Here, we perform operando infrared nanoimaging of hydrogen-doped correlated perovskite, neodymium nickel oxide (H-NdNiO3) devices and reveal how an applied field perturbs dopant distribution at the nanoscale. This perturbation leads to stripe phases of varying conductivity perpendicular to the applied field, which define the macroscale electrical characteristics of the devices. Hyperspectral nano-FTIR imaging in conjunction with density functional theory calculations unveil a real-space map of multiple vibrational states of H-NNO associated with OH stretching modes and their dependence on the dopant concentration. Moreover, the localization of excess charges induces an out-of-plane lattice expansion in NNO which was confirmed by in-situ - x-ray diffraction and creates a strain that acts as a barrier against further diffusion. Our results and the techniques presented here hold great potential to the rapidly growing field of memristors and neuromorphic devices wherein nanoscale ion motion is fundamentally responsible for function., Comment: 30 pages, 5 figures in the main text and 5 figures in the Supplementary Material

We demonstrate an electrically controlled metal-VO2 metasurface for the mid-wave infrared that simultaneously functions as a tunable optical switch, an optical limiter with a tunable limiting threshold, and a nonlinear optical isolator with a tunable operating range. The tunability is achieved via Joule heating through the metal comprising the metasurface, resulting in an integrated optoelectronic device. As an optical switch, the device has an experimental transmission ratio of ~100 when varying the bias current. Operating as an optical limiter, we demonstrated tunability of the limiting threshold from 20 mW to 180 mW of incident laser power. Similar degrees of tunability are also achieved for nonlinear optical isolation, which enables asymmetric (nonreciprocal) transmission., Comment: Main text + supplementary

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. Here, we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly-parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean-satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This paper discusses select examples of these approaches, and provides a perspective for the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

Both the magnitude and spectrum of the blackbody-radiation distribution change with temperature. Here, we designed the temperature-dependent spectral emissivity of a coating to counteract all the changes in the blackbody-radiation distribution over a certain temperature range, enabled by the nonhysteretic insulator-to-metal phase transition of SmNiO3. At each wavelength within the long-wave infrared atmospheric-transparency window, the thermal radiance of our coating remains nearly constant over a temperature range of at least 20 {\deg}C. Our approach can conceal thermal gradients and transient temperature changes from infrared imaging systems, including those that discriminate by wavelength, such as multispectral and hyperspectral cameras., Comment: Main text + supplementary

We demonstrate spatial modification of the optical properties of thin-film metal oxides, zinc oxide and vanadium dioxide as representatives, using a commercial focused ion beam (FIB) system. Using a Ga+ FIB and thermal annealing, we demonstrated variable doping of a band semiconductor, zinc oxide (ZnO), achieving carrier concentrations from 10^18 cm-3 to 10^20 cm-3. Using the same FIB without subsequent thermal annealing, we defect-engineered a correlated semiconductor, vanadium dioxide (VO2), locally modifying its insulator-to-metal transition (IMT) temperature by range of ~25 degrees C. Such area-selective modification of metal oxides by direct writing using a FIB provides a simple, mask-less route to the fabrication of optical structures, especially when multiple or continuous levels of doping or defect density are required., Comment: Main text + supplementary. Updated manuscript with some more science

Neuromorphic computing which aims to mimic the collective and emergent behavior of the brain's neurons, synapses, axons, dendrites offers an intriguing, potentially disruptive solution to society's ever-growing computational needs. Although much progress has been made in designing circuit elements that mimic the behavior of neurons and synapses, challenges remain in designing networks of elements that feature a collective response behavior. We present simulations of networks of circuits and devices based on superconducting and Mott-insulating oxides that display a multiplicity of emergent states that depend on the spatial configuration of the network. Our proposed network designs are based on experimentally known ways of tuning the properties of these oxides using light ions. We show how neuronal and synaptic behavior can be achieved with arrays of superconducting Josephson junction loops, all within the same device. We also show how a multiplicity of synaptic states could be achieved by designing arrays of devices based on hydrogenated rare-earth nickelates. Together, our results demonstrate a new research platform that utilizes the collective macroscopic properties of quantum materials to mimic the emergent behavior found in biological systems., Comment: 11 pages, 8 figures

We use a 30-nm x-ray beam to study the spatially resolved properties of a SmNiO$_3$-based nanodevice that is doped with protons. The x-ray absorption spectra supported by density-functional theory (DFT) simulations show partial reduction of nickel valence in the region with high proton concentration, which leads to the insulating behavior. Concurrently, x-ray diffraction reveals only a small lattice distortion in the doped regions. Together, our results directly show that the knob which proton doping modifies is the electronic valency, and not the crystal lattice. The studies are relevant to on-going efforts to disentangle structural and electronic effects across metal-insulator phase transitions in correlated oxides.

Nano-membrane tri-gate beta-gallium oxide (\b{eta}-Ga2O3) field-effect transistors (FETs) on SiO2/Si substrate fabricated via exfoliation have been demonstrated for the first time. By employing electron beam lithography, the minimum-sized features can be defined with a 50 nm fin structure. For high-quality interface between \b{eta}-Ga2O3 and gate dielectric, atomic layer-deposited 15-nm-thick aluminum oxide (Al2O3) was utilized with Tri-methyl-aluminum (TMA) self-cleaning surface treatment. The fabricated devices demonstrate extremely low subthreshold slope (SS) of 61 mV/dec, high drain current (IDS) ON/OFF ratio of 1.5 X 109, and negligible transfer characteristic hysteresis. We also experimentally demonstrated robustness of these devices with current-voltage (I-V) characteristics measured at temperatures up to 400 {\deg}C., Comment: 5 pages, 6 figures

PdCoO2 , belonging to a family of triangular oxides called delafossite, is one of the most conducting oxides. Its in-plane conductivity is comparable to those of the best metals, and exhibits hydrodynamic electronic transport with extremely long mean free path at cryogenic temperatures. Nonetheless, it is nonmagnetic despite the presence of the cobalt ion. Here, we show that a mild hydrogenation process reduces PdCoO2 thin films to an atomically-mixed alloy of PdCo with strong out-of-plane ferromagnetism and sign-tunable anomalous Hall effect. Considering that many other compounds remain little affected under a similar hydrogenation condition, this discovery may provide a route to creating novel spintronic heterostructures combining strong ferromagnetism, involving oxides and other functional materials.

Strongly correlated materials that exhibit an insulator-metal transition are key candidates in the search for new computing platforms. Understanding the pathways and timescales underlying the electrically-driven insulator-metal transition is crucial for uncovering the fundamental limits of device operation. Using stroboscopic electron diffraction, we perform synchronized time-resolved measurements of atomic motions and electronic transport in operating vanadium dioxide switches. We discover an electrically-triggered, isostructural state that forms transiently on microsecond timescales, stabilized by local heterogeneities and interfacial interactions between the equilibrium phases. This metastable phase bears striking similarity to that formed under photoexcitation within picoseconds, suggesting a universal transformation pathway across eight orders of magnitude of timescale. Our results establish a new route for uncovering non-equilibrium and metastable phases in correlated materials, and open avenues for engineering novel dynamical behavior in nanoelectronics.

Oxygen vacancies play a crucial role in the control of the electronic, magnetic, ionic, and transport properties of functional oxide perovskites. Rare earth nickelates (RENiO$_{3-x}$) have emerged over the years as a rich platform to study the interplay between the lattice, the electronic structure, and ordered magnetism. In this study, we investigate the evolution of the electronic and magnetic structure in thin films of RENiO$_{3-x}$, using a combination of X-ray absorption spectroscopy and imaging, resonant X-ray scattering, and extended multiplet ligand field theory modeling. We find that oxygen vacancies modify the electronic configuration within the Ni-O orbital manifolds, leading to a dramatic evolution of long-range electronic transport pathways despite the absence of nanoscale phase separation. Remarkably, magnetism is robust to substantial levels of carrier doping, and only a moderate weakening of the $(1/4, 1/4, 1/4)_{pc}$ antiferromagnetic order parameter is observed, whereas the magnetic transition temperature is largely unchanged. Only at a certain point long-range magnetism is abruptly erased without an accompanying structural transition. We propose the progressive disruption of the 3D magnetic superexchange pathways upon introduction of point defects as the mechanism behind the sudden collapse of magnetic order in oxygen-deficient nickelates. Our work demonstrates that, unlike most other oxides, ordered magnetism in RENiO$_{3-x}$ is mostly insensitive to carrier doping. The sudden collapse of ordered magnetism upon oxygen removal may provide a new mechanism for solid-state magneto-ionic switching and new applications in antiferromagnetic spintronics., Comment: 6 pages, 4 figures

Optical limiters are nonlinear devices that feature decreasing transmittance with increasing incident optical intensity, and thus can protect sensitive components from high-intensity illumination. The ideal optical limiter reflects rather than absorbs light in its active ("limiting") state, minimizing risk of damage to the limiter itself. Previous efforts to realize reflective limiters were based on embedding nonlinear layers into relatively thick multilayer photonic structures, resulting in substantial fabrication complexity, reduced speed and, in some instances, limited working bandwidth. We overcome these tradeoffs by using the insulator-to-metal transition in vanadium dioxide (VO2) to achieve intensity-dependent modulation of resonant transmission through aperture antennas. Due to the dramatic change of optical properties across the insulator-to-metal transition, low-quality-factor resonators were sufficient to achieve high on-off ratios in device transmittance. As a result, our ultra-thin reflective limiter (thickness ~1/100 of the free-space wavelength) is broadband in terms of operating wavelength (> 2 um at 10 um) and angle of incidence (up to ~50$\deg$ away from the normal)., Comment: Main text + supplementary

Subwavelength nanoparticles can support electromagnetic resonances with distinct features depending on their size, shape and nature. For example, electric and magnetic Mie resonances occur in dielectric particles, while plasmonic resonances appear in metals. Here, we experimentally demonstrate that the multipolar resonances hosted by VO2 nanocrystals can be dynamically tuned and switched thanks to the insulator-to-metal transition of VO2. Using both Mie theory and Maxwell Garnett effective medium theory, we retrieve the complex refractive index of the effective medium composed of a slab of VO2 nanospheres embedded in SiO2 and show that such a resulting metamaterial presents distinct optical tunability compared to unpatterned VO2. We further show that this provides a new degree of freedom to design low-loss phase-change metamaterials with designer optical tunability and actively controlled light scattering.

We present a method for nanoscale thermal imaging of insulating thin films using atomic force microscopy (AFM), and we demonstrate its utility on VO$_2$. We sweep the applied voltage $V$ to a conducting AFM tip in contact mode and measure the local current $I$ through the film. By fitting the $IV$ curves to a Poole-Frenkel conduction model at low $V$, we calculate the local temperature with spatial resolution better than 50 nm using only fundamental constants and known film properties. Our thermometry technique enables local temperature measurement of \textit{any} insulating film dominated by the Poole-Frenkel conduction mechanism, and can be extended to insulators that display other conduction mechanisms.

Thermal emission is the process by which all objects at non-zero temperatures emit light, and is well-described by the classic Planck, Kirchhoff, and Stefan-Boltzmann laws. For most solids, the thermally emitted power increases monotonically with temperature in a one-to-one relationship that enables applications such as infrared imaging and non-contact thermometry. Here, we demonstrate ultrathin thermal emitters that violate this one-to-one relationship via the use of samarium nickel oxide (SmNiO3), a strongly correlated quantum material that undergoes a fully reversible, temperature-driven solid-state phase transition. The smooth and hysteresis-free nature of this unique insulator-to-metal (IMT) phase transition allows us to engineer the temperature dependence of emissivity to precisely cancel out the intrinsic blackbody profile described by the Stefan-Boltzmann law, for both heating and cooling. Our design results in temperature-independent thermally emitted power within the long-wave atmospheric transparency window (wavelengths of 8 - 14 um), across a broad temperature range of ~30 {\deg}C, centered around ~120 {\deg}C. The ability to decouple temperature and thermal emission opens a new gateway for controlling the visibility of objects to infrared cameras and, more broadly, new opportunities for quantum materials in controlling heat transfer., Comment: Main text and supplementary

The insulator-to-metal transition (IMT) in vanadium dioxide (VO2) can enable a variety of optics applications, including switching and modulation, optical limiting, and tuning of optical resonators. Despite the widespread interest in optics, the optical properties of VO2 across its IMT are scattered throughout the literature, and are not available in some wavelength regions. We characterized the complex refractive index of VO2 thin films across the IMT for free-space wavelengths from 300 nm to 30 {\mu}m, using broadband spectroscopic ellipsometry, reflection spectroscopy, and the application of effective-medium theory. We studied VO2 thin films of different thickness, on two different substrates (silicon and sapphire), and grown using different synthesis methods (sputtering and sol gel). While there are differences in the optical properties of VO2 synthesized under different conditions, they are relatively minor compared to the change resulting from the IMT, most notably in the ~2 - 11 {\mu}m range where the insulating phase of VO2 has relatively low optical loss. We found that the macroscopic optical properties of VO2 are much more robust to sample-to-sample variation compared to the electrical properties, making the refractive-index datasets from this article broadly useful for modeling and design of VO2-based optical and optoelectronic components., Comment: Main text + supplementary information

We demonstrate memory devices based on proton doping and re-distribution in perovskite nickelates (RNiO3, {R=Sm,Nd}) that undergo filling-controlled Mott transition. Switching speeds as high as 30 ns in two-terminal devices patterned by electron-beam lithography is observed. The state switching speed reported here are 300X greater than what has been noted with proton-driven resistance switching to date. The ionic-electronic correlated oxide memory devices also exhibit multi-state non-volatile switching. The results are of relevance to use of quantum materials in emerging memory and neuromorphic computing., Comment: 4 figures

A limiting optical diode is an asymmetric nonlinear device that is bidirectionally transparent at low power, but becomes opaque when illuminated by sufficiently intense light incident from a particular direction. We explore the use of a phase-transition material, vanadium dioxide (VO2), as an active element of limiting optical diodes. The VO2 phase transition can be triggered by optical absorption, resulting in a change in refractive index orders of magnitude larger than what can be achieved with conventional nonlinearities. As a result, a limiting optical diode based on incident-direction-dependent absorption in a VO2 layer can be very thin, and can function at low powers without field enhancement, resulting in broadband operation. We demonstrate a simple thin-film limiting optical diode comprising a transparent substrate, a VO2 film, and a semi-transparent metallic layer. For sufficiently high incident intensity, our proof-of-concept device realizes broadband asymmetric transmission across the near infrared, and is approximately ten times thinner than the free-space wavelength.

Thermal runaway occurs when a rise in system temperature results in heat generation rates exceeding dissipation rates. Here we demonstrate that thermal runaway occurs in thermal radiative systems, given a sufficient level of negative differential thermal emission. By exploiting the insulator-to-metal phase transition of vanadium dioxide, we show that a small increase in heat generation (e.g., 10 nW/mm2) can result in a large change in surface temperature (e.g., ~35 K), as the thermal emitter switches from high emissivity to low emissivity. While thermal runaway is typically associated with catastrophic failure mechanisms, detailed understanding and control of this phenomenon may give rise to new opportunities in infrared sensing, camouflage, and rectification.

A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we present a novel unsupervised learning mechanism ASP (Adaptive Synaptic Plasticity) for improved recognition with Spiking Neural Networks (SNNs) for real time on-line learning in a dynamic environment. We incorporate an adaptive weight decay mechanism with the traditional Spike Timing Dependent Plasticity (STDP) learning to model adaptivity in SNNs. The leak rate of the synaptic weights is modulated based on the temporal correlation between the spiking patterns of the pre- and post-synaptic neurons. This mechanism helps in gradual forgetting of insignificant data while retaining significant, yet old, information. ASP, thus, maintains a balance between forgetting and immediate learning to construct a stable-plastic self-adaptive SNN for continuously changing inputs. We demonstrate that the proposed learning methodology addresses catastrophic forgetting while yielding significantly improved accuracy over the conventional STDP learning method for digit recognition applications. Additionally, we observe that the proposed learning model automatically encodes selective attention towards relevant features in the input data while eliminating the influence of background noise (or denoising) further improving the robustness of the ASP learning., Comment: 14 pages, 14 figures

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making1-3. This behavior, known as habituation, is universal among forms of life with a central nervous system, and interestingly observed even in single cellular organisms that do not possess a brain4-5. Here, we report the discovery of habituation based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization via reversible dopant incorporation. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by a combination of first-principles theory, synchrotron investigations, ab-initio dynamical simulations and in-situ environmental breathing studies. We implement a new learning algorithm inspired from the conductance relaxation behavior of perovskites that naturally incorporates habituation and demonstrate "learning to forget": a key feature of animal and human brains6. Most surprisingly, our results show that incorporating this elementary skill in learning dramatically boosts the capability of artificial cognitive systems.

We use electronic transport and atom probe tomography to study ZnO:Al / SiO2 / Si Schottky junctions on lightly-doped n- and p-type Si. We vary the carrier concentration in the the ZnO:Al films by two orders of magnitude but the Schottky barrier height remains constant, consistent with Fermi level pinning seen in metal / Si junctions. Atom probe tomography shows that Al segregates to the interface, so that the ZnO:Al at the junction is likely to be metallic even when the bulk of the ZnO:Al film is semiconducting. We hypothesize that Fermi level pinning is connected to the insulator-metal transition in doped ZnO, and that controlling this transition may be key to un-pinning the Fermi level in oxide / Si Schottky junctions.

Strongly correlated electron systems such as the rare-earth nickelates (RNiO3, R = rare-earth element) can exhibit synapse-like continuous long term potentiation and depression when gated with ionic liquids; exploiting the extreme sensitivity of coupled charge, spin, orbital, and lattice degrees of freedom to stoichiometry. We present experimental real-time, device-level classical conditioning and unlearning using nickelate-based synaptic devices in an electronic circuit compatible with both excitatory and inhibitory neurons. We establish a physical model for the device behavior based on electric-field driven coupled ionic-electronic diffusion that can be utilized for design of more complex systems. We use the model to simulate a variety of associate and non-associative learning mechanisms, as well as a feedforward recurrent network for storing memory. Our circuit intuitively parallels biological neural architectures, and it can be readily generalized to other forms of cellular learning and extinction. The simulation of neural function with electronic device analogues may provide insight into biological processes such as decision making, learning and adaptation, while facilitating advanced parallel information processing in hardware.

Interaction between the lattice and the orbital degrees of freedom not only makes rare-earth nickelates unusually "bad metal", but also introduces a temperature driven insulator-metal phase transition. Here we investigate this insulator-metal phase transition in thin films of $\mathrm{SmNiO_3}$ using the slow time dependent fluctuations (noise) in resistivity. The normalized magnitude of noise is found to be extremely large, being nearly eight orders of magnitude higher than thin films of common disordered metallic systems, and indicates electrical conduction via classical percolation in a spatially inhomogeneous medium. The higher order statistics of the fluctuations indicate a strong non-Gaussian component of noise close to the transition, attributing the inhomogeneity to co-existence of the metallic and insulating phases. Our experiment offers a new insight on the impact of lattice-orbital coupling on the microscopic mechanism of electron transport in the rare-earth nickelates., Comment: 5 pages, 4 figures