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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Photonic neural network has been sought as an alternative solution to surpass the efficiency and speed bottlenecks of electronic neural network. Despite that the integrated Mach-Zehnder Interferometer (MZI) mesh can perform vector-matrix multiplication in photonic neural network, a programmable in-situ nonlinear activation function has not been proposed to date, suppressing further advancement of photonic neural network. Here, we demonstrate an efficient in-situ nonlinear accelerator comprising a unique solution-processed two-dimensional (2D) MoS 2 Opto-Resistive RAM Switch (ORS), which exhibits tunable nonlinear resistance switching that allow us to introduce nonlinearity to the photonic neuron which overcomes the linear voltage-power relationship of typical photonic components. Our reconfigurable scheme enables implementation of a wide variety of nonlinear responses. Furthermore, we confirm its feasibility and capability for MNIST handwritten digit recognition, achieving a high accuracy of 91.6%. Our accelerator constitutes a major step towards the realization of in-situ photonic neural network and pave the way for the integration of photonic integrated circuits (PIC)., (© 2022. The Author(s).)

Memtransistors that combine the properties of transistor and memristor hold significant promise for in-memory computing. While superior data storage capability is achieved in memtransistors through gate voltage-induced conductance modulation, the lateral device configuration would not only result in high write bias, which compromises the power efficiency, but also suffers from unsuccessful memory reset that leads to reliability concerns. To circumvent such performance limitations, an advanced physics-based model is required to uncover the dynamic resistive switching behavior and deduce the key driving parameters for the switching process. This work demonstrates a self-consistent physics-based model which incorporates the often-overlooked effects of lattice temperature, vacancy dynamics, and channel electrostatics to accurately solve the interaction between gate potential, ions, and carriers on the memristive switching mechanism. The completed model is carefully calibrated with an ambipolar WSe 2 memtransistor and hence enables the investigation of the carrier polarity effect (electrons vs holes) on vacancy transport. Nevertheless, the validity of the model can be extended to different materials by a simple material-dependent parameter modification. Building upon the existing understanding of Schottky barrier height modulation, our study reveals three key insights─leveraging threshold voltage shifts to lower write bias; optimizing lattice temperature distribution and read bias polarity to achieve successful memory state recovery; engineering contact work function to overcome the detrimental parasitic current flow in short channel ambipolar memtransistors. Therefore, understanding the significant correlation between the switching mechanisms, different material systems, and device structures allows performance optimization of operating modes and device designs for future memtransistors-based computing systems.

Realization of high-density and reliable resistive random access memories based on two-dimensional semiconductors is crucial toward their development in next-generation information storage and neuromorphic computing. Here, wafer-scale integration of solution-processed two-dimensional MoS 2 memristor arrays are reported. The MoS 2 memristors achieve excellent endurance, long memory retention, low device variations, and high analog on/off ratio with linear conductance update characteristics. The two-dimensional nanosheets appear to enable a unique way to modulate switching characteristics through the inter-flake sulfur vacancies diffusion, which can be controlled by the flake size distribution. Furthermore, the MNIST handwritten digits recognition shows that the MoS 2 memristors can operate with a high accuracy of >98.02%, which demonstrates its feasibility for future analog memory applications. Finally, a monolithic three-dimensional memory cube has been demonstrated by stacking the two-dimensional MoS 2 layers, paving the way for the implementation of two memristor into high-density neuromorphic computing system., (© 2022. The Author(s).)

The recent legalization of cannabidiol (CBD) to treat neurological conditions such as epilepsy has sparked rising interest across global pharmaceuticals and synthetic biology industries to engineer microbes for sustainable synthetic production of medicinal CBD. Since the process involves screening large amounts of samples, the main challenge is often associated with the conventional screening platform that is time consuming, and laborious with high operating costs. Here, a portable, high-throughput Aptamer-based BioSenSing System (ABS 3 ) is introduced for label-free, low-cost, fully automated, and highly accurate CBD concentrations' classification in a complex biological environment. The ABS 3 comprises an array of interdigitated microelectrode sensors, each functionalized with different engineered aptamers. To further empower the functionality of the ABS 3 , unique electrochemical features from each sensor are synergized using physics-guided multidimensional analysis. The capabilities of this ABS 3 are demonstrated by achieving excellent CBD concentrations' classification with a high prediction accuracy of 99.98% and a fast testing time of 22 µs per testing sample using the optimized random forest (RF) model. It is foreseen that this approach will be the key to the realistic transformation from fundamental research to system miniaturization for diagnostics of disease biomarkers and drug development in the field of chemical/bioanalytics., (© 2022 Wiley-VCH GmbH.)

One of the significant limitations of the pulsed laser deposition method in the mass-production-technologies of micro- and nanoelectronic and molecular device electronic fabrication is the issue of ensuring deposition of films with uniform thickness on substrates with large diameter (more than 100 mm) since the area of the laser spot (1-5 mm 2 ) on the surface of the ablated target is incommensurably smaller than the substrate area. This paper reports the methodology that allows to calculate the distribution profile of the film thickness over the surface substrate with a large diameter, taking into account the construction and technological parameters of the pulsed laser deposition equipment. Experimental verification of the proposed methodology showed that the discrepancy with the experiment does not exceed 8%. The modeling of various technological parameters influence on the thickness uniformity has been carried out. Based on the modeling results, recommendations and parameters are proposed for manufacturing uniform thickness films. The results allow for increasing the film thickness uniformity with the thickness distribution < 5% accounts for ~ 31% of 300 mm diameter substrate.

Energy conversion devices draw much attention due to their effective usage of energy and resulting decrease in CO 2 emissions, which slows down the global warming processes. Fabrication of energy conversion devices based on ferroelectric and piezoelectric lead-free films is complicated due to the difficulties associated with insufficient elaboration of growth methods. Most ferroelectric and piezoelectric materials (LiNbO 3 , BaTiO 3 , etc.) are multi-component oxides, which significantly complicates their integration with micro- and nanoelectronic technology. This paper reports the effect of the oxygen pressure on the properties of nanocrystalline lithium niobate (LiNbO 3 ) films grown by pulsed laser deposition on SiO 2 /Si structures. We theoretically investigated the mechanisms of LiNbO 3 dissociation at various oxygen pressures. The results of x-ray photoelectron spectroscopy study have shown that conditions for the formation of LiNbO 3 films are created only at an oxygen pressure of 1 × 10 -2 Torr. At low residual pressure (1 × 10 -5 Torr), a lack of oxygen in the formed films leads to the formation of niobium oxide (Nb 2 O 5 ) clusters. The presented theoretical and experimental results provide an enhanced understanding of the nanocrystalline LiNbO 3 films growth with target parameters using pulsed laser deposition for the implementation of piezoelectric and photoelectric energy converters.

3D monolithic integration of logic and memory has been the most sought after solution to surpass the Von Neumann bottleneck, for which a low-temperature processed material system becomes inevitable. Two-dimensional materials, with their excellent electrical properties and low thermal budget are potential candidates. Here, we demonstrate a low-temperature hybrid co-integration of one-transistor-one-resistor memory cell, comprising a surface functionalized 2D WSe 2 p-FET, with a solution-processed WSe 2 Resistive Random Access Memory. The employed plasma oxidation technique results in a low Schottky barrier height of 25 meV with a mobility of 230 cm 2  V -1  s -1 , leading to a 100x performance enhanced WSe 2 p-FET, while the defective WSe 2 Resistive Random Access Memory exhibits a switching energy of 2.6 pJ per bit. Furthermore, guided by our device-circuit modelling, we propose vertically stacked channel FETs for high-density sub-0.01 μm 2 memory cells, offering a new beyond-Si solution to enable 3-D embedded memories for future computing systems.