Proton Conducting Neuromorphic Materials and Devices

Chemical Reviews, Год журнала: 2024, Номер 124(16), С. 9733 - 9784

Опубликована: Июль 22, 2024

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components enable the development of energy-efficient machines. In brain, ionic currents temporal concentration gradients control information flow storage. It is therefore interest examine materials devices for neuromorphic wherein electronic can propagate. Protons being mobile under an external electric field offers a compelling avenue facilitating functionalities synapses neurons. this review, we first highlight interesting analog protons as neurotransmitters various animals. We then discuss experimental approaches mechanisms proton doping classes inorganic organic proton-conducting advancement architectures. Since hydrogen among lightest elements, characterization solid matrix requires advanced techniques. review powerful synchrotron-based spectroscopic techniques characterizing well complementary scattering detect hydrogen. First-principles calculations are discussed they help provide understanding migration structure modification. Outstanding scientific challenges further our its use emerging electronics pointed out.

Язык: Английский

Neuromorphic one-shot learning utilizing a phase-transition material

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(17)

Опубликована: Апрель 17, 2024

Design of hardware based on biological principles neuronal computation and plasticity in the brain is a leading approach to realizing energy- sample-efficient AI learning machines. An important factor selection building blocks identification candidate materials with physical properties suitable emulate large dynamic ranges varied timescales signaling. Previous work has shown that all-or-none spiking behavior neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate devices prototypical metal-insulator-transition material, vanadium dioxide (VO 2 ), dynamically controlled access continuum intermediate resistance states. Furthermore, timescale their intrinsic relaxation configured match range biologically relevant from milliseconds seconds. We exploit these device three aspects analog computation: fast (~1 ms) soma compartment, slow (~100 dendritic ultraslow s) biochemical signaling involved temporal credit assignment for recently discovered mechanism one-shot learning. Simulations show an artificial neural network using VO control agent navigating spatial environment learn efficient path reward up fourfold fewer trials than standard methods. The relaxations described our study may engineered variety thermal, electrical, or optical stimuli, suggesting further opportunities neuromorphic hardware.

Язык: Английский

Minimal motifs for habituating systems

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(41)

Опубликована: Окт. 4, 2024

Habituation—a phenomenon in which a dynamical system exhibits diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld—is universally observed living systems from animals unicellular organisms. Despite its prevalence, generic mechanisms for this fundamental form of learning remain poorly defined. Drawing inspiration prior work on respond adaptively step inputs, we study habituation nonlinear dynamics perspective. This approach enables us formalize classical hallmarks have been experimentally identified diverse organisms and scenarios. We use framework investigate distinct circuits capable habituation. In particular, show driven linear memory variable with static nonlinearities acting at input output can implement numerous mathematically interpretable manner. establishes foundation understanding substrates primitive behavior offers blueprint identification habituating biological systems.

Язык: Английский