Synergistic effects of mixing and strain in high entropy spinel oxides for oxygen evolution reaction.

Developing stable and efficient electrocatalysts is vital for boosting oxygen evolution reaction (OER) rates in sustainable hydrogen production. High-entropy oxides (HEOs) consist of five or more metal cations, providing opportunities to tune their catalytic properties toward high OER efficiency. This work combines theoretical and experimental studies to scrutinize the OER activity and stability for spinel-type HEOs. Density functional theory confirms that randomly mixed metal sites show thermodynamic stability, with intermediate adsorption energies displaying wider distributions due to mixing-induced equatorial strain in active metal-oxygen bonds. The rapid sol-flame method is employed to synthesize HEO, comprising five 3d-transition metal cations, which exhibits superior OER activity and durability under alkaline conditions, outperforming lower-entropy oxides, even with partial surface oxidations. The study highlights that the enhanced activity of HEO is primarily attributed to the mixing of multiple elements, leading to strain effects near the active site, as well as surface composition and coverage.

Plasmonic sensors based on graphene and graphene hybrid materials.

The past decade has witnessed a rapid growth of graphene plasmonics and their applications in different fields. Compared with conventional plasmonic materials, graphene enables highly confined plasmons with much longer lifetimes. Moreover, graphene plasmons work in an extended wavelength range, i.e., mid-infrared and terahertz regime, overlapping with the fingerprints of most organic and biomolecules, and have broadened their applications towards plasmonic biological and chemical sensors. In this review, we discuss intrinsic plasmonic properties of graphene and strategies both for tuning graphene plasmons as well as achieving higher performance by integrating graphene with plasmonic nanostructures. Next, we survey applications of graphene and graphene-hybrid materials in biosensors, chemical sensors, optical sensors, and sensors in other fields. Lastly, we conclude this review by providing a brief outlook and challenges of the field. Through this review, we aim to provide an overall picture of graphene plasmonic sensing and to suggest future trends of development of graphene plasmonics.

High thermoelectric figure of merit of porous Si nanowires from 300 to 700 K.

Thermoelectrics operating at high temperature can cost-effectively convert waste heat and compete with other zero-carbon technologies. Among different high-temperature thermoelectrics materials, silicon nanowires possess the combined attributes of cost effectiveness and mature manufacturing infrastructures. Despite significant breakthroughs in silicon nanowires based thermoelectrics for waste heat conversion, the figure of merit (ZT) or operating temperature has remained low. Here, we report the synthesis of large-area, wafer-scale arrays of porous silicon nanowires with ultra-thin Si crystallite size of ~4 nm. Concurrent measurements of thermal conductivity (κ), electrical conductivity (σ), and Seebeck coefficient (S) on the same nanowire show a ZT of 0.71 at 700 K, which is more than ~18 times higher than bulk Si. This ZT value is more than two times higher than any nanostructured Si-based thermoelectrics reported in the literature at 700 K. Experimental data and theoretical modeling demonstrate that this work has the potential to achieve a ZT of ~1 at 1000 K.

Large scale self-assembly of plasmonic nanoparticles on deformed graphene templates.

Hierarchical heterostructures of two-dimensional (2D) nanomaterials are versatile platforms for nanoscale optoelectronics. Further coupling of these 2D materials with plasmonic nanostructures, especially in non-close-packed morphologies, imparts new metastructural properties such as increased photosensitivity as well as spectral selectivity and range. However, the integration of plasmonic nanoparticles with 2D materials has largely been limited to lithographic patterning and/or undefined deposition of metallic structures. Here we show that colloidally synthesized zero-dimensional (0D) gold nanoparticles of various sizes can be deterministically self-assembled in highly-ordered, anisotropic, non-close-packed, multi-scale morphologies with templates designed from instability-driven, deformed 2D nanomaterials. The anisotropic plasmonic coupling of the particle arrays exhibits emergent polarization-dependent absorbance in the visible to near-IR regions. Additionally, controllable metasurface arrays of nanoparticles by functionalization with varying polymer brushes modulate the plasmonic coupling between polarization dependent and independent assemblies. This self-assembly method shows potential for bottom-up nanomanufacturing of diverse optoelectronic components and can potentially be adapted to a wide array of nanoscale 0D, 1D, and 2D materials.

Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system.

Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips (i.e., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS2-organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.

Ultrasensitive detection of nucleic acids using deformed graphene channel field effect biosensors.

Field-effect transistor (FET)-based biosensors allow label-free detection of biomolecules by measuring their intrinsic charges. The detection limit of these sensors is determined by the Debye screening of the charges from counter ions in solutions. Here, we use FETs with a deformed monolayer graphene channel for the detection of nucleic acids. These devices with even millimeter scale channels show an ultra-high sensitivity detection in buffer and human serum sample down to 600 zM and 20 aM, respectively, which are ∼18 and ∼600 nucleic acid molecules. Computational simulations reveal that the nanoscale deformations can form 'electrical hot spots' in the sensing channel which reduce the charge screening at the concave regions. Moreover, the deformed graphene could exhibit a band-gap, allowing an exponential change in the source-drain current from small numbers of charges. Collectively, these phenomena allow for ultrasensitive electronic biomolecular detection in millimeter scale structures.

Uniaxially crumpled graphene as a platform for guided myotube formation.

Graphene, owing to its inherent chemical inertness, biocompatibility, and mechanical flexibility, has great potential in guiding cell behaviors such as adhesion and differentiation. However, due to the two-dimensional (2D) nature of graphene, the microfabrication of graphene into micro/nanoscale patterns has been widely adopted for guiding cellular assembly. In this study, we report crumpled graphene, i.e., monolithically defined graphene with a nanoscale wavy surface texture, as a tissue engineering platform that can efficiently promote aligned C2C12 mouse myoblast cell differentiation. We imparted out-of-plane, nanoscale crumpled morphologies to flat graphene via compressive strain-induced deformation. When C2C12 mouse myoblast cells were seeded on the uniaxially crumpled graphene, not only were the alignment and elongation promoted at a single-cell level but also the differentiation and maturation of myotubes were enhanced compared to that on flat graphene. These results demonstrate the utility of the crumpled graphene platform for tissue engineering and regenerative medicine for skeletal muscle tissues.

Photonic crystallization of two-dimensional MoS2 for stretchable photodetectors.

Low temperature synthesis of high quality two-dimensional (2D) materials directly on flexible substrates remains a fundamental limitation towards scalable realization of robust flexible electronics possessing the unique physical properties of atomically thin structures. Herein, we describe room temperature sputtering of uniform, stoichiometric amorphous MoS2 and subsequent large area (>6.25 cm2) photonic crystallization of 5 nm 2H-MoS2 films in air to enable direct, scalable fabrication of ultrathin 2D photodetectors on stretchable polydimethylsiloxane (PDMS) substrates. The lateral photodetector devices demonstrate an average responsivity of 2.52 µW A-1 and a minimum response time of 120 ms under 515.6 nm illumination. Additionally, the surface wrinkled, or buckled, PDMS substrate with conformal MoS2 retained the photoconductive behavior at tensile strains as high as 5.72% and over 1000 stretching cycles. The results indicate that the photonic crystallization method provides a significant advancement in incorporating high quality semiconducting 2D materials applied directly on polymer substrates for wearable and flexible electronic systems.

Ultraviolet to Mid-Infrared Emissivity Control by Mechanically Reconfigurable Graphene.

Spectral emissivity control is critical for optical and thermal management in the ambient environment because solar irradiance and atmospheric transmissions occur at distinct wavelength regions. For instance, selective emitters with low emissivity in the solar spectrum but high emissivity in the mid-infrared can lead to significant radiative cooling. Ambient variations require not only spectral control but also a mechanism to adjust the emissivity. However, most selective emitters are fixed to specific wavelength ranges and lack dynamic control mechanisms. Here we show ultraviolet to mid-infrared emissivity control by mechanically reconfiguring graphene, in which stretching and releasing induce dynamic topographic changes. We fabricate crumpled graphene with pitches ranging from 40 nm to 10 µm using deformable substrates. Our measurements and computations show that 140 nm-pitch crumpled graphene offers ultraviolet emissivity control in 200-300 nm wavelengths whereas 10 µm-pitch crumpled graphene offers mid-infrared emissivity control in 7-19 µm wavelengths. Significant emissivity changes arise from interference induced by the periodic topography and selective transmissivity reductions. Dynamic stretching and releasing of 140 nm and 10 µm pitch crumpled graphene show reversible emissivity peak changes at 250 nm and at 9.9 µm wavelengths, respectively. This work demonstrates the unique potential of crumpled graphene as a reconfigurable optical and thermal management platform.