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Ion‐sensitive field‐effect transistors (ISFETs) are electrochemical sensors that work on the principle of metal‐oxide field‐effect transistors. Dual‐gate ion‐sensitive field‐effect transistors (DGISFETs) are an advanced version of ISFETs with an additional gate dielectric, resulting in sensitivity enhancement on account of the coupling of the capacitances of the two gate dielectrics. ISFETs were demonstrated first in 1970 and there are several review articles available on various aspects of ISFETs; although DGISFETs were first demonstrated in 2010, there are no focused review articles on this subject and this is the motivation of present work. This review has explored the understanding of the basic platform, the working principle, different structures, and various applications of DGISFETs. Further, types of DGISFETs are elaborated based on their architecture, material used for fabrication, and substrates used for such devices with utilization of different semiconductor and gate dielectric materials, rigid and flexible substrates. The state‐of‐the‐art of rigid and flexible DGISFETs is discussed for various applications. Challenges in the fabrication and utilization of DGISFETs in various fields and further advances are discussed.   

Human brain outperforms the current von Neumann digital computer in many aspects, such as energy efficiency and fault‐tolerance. Inspired by human brain, neuromorphic computation has attracted increasing research interest. In recent years, emerging neuromorphic devices are widely developed for neuromorphic computing. Herein, the recent progress on transistor‐based neuromorphic devices is presented. First, a brief introduction of biological synaptic and neuronal functions is given. Then operation principles and latest progress in neuromorphic transistors, including ion‐gate neuromorphic transistors, ferroelectric‐gate neuromorphic transistors, and floating‐gate neuromorphic transistors, are reviewed and discussed. At last, conclusions and prospects are given. Herein, the recent progress of emerging transistor‐based neuromorphic devices is presented. Beginning with an introduction of biological synaptic and neuronal functions, the operation principles and latest progress in neuromorphic transistors, including ion‐gate neuromorphic transistors, ferroelectric‐gate neuromorphic transistors, and floating‐gate neuromorphic transistors, are reviewed and discussed. At last, conclusions and prospects are given.

In this study, we developed a high-performance extended-gate ion-sensitive field-effect transistor (EG-ISFET) sensor on a flexible polyethylene naphthalate (PEN) substrate. The EG-ISFET sensor comprises a tin dioxide (SnO 2 ) extended gate, which acts as a detector, and an amorphous indium-gallium-zinc-oxide (a-IGZO) thin-film transistor (TFT) for a transducer. In order to self-amplify the sensitivity of the pH sensors, we designed a uniquely-structured a-IGZO TFT transducer with a high-k engineered top gate insulator consisting of a silicon dioxide/tantalum pentoxide (SiO 2 /Ta 2 O 5 ) stack, a floating layer under the channel, and a control gate coplanar with the channel. The SiO 2 /Ta 2 O 5 stacked top gate insulator and in-plane control gate significantly contribute to capacitive coupling, enabling the amplification of sensitivity to be enlarged compared to conventional dual-gate transducers. For a pH sensing method suitable for EG-ISFET sensors, we propose an in-plane control gate (IG) sensing mode, instead of conventional single-gate (SG) or dual-gate (DG) sensing modes. As a result, a pH sensitivity of 2364 mV/pH was achieved at room temperature - this is significantly superior to the Nernstian limit (59.15 mV/pH at room temperature). In addition, we found that non-ideal behavior was improved in hysteresis and drift measurements. Therefore, the proposed transparent EGISFFET sensor with an IG sensing mode is expected to become a promising platform for flexible and wearable biosensing applications.

The recent proliferation of published TRP channel structures provides a foundation for understanding the diverse functional properties of this important family of ion channel proteins. To facilitate mechanistic investigations, we constructed a structure-based alignment of the transmembrane domains of 120 TRP channel structures. Comparison of structures determined in the absence or presence of activating stimuli reveals similar constrictions in the central ion permeation pathway near the intracellular end of the S6 helices, pointing to a conserved cytoplasmic gate and suggesting that most available structures represent non-conducting states. Comparison of the ion selectivity filters toward the extracellular end of the pore supports existing hypotheses for mechanisms of ion selectivity. Also conserved to varying extents are hot spots for interactions with hydrophobic ligands, lipids and ions, as well as discrete alterations in helix conformations. This analysis therefore provides a framework for investigating the structural basis of TRP channel gating mechanisms and pharmacology, and, despite the large number of structures included, reveals the need for additional structural data and for more functional studies to establish the mechanistic basis of TRP channel function.

A novel ion gate for electrospray-ionization atmospheric-pressure ion-mobility spectrometry (ESI-IMS) has been constructed and evaluated. The ion gate consisted of a chopper wheel with two windows--one for periodic ion passage from the ESI source into the drift region and the other for timing and synchronization purposes. The instrument contained a 45.0 cm long drift tube comprising 78 stainless steel rings (0.12 cm thick, 4.90 cm o.d., 2.55 cm i.d.). The rings were connected together in series with 3.34-MΩ resistors. The interface plate and the back plate were also connected with the first and the last rings, respectively, of the drift tube with 3.34-MΩ resistors. A potential of -20.0 kV was applied to the back plate and the interface plate was grounded. The drift tube was maintained at an electric field strength of ~400 V cm-¹. An aperture grid was attached to the last ring in front of a Faraday plate detector, center-to-center. Several sample solutions were electrosprayed at +5.0 kV with +500 V applied to the ion gate. Baseline separations of selected benzodiazepines, antidepressants, and antibiotics were observed with moderate experimental resolution of ~70.

An analytical model for current (I)–voltage (V) characteristics of a short-channel ion-implanted GaAs MESFET has been presented for dark and illuminated conditions. For the sake of simplicity, the non-analytic (i.e. non-integral) Gaussian doping function commonly considered for the channel doping of an ion-implanted GaAs metal semiconductor field effect transistor (MESFET) has been replaced by an analytic Gaussian-like doping profile in the vertical direction. The device uses an indium–tin oxide-based Schottky gate through which an optical radiation of 0.87 μm wavelength is coupled from an external source into the device to modulate the I–V characteristics of the short-gate length GaAs MESFET. The coupled light generates electron–hole pairs in the active channel region below the gate and develops a photovoltage across the Schottky gate–channel junction and modulates the device characteristics. This study also includes the modelling of this photovoltaic effect by taking the short-gate length effects into consideration. The developed model includes the effects of doping profile and device parameters on the drain current of the short-channel ion-implanted GaAs MESFETs under dark and illuminated conditions of operations. The accuracy of the proposed model is extensively verified by comparing the theoretically predicted results with numerical simulation data obtained by using the commercially available ATLASTM device simulation software.

Ion channel proteins control ionic flux across biological membranes through conformational changes in their transmembrane pores. An exponentially increasing number of channel structures captured in different conformational states are now being determined; however, these newly resolved structures are commonly classified as either open or closed based solely on the physical dimensions of their pore, and it is now known that more accurate annotation of their conductive state requires additional assessment of the effect of pore hydrophobicity. A narrow hydrophobic gate region may disfavor liquid-phase water, leading to local dewetting, which will form an energetic barrier to water and ion permeation without steric occlusion of the pore. Here we quantify the combined influence of radius and hydrophobicity on pore dewetting by applying molecular dynamics simulations and machine learning to nearly 200 ion channel structures. This allows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the presence of hydrophobic gates. This not only enables the functional annotation of new channel structures as soon as they are determined, but also may facilitate the design of novel nanopores controlled by hydrophobic gates.

Piezo1 and Piezo2 belong to a family of mechanically-activated ion channels implicated in a wide range of physiological processes. Mechanical stimulation triggers Piezo channels to open, but their characteristic fast inactivation process results in rapid closure. Several disease-causing mutations in Piezo1 alter the rate of inactivation, highlighting the importance of inactivation to the normal function of this channel. However, despite the structural identification of two physical constrictions within the closed pore, the mechanism of inactivation remains unknown. Here we identify a functionally conserved inactivation gate in the pore-lining inner helix of mouse Piezo1 and Piezo2 that is distinct from the two constrictions. We show that this gate controls the majority of Piezo1 inactivation via a hydrophobic mechanism and that one of the physical constrictions acts as a secondary gate. Our results suggest that, unlike other rapidly inactivating ion channels, a hydrophobic barrier gives rise to fast inactivation in Piezo channels.

In recent years, small-scale quantum information processors have been realized in multiple physical architectures. These systems provide a universal set of gates that allow one to implement any given unitary operation. The decomposition of a particular algorithm into a sequence of these available gates is not unique. Thus, the fidelity of the implementation of an algorithm can be increased by choosing an optimized decomposition into available gates. Here, we present a method to find such a decomposition, where a small-scale ion trap quantum information processor is used as an example. We demonstrate a numerical optimization protocol that minimizes the number of required multi-qubit entangling gates by design. Furthermore, we adapt the method for state preparation, and quantum algorithms including in-sequence measurements.