Electrolyte-gated transistors can function as switching elements, artificial synapses and memristive systems, and could be used to create compact and powerful neuromorphic computing networks. However, insight into the underlying physics of such devices, including complex ion dynamics and the resulting capacitances, remains limited. Here we report a concise model for the transient ion-dynamic capacitance in electrolyte-gated transistors. The theory predicts that plasticity, high apparent mobility, sharp subthreshold swing and memristive conductance can be achieved—on demand—in a single transistor by appropriately programming the interfacial ion concentrations or matching the scan speed with ion motions. We then fabricate such multimode transistors using common solid-state electrolyte films and experimentally confirm the different capabilities. We also show in software that the multimode devices could be used to create neural networks that can be switched between conventional artificial neural networks, recurrent neural networks and spiking neural networks.

Advanced field‐effect transistors (FETs) with nontrivial gates (e.g., offset‐gates, mid‐gates, split‐gates, or multi‐gates) or hybrid integrations (e.g., with diodes, photodetectors, or field‐emitters) have been extensively developed in pursuit for the “More‐than‐Moore” demand. But understanding their conduction mechanisms and predicting current–voltage relations is rather difficult due to countless combinations of materials and device factors. Here, it is shown that they could be understood within the same physical picture, i.e., charge transport from gated to nongated semiconductors. One proposes an indicator based on material and device factors for characterizing the transport and derives a unified and simplified solution for describing the current–voltage relations, current saturation, channel potentials, and drift field. It is verified by simulations and experiments of different types of devices with varied materials and device factors, employing organic, oxide, nanomaterial semiconductors in transistors or hybrid integrations. The concise and unified solution provides general rules for quick understanding and designing of these complex, innovative devices.

Precise tuning of phase transition material properties enables multifunctional devices for information processing and energy conversion, but controlling on-device phase transitions and monitoring microscopic mechanisms remains challenging. Here, we develop a lab-on-device system for molybdenum oxide to probe operando hydrogenation mechanisms through in situ electrical and spectral characterization with density functional theory calculations, revealing threshold-driven proton dynamics that govern the transition between nonvolatile memory operation and catalytic hydrogen evolution. Moderate proton intercalation (flux < 10¹⁷cm^-2) achieves a five-order conductance modulation under ambient conditions via polaron formation and stoichiometric optimization (H/Mo up to 22%, Mo/O approaching ideal ratios), outperforming oxygen vacancy engineering. Beyond this threshold (flux ~10¹⁷ cm^-2), intensive proton intercalation triggers electric-to-chemical energy conversion, directly linking proton history to catalytic activity. Leveraging these principles, we achieve nonvolatile electrochemical memory with linear synaptic and accumulative neuronal functionalities, and demonstrate an all electrochemical random-access memory neural network hardware that executes memory-efficient rank-order coding for sparse signals even under noisy conditions.

Amorphous oxide semiconductor thin-film transistors (TFTs) are widely used in display technology, yet balancing high mobility with illumination stability is challenging. In this article, we report a homojunction TFT based on Pr-doped In2O3 (InPrO), where the oxygen partial pressure is modulated to control device's mobility and stability significantly. Combining the characteristic of enhanced mobility at low oxygen partial pressure and the enhanced recombination role of Pr at high oxygen partial pressure, compatibility between high mobility and high illumination stability is achieved. This InPrO homojunction TFT exhibits excellent electrical characteristics, including a mobility of 50 cm2/Vs, a threshold voltage of 0.1 V, an Ion/off of 108, and a subthreshold swing of 0.1 V/dec. It also demonstrates enhanced stability, with threshold voltage shifts of −0.6 V for negative bias stress, 1.0 V for positive bias stress, and −0.9 V for negative bias illumination stress. This work provides a pathway for advancing AOS TFTs in transparent display technologies.