Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing.

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage.

Correction: High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing.

Correction for 'High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing' by Sujaya Kumar Vishwanath , , 2024, , 2643-2656, https://doi.org/10.1039/D3MH02055J.

High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing.

Despite impressive demonstrations of memristive behavior with halide perovskites, no clear pathway for material and device design exists for their applications in neuromorphic computing. Present approaches are limited to single element structures, fall behind in terms of switching reliability and scalability, and fail to map out the analog programming window of such devices. Here, we systematically design and evaluate robust pyridinium-templated one-dimensional halide perovskites as crossbar memristive materials for artificial neural networks.

Strongly Confined CsPbBr Quantum Dots as Quantum Emitters and Building Blocks for Rhombic Superlattices.

The success of the colloidal semiconductor quantum dots (QDs) field is rooted in the precise synthetic control of QD size, shape, and composition, enabling electronically well-defined functional nanomaterials that foster fundamental science and motivate diverse fields of applications. While the exploitation of the strong confinement regime has been driving commercial and scientific interest in InP or CdSe QDs, such a regime has still not been thoroughly explored and exploited for lead-halide perovskite QDs, mainly due to a so far insufficient chemical stability and size monodispersity of perovskite QDs smaller than about 7 nm. Here, we demonstrate chemically stable strongly confined 5 nm CsPbBr colloidal QDs via a postsynthetic treatment employing didodecyldimethylammonium bromide ligands.

Ionic-electronic halide perovskite memdiodes enabling neuromorphic computing with a second-order complexity.

With increasing computing demands, serial processing in von Neumann architectures built with zeroth-order complexity digital circuits is saturating in computational capacity and power, entailing research into alternative paradigms. Brain-inspired systems built with memristors are attractive owing to their large parallelism, low energy consumption, and high error tolerance. However, most demonstrations have thus far only mimicked primitive lower-order biological complexities using devices with first-order dynamics.

Assessing the Drawbacks and Benefits of Ion Migration in Lead Halide Perovskites.

Since the inception of the unprecedented rise of halide perovskites for photovoltaic research, ion migration has shadowed this material class with undesirable hysteresis and degradation effects, limiting its practical implementations. Unfortunately, the localized doping and electrochemical reactions triggered by ion migration cause many more undesirable effects that are often unreported or misinterpreted because they deviate from classical semiconductor behavior. In this Perspective, we provide a concise overview of such effects in halide perovskites, such as operational instability in photovoltaics, polarization-induced abnormal external quantum efficiency in light-emitting diodes, and energy channel shift and anomalous sensitivities in hard radiation detection.

Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing.

Many in-memory computing frameworks demand electronic devices with specific switching characteristics to achieve the desired level of computational complexity. Existing memristive devices cannot be reconfigured to meet the diverse volatile and non-volatile switching requirements, and hence rely on tailored material designs specific to the targeted application, limiting their universality. "Reconfigurable memristors" that combine both ionic diffusive and drift mechanisms could address these limitations, but they remain elusive.

Structural Diversity in Multicomponent Nanocrystal Superlattices Comprising Lead Halide Perovskite Nanocubes.

Nanocrystal (NC) self-assembly is a versatile platform for materials engineering at the mesoscale. The NC shape anisotropy leads to structures not observed with spherical NCs. This work presents a broad structural diversity in multicomponent, long-range ordered superlattices (SLs) comprising highly luminescent cubic CsPbBr NCs (and FAPbBr NCs) coassembled with the spherical, truncated cuboid, and disk-shaped NC building blocks.

An adaptive device for AI neural networks.

[Figure: see text].

Shape-Directed Co-Assembly of Lead Halide Perovskite Nanocubes with Dielectric Nanodisks into Binary Nanocrystal Superlattices.

Self-assembly of colloidal nanocrystals (NCs) holds great promise in the multiscale engineering of solid-state materials, whereby atomically engineered NC building blocks are arranged into long-range ordered structures-superlattices (SLs)-with synergistic physical and chemical properties. Thus far, the reports have by far focused on single-component and binary systems of spherical NCs, yielding SLs isostructural with the known atomic lattices. Far greater structural space, beyond the realm of known lattices, is anticipated from combining NCs of various shapes.

Halide perovskite memristors as flexible and reconfigurable physical unclonable functions.

Physical Unclonable Functions (PUFs) address the inherent limitations of conventional hardware security solutions in edge-computing devices. Despite impressive demonstrations with silicon circuits and crossbars of oxide memristors, realizing efficient roots of trust for resource-constrained hardware remains a significant challenge. Hybrid organic electronic materials with a rich reservoir of exotic switching physics offer an attractive, inexpensive alternative to design efficient cryptographic hardware, but have not been investigated till date.

Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics.

Sensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphery to central processors, at the cost of wiring, latency, fault tolerance and robustness. We envision a decentralized approach where intelligence is embedded in the sensing nodes, using a unique neuromorphic methodology to extract relevant information in robotic skins. Here we specifically address pain perception and the association of nociception with tactile perception to trigger the escape reflex in a sensorized robotic arm.

Optogenetics inspired transition metal dichalcogenide neuristors for in-memory deep recurrent neural networks.

Shallow feed-forward networks are incapable of addressing complex tasks such as natural language processing that require learning of temporal signals. To address these requirements, we need deep neuromorphic architectures with recurrent connections such as deep recurrent neural networks. However, the training of such networks demand very high precision of weights, excellent conductance linearity and low write-noise- not satisfied by current memristive implementations.

Cubic NaSbS as an Ionic-Electronic Coupled Semiconductor for Switchable Photovoltaic and Neuromorphic Device Applications.

The recent emergence of lead halide perovskites as ionic-electronic coupled semiconductors motivates the investigation of alternative solution-processable materials with similar modulatable ionic and electronic transport properties. Here, a novel semiconductor-cubic NaSbS -for ionic-electronic coupled transport is investigated through a combined theoretical and experimental approach. The material exhibits mixed ionic-electronic conductivity in inert atmosphere and superionic conductivity in humid air.

Perturbation-Induced Seeding and Crystallization of Hybrid Perovskites over Surface-Modified Substrates for Optoelectronic Devices.

Growing a monocrystalline layer of lead halide perovskites directly over substrates is necessary to completely harness their stellar properties in optoelectronic devices, as the single crystals of these materials are extremely brittle. We study the crystallization mechanism of perovskites by antisolvent vapor diffusion to its precursor solution and find that heterogeneous nucleation prevails in the process, with the crystallization dish walls providing the energy to overcome the nucleation barrier. By perturbing the system using sonication, we are able to introduce homogeneously nucleated seed crystals in the precursor solution.

Completely Solvent-free Protocols to Access Phase-Pure, Metastable Metal Halide Perovskites and Functional Photodetectors from the Precursor Salts.

Mechanochemistry is a green, solid-state, re-emerging synthetic technique that can rapidly form complex molecules and materials without exogenous heat or solvent(s). Herein, we report the application of solvent-free mechanochemical ball milling for the synthesis of metal halide perovskites, to overcome problems with solution-based syntheses. We prepared phase-pure, air-sensitive CsSnX (X = I, Br, Cl) and its mixed halide perovskites by mechanochemistry for the first time by reactions between cesium and tin(II) halides.

Field-Driven Athermal Activation of Amorphous Metal Oxide Semiconductors for Flexible Programmable Logic Circuits and Neuromorphic Electronics.

Despite extensive research, large-scale realization of metal-oxide electronics is still impeded by high-temperature fabrication, incompatible with flexible substrates. Ideally, an athermal treatment modifying the electronic structure of amorphous metal oxide semiconductors (AMOS) to generate sufficient carrier concentration would help mitigate such high-temperature requirements, enabling realization of high-performance electronics on flexible substrates. Here, a novel field-driven athermal activation of AMOS channels is demonstrated via an electrolyte-gating approach.

Ultralow Power Dual-Gated Subthreshold Oxide Neuristors: An Enabler for Higher Order Neuronal Temporal Correlations.

Inspired by neural computing, the pursuit of ultralow power neuromorphic architectures with highly distributed memory and parallel processing capability has recently gained more traction. However, emulation of biological signal processing via artificial neuromorphic architectures does not exploit the immense interplay between local activities and global neuromodulations observed in biological neural networks and hence are unable to mimic complex biologically plausible adaptive functions like heterosynaptic plasticity and homeostasis. Here, we demonstrate emulation of complex neuronal behaviors like heterosynaptic plasticity, homeostasis, association, correlation, and coincidence in a single neuristor via a dual-gated architecture.

Ionotronic Halide Perovskite Drift-Diffusive Synapses for Low-Power Neuromorphic Computation.

Emulation of brain-like signal processing is the foundation for development of efficient learning circuitry, but few devices offer the tunable conductance range necessary for mimicking spatiotemporal plasticity in biological synapses. An ionic semiconductor which couples electronic transitions with drift-diffusive ionic kinetics would enable energy-efficient analog-like switching of metastable conductance states. Here, ionic-electronic coupling in halide perovskite semiconductors is utilized to create memristive synapses with a dynamic continuous transition of conductance states.

Indium Tungsten Oxide Thin Films for Flexible High-Performance Transistors and Neuromorphic Electronics.

Thin-film transistors (TFTs) with high electrical performances (mobility > 10 cm/V s, V < 1 V, SS < 1 V/decade, on/off ratio ≈ 10) obtained from the silicon- and oxide-based single-crystalline semiconductor materials require high processing temperature and hence are not suitable for flexible electronics. Amorphous oxide-based transparent electronic devices are attractive to meet emerging technological demands where crystalline oxide-/silicon-based architectures cannot provide a solution. Here, we tackle this problem by using a novel amorphous oxide semiconducting material-namely, indium tungsten oxide (IWO)-as the active channel in flexible TFTs (FTFTs).

Doping and Switchable Photovoltaic Effect in Lead-Free Perovskites Enabled by Metal Cation Transmutation.

Creating defect tolerant lead-free halide perovskites is the major challenge for development of high-performance photovoltaics with nontoxic absorbers. Few compounds of Sn, Sb, or Bi possess ns electronic configuration similar to lead, but their poor photovoltaic performances inspire us to evaluate other factors influencing defect tolerance properties. The effect of heavy metal cation (Bi) transmutation and ionic migration on the defects and carrier properties in a 2D layered perovskite (NH ) (Sb Bi ) I system is investigated.

Synergistic Gating of Electro-Iono-Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity.

Emulation of brain-like signal processing with thin-film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di-chalcogenide (MoS ) neuristors are designed to mimic intracellular ion endocytosis-exocytosis dynamics/neurotransmitter-release in chemical synapses using three approaches: (i) electronic-mode: a defect modulation approach where the traps at the semiconductor-dielectric interface are perturbed; (ii) ionotronic-mode: where electronic responses are modulated via ionic gating; and (iii) photoactive-mode: harnessing persistent photoconductivity or trap-assisted slow recombination mechanisms.

Healable and flexible transparent heaters.

Challenges associated with the mechanical fracture of electrical conductors have hindered the realization of truly flexible high performance wearable electronics. Here, transparent healable electrodes have been developed and examined to alleviate these problems. The composite electrode features a layer of an interconnecting AgNW network on a polyurethane film modified with Diels-Alder adducts (PU-DA).

Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing.

Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm V s with good mechanical performance.

Transparent Flexible Multifunctional Nanostructured Architectures for Non-optical Readout, Proximity, and Pressure Sensing.

Electronic skins need to be versatile and able to detect multiple inputs beyond simple pressure and touch while having attributes of transparency and facile manufacturability. Herein, we demonstrate a versatile nanostructured transparent sensor capable of detecting wide range of pressures and proximity as well as novel nonoptical detection of printed patterns. The architecture and fabrication processes are straightforward and show robustness to repeated cycling and testing.