Complementary metal–oxide–semiconductor (CMOS)-based neural architectures and memristive devices containing many artificial synapses are promising technologies that are being developed for pattern recognition and machine learning. However, the volatility and design complexity of traditional CMOS architectures, and the trade-off between the operating time and power consumption of conventional memristive devices, have tended to impede the path to achieve the interconnectivity/compactness and information density of the brain using either approach. Here, by developing a nanoscale deposit-only-metal-electrode-fabrication-based uniform-partial-state-transition-facilitated approach, we demonstrate a fast artificial synapse with a Rapid-operating-time, Intermediate-bias-range, Multiple-states, and Several-synaptic-functions (RIMS) synapse, implemented using deposit-only, nanopillar-based Ge2Sb2Te5-type memristive devices. A previously unconsidered, fast, paired-pulse facilitation/depression using ∼50 ns spikes with an ∼1 µs inter-spike interval within an ∼1 V range and with a low-energy consumption of ∼1.8 pJ per paired-spike as well as a previously inaccessible multi-state, rapid long-term potentiation/depression with ∼15 distinct states using ∼50 ns spikes within a 0.7/1.4 V range was achieved. Fast spike-timing-dependent plasticity using ∼50 ns spikes with an ∼1 µs inter-spike interval within a 1.3 V range was also achieved. Electro-thermal simulations reveal a uniform-partial-state-transition-facilitated variation in conductance states. This artificial synapse, equipped with a nanoscale deposit-only-metal-electrode-fabrication-based uniform-partial-state-transition-facilitated framework, shows the potential for a substantial overall performance improvement in artificial-intelligence tasks.

A direct current (DC) resistance sensor based on two-dimensional (2D) molybdenum disulfide (MoS2) was developed to enable cancer cell-specific detection via micro-changes in the cancer cell membrane.

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Long-term nondestructive monitoring of cells is of significant importance for understanding cell proliferation, cell signaling, cell death, and other processes. However, traditional monitoring methods are limited to a certain range of testing conditions and may reduce cell viability. Here, we present a microgap, multishot electroporation (M2E) system for monitoring cell recovery for up to ∼2 h using ∼5 V pulses and with excellent cell viability using a medium cell population. Electric field simulations reveal the bias-voltage- and gap-size-dependent electric field intensities in the M2E system. In addition to excellent transparency with low cell toxicity, the M2E system does not require specialized components, expensive materials, complicated fabrication processes, or cell manipulations; it just consists of a micrometer-sized pattern and a low-voltage square-wave generator. Ultimately, the M2E system can offer a long-term and nontoxic method of cell monitoring.

There is an ever-increasing demand for next-generation devices that do not require passwords and are impervious to cloning. For traditional hardware security solutions in edge computing devices, inherent limitations are addressed by physical unclonable functions (PUF). However, realizing efficient roots of trust for resource constrained hardware remains extremely challenging, despite excellent demonstrations with conventional silicon circuits and archetypal oxide memristor-based crossbars. An attractive, down-scalable approach to design efficient cryptographic hardware is to harness memristive materials with a large-degree-of-randomness in materials state variations, but this strategy is still not well understood. Here, the utilization of high-degree-of-randomness amorphous (A) state variations associated with different operating conditions via thermal fluctuation effects is demonstrated, as well as an integrated framework for in memory computing and next generation security primitives, viz.