Quasi-Copper-Mers Enable High-Performance Catalysis for CO Reduction.

As the atmospheric carbon dioxide (CO ) level keeps hitting the new record, humanity is facing an ever-daunting challenge to efficiently mitigate CO from the atmosphere. Though electrochemical CO reduction presents a promising pathway to convert CO to valuable fuels and chemicals, the general lack of suitable electrocatalysts with high activity and selectivity severely constrains this approach. Herein, a novel class of electrocatalysts is investigated, the quasi-copper-mers, in which the CuN rather than Cu atom itself serve as the basic building block.

Integration of Single-Atom Catalyst with Z-Scheme Heterojunction for Cascade Charge Transfer Enabling Highly Efficient Piezo-Photocatalysis.

Piezo-assisted photocatalysis (namely, piezo-photocatalysis), which utilizes mechanical energy to modulate spatial and energy distribution of photogenerated charge carriers, presents a promising strategy for molecule activation and reactive oxygen species (ROS) generation toward applications such as environmental remediation. However, similarly to photocatalysis, piezo-photocatalysis also suffers from inferior charge separation and utilization efficiency. Herein, a Z-scheme heterojunction composed of single Ag atoms-anchored polymeric carbon nitride (Ag-PCN) and SnO is developed for efficient charge carrier transfer/separation both within the catalyst and between the catalyst and surface oxygen molecules (O ).

Explainable artificial intelligence in ophthalmology.

Purpose Of Review: Despite the growing scope of artificial intelligence (AI) and deep learning (DL) applications in the field of ophthalmology, most have yet to reach clinical adoption. Beyond model performance metrics, there has been an increasing emphasis on the need for explainability of proposed DL models.

Recent Findings: Several explainable AI (XAI) methods have been proposed, and increasingly applied in ophthalmological DL applications, predominantly in medical imaging analysis tasks.

Acidic Media Impedes Tandem Catalysis Reaction Pathways in Electrochemical CO Reduction.

Electrochemical CO reduction (CO R) in acidic media with Cu-based catalysts tends to suffer from lowered selectivity towards multicarbon products. This could in principle be mitigated using tandem catalysis, whereby the *CO coverage on Cu is increased by introducing a CO generating catalyst (e.g.

Crystalline lens nuclear age prediction as a new biomarker of nucleus degeneration.

Background: The crystalline lens is a transparent structure of the eye to focus light on the retina. It becomes muddy, hard and dense with increasing age, which makes the crystalline lens gradually lose its function. We aim to develop a nuclear age predictor to reflect the degeneration of the crystalline lens nucleus.

A voxel-based morphometry study on gray matter correlates of need for cognition and exploratory information seeking.

Background: Need for cognition (NFC) represents interindividual differences in tendencies to engage and enjoy cognitive endeavors. Exploratory information seeking (EIS) refers to individual tendencies to attain cognitive stimulation through acquiring information related to consumer products or services out of curiosity.

Methods: The current study aims to provide an in-depth investigation of the relationship between NFC and EIS and extend this relation to determine neuroanatomical correlates of NFC and EIS.

Fluctuotaxis: Nanoscale directional motion away from regions of fluctuation.

Regulating the motion of nanoscale objects on a solid surface is vital for a broad range of technologies such as nanotechnology, biotechnology, and mechanotechnology. In spite of impressive advances achieved in the field, there is still a lack of a robust mechanism which can operate under a wide range of situations and in a controllable manner. Here, we report a mechanism capable of controllably driving directed motion of any nanoobjects (e.

Use of artificial intelligence in forecasting glaucoma progression.

Artificial intelligence (AI) has been widely used in ophthalmology for disease detection and monitoring progression. For glaucoma research, AI has been used to understand progression patterns and forecast disease trajectory based on analysis of clinical and imaging data. Techniques such as machine learning, natural language processing, and deep learning have been employed for this purpose.

Accelerated Surface Reconstruction through Regulating the Solid-Liquid Interface by Oxyanions in Perovskite Electrocatalysts for Enhanced Oxygen Evolution.

A comprehensive understanding of surface reconstruction was critical to developing high performance lattice oxygen oxidation mechanism (LOM) based perovskite electrocatalysts. Traditionally, the primary determining factor of the surface reconstruction process was believed to be the oxygen vacancy formation energy. Hence, most previous studies focused on optimizing composition to reduce the oxygen vacancy formation energy, which in turn facilitated the surface reconstruction process.

Identify hidden spreaders of pandemic over contact tracing networks.

The COVID-19 infection cases have surged globally, causing devastations to both the society and economy. A key factor contributing to the sustained spreading is the presence of a large number of asymptomatic or hidden spreaders, who mix among the susceptible population without being detected or quarantined. Due to the continuous emergence of new virus variants, even if vaccines have been widely used, the detection of asymptomatic infected persons is still important in the epidemic control.

Synergistic Adsorption and In Situ Catalytic Conversion of SO by Transformed Bimetal-Phenolic Functionalized Biomass.

SO removal is critical to flue gas purification. However, based on performance and cost, materials under development are hardly adequate substitutes for active carbon-based materials. Here, we engineered biomass-derived nanostructured carbon nanofibers integrated with highly dispersed bimetallic Ti/CoO nanoparticles through the thermal transition of metal-phenolic functionalized industrial leather wastes for synergistic SO adsorption and in situ catalytic conversion.

A Thermochromic, Viscoelastic Nacre-like Nanocomposite for the Smart Thermal Management of Planar Electronics.

Cutting-edge heat spreaders for soft and planar electronics require not only high thermal conductivity and a certain degree of flexibility but also remarkable self-adhesion without thermal interface materials, elasticity, arbitrary elongation along with soft devices, and smart properties involving thermal self-healing, thermochromism and so on. Nacre-like composites with excellent in-plane heat dissipation are ideal as heat spreaders for thin and planar electronics. However, the intrinsically poor viscoelasticity, i.

Enhancing LED spectral output with perylene dye-based remote phosphor.

LEDs offer a wide range of spectral output with high efficiencies. However, the efficiencies of solid-state LEDs with green and yellow wavelengths are rather low due to the lack of suitable direct bandgap materials. Here, we introduce and develop perylene-enhanced green LEDs that produce a higher wall-plug efficiency of 48% compared to 38% for a solid-state green LED.

Quantum Uncertainty Principles for Measurements with Interventions.

Heisenberg's uncertainty principle implies fundamental constraints on what properties of a quantum system we can simultaneously learn. However, it typically assumes that we probe these properties via measurements at a single point in time. In contrast, inferring causal dependencies in complex processes often requires interactive experimentation-multiple rounds of interventions where we adaptively probe the process with different inputs to observe how they affect outputs.

Convex Optimization for Nonequilibrium Steady States on a Hybrid Quantum Processor.

Finding the transient and steady state properties of open quantum systems is a central problem in various fields of quantum technologies. Here, we present a quantum-assisted algorithm to determine the steady states of open system dynamics. By reformulating the problem of finding the fixed point of Lindblad dynamics as a feasibility semidefinite program, we bypass several well-known issues with variational quantum approaches to solving for steady states.

Size-dependent bending of a rectangular polymer film.

Inhomogeneous swelling of polymer films in liquid environments may find applications in soft actuators and sensors. Among them, fluoroelastomer based films bend up spontaneously once they are placed on an acetone-soaked filter paper. The stretchability and dielectric properties of a fluoroelastomer is attractive in the fields of soft actuators and sensors, making in-depth studies on and understanding of fluoroelastomer bending behaviors important.

Integration of hybrid and self-correction method improves the quality of long-read sequencing data.

Third-generation sequencing (TGS) technologies have revolutionized genome science in the past decade. However, the long-read data produced by TGS platforms suffer from a much higher error rate than that of the previous technologies, thus complicating the downstream analysis. Several error correction tools for long-read data have been developed; these tools can be categorized into hybrid and self-correction tools.

Chiral Phosphoric Acid Catalyzed Asymmetric Hydrolysis of Biaryl Oxazepines for the Synthesis of Axially Chiral Biaryl Amino Phenol Derivatives.

The development of catalytic asymmetric reaction with water as the reactant is challenging due to the reactivity- and stereoselectivity-control issues resulted from the low nucleophilicity and the small size of water. We disclose herein a chiral phosphoric acid (CPA) catalyzed atroposelective ring-opening reaction of biaryl oxazepines with water. A series of biaryl oxazepines undergo the CPA catalyzed asymmetric hydrolysis in a highly enantioselective manner.

Deformation Coupled Moiré Mapping of Superlubricity in Graphene.

The ultralow friction of two-dimensional (2D) materials, commonly referred to as superlubricity, has been associated with Moiré superlattices (MSLs). While MSLs have been shown to play a crucial role in achieving superlubricity, the long-standing challenge of achieving superlubricity in engineering has been attributed to surface roughness, which tends to destroy MSLs. Here, we show via molecular dynamics simulations that MSLs alone are not capable of capturing the friction behavior of a multilayer-graphene-coated substrate where similar MSLs persist in spite of significant changes in friction as the graphene coating thickness increases.

Transformers in medical imaging: A survey.

Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of convolutional neural networks (CNNs) as de facto operators. Capitalizing on these advances in computer vision, the medical imaging field has also witnessed growing interest for Transformers that can capture global context compared to CNNs with local receptive fields. Inspired from this transition, in this survey, we attempt to provide a comprehensive review of the applications of Transformers in medical imaging covering various aspects, ranging from recently proposed architectural designs to unsolved issues.

Selective and Stable CO Electroreduction to CH via Electronic Metal-Support Interaction upon Decomposition/Redeposition of MOF.

The CO electroreduction to fuels is a feasible approach to provide renewable energy sources. Therefore, it is necessary to conduct experimental and theoretical investigations on various catalyst design strategies, such as electronic metal-support interaction, to improve the catalytic selectivity. Here a solvent-free synthesis method is reported to prepare a copper (Cu)-based metal-organic framework (MOF) as the precursor.

Achieving Boron-Carbon-Nitrogen Heterostructures by Collision Fusion of Carbon Nanotubes and Boron Nitride Nanotubes.

Heterostructures may exhibit completely new physical properties that may be otherwise absent in their individual component materials. However, how to precisely grow or assemble desired complex heterostructures is still a significant challenge. In this work, the collision dynamics of a carbon nanotube and a boron nitride nanotube under different collision modes were investigated using the self-consistent-charge density-functional tight-binding molecular dynamics method.

A fluid model of pulsed direct current planar magnetron discharge.

We simulated a pulsed direct current (DC) planar magnetron discharge using fluid model, solving for species continuity, momentum, and energy transfer equations, coupled with Poisson equation and Lorentz force for electromagnetism. Based on a validated DC magnetron model, an asymmetric bipolar potential waveform is applied at the cathode at 50-200 kHz frequency and 50-80% duty cycle. Our results show that pulsing leads to increased electron density and electron temperature, but decreased deposition rate over non-pulsed DC magnetron, trends consistent with those reported by experimental studies.

Fluid-structure interaction analysis of amniotic fluid with fetus and placenta inside uterus exposed to military blasts.

Introduction: Pregnancy-related trauma is one of the leading causes of morbidity and mortality in pregnant women and fetuses. The fetal response to injury is largely dependent on the timing of fetal presentation and the underlying pathophysiology of the trauma. The optimal management of pregnant patients who have suffered an obstetric emergency depends on clinical assessment and understanding of the placental implantation process, which can be difficult to perform during an emergency.