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Abstract Cardiac microtissues provide a promising platform for disease modeling and developmental studies, which require the close monitoring of the multimodal excitation-contraction dynamics. However, no existing assessing tool can track these multimodal dynamics across the live tissue. We develop a tissue-like mesh bioelectronic system to track these multimodal dynamics. The mesh system has tissue-level softness and cell-level dimensions to enable stable embedment in the tissue. It is integrated with an array of graphene sensors, which uniquely converges both bioelectrical and biomechanical sensing functionalities in one device. The system achieves stable tracking of the excitation-contraction dynamics across the tissue and throughout the developmental process, offering comprehensive assessments for tissue maturation, drug effects, and disease modeling. It holds the promise to provide more accurate quantification of the functional, developmental, and pathophysiological states in cardiac tissues, creating an instrumental tool for improving tissue engineering and studies. 

Abstract Air humidity is a vast, sustainable reservoir of energy that, unlike solar and wind, is continuously available. However, previously described technologies for harvesting energy from air humidity are either not continuous or require unique material synthesis or processing, which has stymied scalability and broad deployment. Here, a generic effect for continuous energy harvesting from air humidity is reported, which can be applied to a broad range of inorganic, organic, and biological materials. The common feature of these materials is that they are engineered with appropriate nanopores to allow air water to pass through and undergo dynamic adsorption–desorption exchange at the porous interface, resulting in surface charging. The top exposed interface experiences this dynamic interaction more than the bottom sealed interface in a thin‐film device structure, yielding a spontaneous and sustained charging gradient for continuous electric output. Analyses of material properties and electric outputs lead to a “leaky capacitor” model that can describe how electricity is harvested and predict current behaviors consistent with experiments. Predictions from the model guide the fabrication of devices made from heterogeneous junctions of different materials to further expand the device category. The work opens a wide door for the broad exploration of sustainable electricity from air. 

Abstract An efficient strategy for addressing individual devices is required to unveil the full potential of memristors for high‐density memory and computing applications. Existing strategies using two‐terminal selectors that are preferable for compact integration have trade‐offs in reduced generality or functional window. A strategy that applies to broad memristors and maintains their full‐range functional window is proposed. This strategy uses a type of unipolar switch featuring a transient relaxation or retention as the selector. The unidirectional current flow in the switch suppresses the sneak‐path current, whereas the transient‐relaxation window is exploited for bidirectional programming. A unipolar volatile memristor with ultralow switching voltage (e.g., <100 mV), constructed from a protein nanowire dielectric harvested fromGeobacter sulfurreducens, is specifically employed as the example switch to highlight the advantages and scalability in the strategy for array integration. 

Free Electricity from Thin Air-Is It Really Possible Anywhere, Anytime? 

Electrically conductive, genetically tunable, pilin-based protein nanowires (ePNs) expressed in Escherichia coli grown on the biodiesel byproduct glycerol are a sustainable electronic material. They were previously shown to effectively function as sensing components for volatile analytes when deployed as thin films in electronic devices. However, thin-film devices are not suitable for analyzing components dissolved in water. To evaluate the possibility of fabricating a water-stable ePN matrix, ePNs purified from cells were mixed with polyvinyl butyral (PVB) to produce a transparent, electrically conductive, water-stable composite. ePN/PVB composite conductivity was tuned by changing the concentration of ePNs in the composite or genetically tailoring ePNs for different conductivities. Devices with an ePN/PVB sensing component rapidly responded in a linear fashion to changes in concentrations of dissolved ammonia or acetate. Genetically modifying nanowires to display an analyte-binding peptide on the ePN outer surface that was specific for ammonia or acetate increased sensing sensitivity and specificity. Composites comprised of whole cells of E. coli expressing ePNs and PVB were also electrically conductive. They functioned as sensing components whose sensitivity could also be tuned with the expression of ePNs displaying specific analyte-binding peptides. This approach avoids the laborious and time-consuming purification of protein nanowires from cells. The simplicity of sustainably fabricating an electronic sensing component with ePN-expressing E. coli mixed with a polymer, coupled with the potential of exquisitely tuning sensing specificity with facile ‘plug and play’ nanowire design, demonstrates the possibility of simply and inexpensively producing sensing devices for detecting a broad range of analytes. 

Memristors are promising candidates for constructing neural networks. However, their dissimilar working mechanism to that of the addressing transistors can result in a scaling mismatch, which may hinder efficient integration. Here, we demonstrate two-terminal MoS2 memristors that work with a charge-based mechanism similar to that in transistors, which enables the homogeneous integration with MoS2 transistors to realize one-transistor-one-memristor addressable cells for assembling programmable network. The homogenously integrated cells are implemented in a 2×2 network array to demonstrate the enabled addressability and programmability. The potential for assembling scalable network is evaluated in a simulated neural network using obtained realistic device parameters, which achieves over 91% pattern recognition accuracy. This study also reveals a generic mechanism and strategy that can be applied to other semiconducting devices for the engineering and homogeneous integration of memristive systems. 

Nanowires have substantial potential as the sensor component in electronic sensing devices. However, surface functionalization of traditional nanowire and nanotube materials with short peptides that increase sensor selectivity and sensitivity requires complex chemistries with toxic reagents. In contrast, microorganisms can assemble pilin monomers into protein nanowires with intrinsic conductivity from renewable feedstocks, yielding an electronic material that is robust and stable in applications, but also biodegradable. Here we report that the sensitivity and selectivity of protein nanowire-based sensors can be modified with a simple plug and play genetic approach in which a short peptide sequence, designed to bind the analyte of interest, is incorporated into the pilin protein that is microbially assembled into nanowires. We employed a scalable Escherichia coli chassis to fabricate protein nanowires that displayed either a peptide previously demonstrated to effectively bind ammonia, or a peptide known to bind acetic acid. Sensors comprised of thin films of the nanowires amended with the ammonia-specific peptide had a ca. 100-fold greater response to ammonia than sensors made with unmodified protein nanowires. Protein nanowires with the peptide that binds acetic acid yielded a 4-fold higher response than nanowires without the peptide. The protein nanowire-based sensors had greater responses than previously reported sensors fabricated with other nanomaterials. The results demonstrate that protein nanowires with enhanced sensor response for analytes of interest can be fabricated with a flexible genetic strategy that sustainably eliminates the energy, environmental, and health concerns associated with other common nanomaterials. 

Neuromorphic systems built from memristors that emulate bioelectrical information processing in a brain may overcome limits in traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50-120 mV at least 10-time lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude thus can advance neuromorphic engineering and bio-emulated integration. This review aims to provide a timely update on the effort and progress in this burgeoning direction, covering aspects in device material composition, performance, working mechanism, and potential application.