While fast-switching rewritable nonvolatile memory units based on phase-change materials (PCMs) are already in production at major technology companies such as Intel (16–64 GB chips are currently available), an in-depth understanding of the physical factors that determine their success is still lacking. Recently, we have argued for a liquid-phase metal-to-semiconductor transition (M-SC), located not far below the melting point, Tm, as essential. The M-SC is itself a consequence of atomic rearrangements that are involved in a fragile-to-strong viscosity transition that controls both the speed of crystallization and the stabilization of the semiconducting state. Here, we review past work and introduce a new parameter, the “metallicity” (inverse of the average Pauling electronegativity of a multicomponent alloy). When Tm-scaled temperatures of known M-SCs of Group IV, V, and VI alloys are plotted against their metallicities, the curvilinear plot leads directly to the composition zone of all known PCMs and the temperature interval below Tm, where the transition should occur. The metallicity concept could provide guidance for tailoring PCMs.

Driven by the rapid rise of silicon photonics, optical signaling is moving from the realm of long-distance communications to chip-to-chip, and even on-chip domains. If on-chip signaling becomes optical, we should consider what more we might do with light than just communicate. We might, for example, set goals for the storing and processing of information directly in the optical domain. Doing this might enable us to supplement, or even surpass, the performance of electronic processors, by exploiting the ultrahigh bandwidth and wavelength division multiplexing capabilities offered by optics. In this article, we show how, by using an integrated photonics platform that embeds chalcogenide phase-change materials into standard silicon photonics circuits, we can achieve some of these goals. Specifically, we show that a phase-change integrated photonics platform can deliver binary and multilevel memory, arithmetic and logic processing, as well as synaptic and neuronal mimics for use in neuromorphic, or brain-like, computing—all working directly in the optical domain.

The cycling endurance of phase-change memory is one of the last hurdles to overcome to enable its adoption in the larger market for persistent memory products. Phase-change memory cycling endurance failures, whether they are stuck-SET (caused by elemental segregation) or stuck-RESET (caused by void formation), are caused by atomic migration. Various driving forces responsible for the atomic migration have been identified, such as hole-wind force, electrostatic force, and crystallization-induced segregation. We introduce several strategies to improve cycling endurance based on an understanding of driving forces and interactions among them. Utilizing some of these endurance-improving techniques, record-high phase-change memory cycling endurance at around 1012 cycles has been recently reported using a confined phase-change memory cell with a metallic liner.

The exploitation of phase-change materials (PCMs) in diverse technological applications can be greatly aided by a better understanding of the microscopic origins of their functional properties. Over the last decade, simulations based on electronic-structure calculations within density functional theory (DFT) have provided useful insights into the properties of PCMs. However, large simulation cells and long simulation times beyond the reach of DFT simulations are needed to address several key issues of relevance for the performance of devices. One way to overcome the limitations of DFT methods is to use machine learning (ML) techniques to build interatomic potentials for fast molecular dynamics simulations that still retain a quasi-ab initio accuracy. Here, we review the insights gained on the functional properties of the prototypical PCM GeTe by harnessing such interatomic potentials. Applications and future challenges of the ML techniques in the study of PCMs are also outlined.

A simple and facile stereolithography 3D printing technique was utilized to fabricate piezoelectric photopolymer-based polyvinylidene fluoride (PVDF) blends. Different process variables, such as solvent (N,N-dimethylformamide, DMF) to PVDF ratio and PVDF solution to photopolymer resin (PR) ratio, were engineered to enhance the dispersion of the PVDF into the PR so as to achieve the maximum piezoelectric coupling coefficient. Our results demonstrate that a ratio of 1:10 (PVDF:DMF) and 2 wt%-PVDF/PR was optimal for the best dissolution of the PVDF, 3D printability, and piezoelectric properties. Under these conditions, the blend generated ±0.121 nA under 80 N dynamic loading excitation. We believe that the findings of this work would promote many further studies on the mass production of flexible piezoelectric polymer blends with higher quality finished surface and design flexibility.

Enthalpy increments, $\Delta _{298}^T{H^0}$, for highly nonstoichiometric SrFeO3−δ (δ = 0.18–0.41) were obtained between 373 and 1273 K in air using drop calorimetry. The analysis of the $\Delta _{298}^T{H^0}\left( T \right)$ dependence at lower temperatures allowed evaluating the enthalpy of tetragonal to cubic ${{I4} / {mmm}} \,{\tf="TeX CM Bold Maths Symbols"\char33}\, Pm\bar{3}m$ phase transition at 560 K, 1.57 kJ/mol, and the Maier–Kelley function for $\Delta _{298}^T{H^0}\left( T \right)$ of tetragonal SrFeO3−δ (space group ${{I4} / {mmm}}$). Combined investigation of oxygen nonstoichiometry $\bolddelta \left( T \right)$ dependence, measured by thermogravimetry, and higher-temperature $\Delta _{298}^T{H^0}\left( T \right)$ of cubic SrFeO3−δ (space group $Pm\bar{3}m$) yielded the temperature-dependent reduction (oxygen release) enthalpy, $\Delta H_{{\rm{red}}}^{\rm{0}}$. Calorimetrically-determined $\Delta H_{{\rm{red}}}^{\rm{0}}$ of SrFeO3−δ increases from 65 ± 7 kJ/mol O at 873–973 K to 84 ± 7 kJ/mol O at 1073–1273 K, which may indicate that the short-range vacancy ordering in SrFeO3−δ is hampered at higher temperatures.

Electric cell–substrate impedance sensing is widely used to study cell behavior such as adhesion, migration, and cell toxicity. However, a simultaneous optical imaging of cells is limited by inefficient transmission of visible light through the gold electrodes. To overcome this limitation, we fabricated carbon nanotube (CNT) electrodes with high electrical conductivity as well as optical transmittance. The impedimetric monitoring of cell proliferation and migration by gold and CNT electrodes were compared and analyzed. Taking advantage of the optical transparency of CNTs, we demonstrated a simultaneous electronic and optical monitoring of MCF7 cells, with acquisition of high-resolution images.

Wire-shaped supercapacitors (WSSCs) hold great promise in portable and wearable electronics. Herein, a novel kind of high-performance coaxial WSSCs has been demonstrated and realized by scrolling porous carbon dodecahedrons/Al foil film electrode on vertical FeOOH nanosheets wrapping carbon fiber tows (FeOOH NSs/CFTs) yarn electrode. Remarkably, ionogel is utilized as solid-state electrolyte and exhibits a high thermal/electrochemical stability, which effectively ensures the great reliability and high operating voltage of coaxial WSSCs. Benefiting from the intriguing configuration, the coaxial WSSCs with superior flexibility act as efficient energy storage devices and exhibit low resistance, high volumetric energy density (3.2 mW h/cm3), and strong durability (82% after 10,000 cycles). Importantly, the coaxial WSSCs can be effectively recharged by harvesting sustainable wind source and repeatedly supply power to the lamp without a decline of electrochemical performance. Considering the facile fabrication technology with an outstanding performance, this work has paved the way for the integration of sustainable energy harvesting and wearable energy storage units.

Bamboo is a natural composite and one of the most efficient structures in nature because of the relationship of mechanical properties with its microstructural features. This research presents the 3D characterization of the reinforcement bundles of a branching nodal region of bamboo, through high-resolution X-ray microtomography (µCT). µCT was used to characterize a sample regarding the volume, relative density, and porosity of parenchyma and sclerenchyma tissues, and the resulting data were used to estimate their constitutive properties. A nonlinear finite element analysis (FEA) was performed based on a discretized model of the µCT to the limiting compressive load. Secondary bundles presented an interweaved arrangement into the primary vascular elements that distribute axial compressive stresses into new branches. Our findings suggest that the foam-like behavior of the parenchyma, the sclerenchyma thickening above the nodal zone, and the nodal vascular branching are ways for bamboo to protect important tissues from mechanical stress by allocating axial loads. In addition, such mechanism could be applied in the design of biomimetic structures with selective load-bearing capabilities.