Showing papers by "Zhong Chen published in 2022"

Steering Unit Cell Dipole and Internal Electric Field by Highly Dispersed Er atoms Embedded into NiO for Efficient CO2 Photoreduction

Abstract: The weak internal electric field over antiferromagnetic materials makes it difficult to facilitate charge migration to the surface, leading to low performance for CO2 photoreduction. The asymmetry and polarization refinement structure can induce an intensive internal electric field. Herein, n‐type NiO is synthesized with highly dispersed erbium atoms doping (Er/NiO1−x) via a molten salt method to accelerate charge separation and transfer. The doping of Er atoms can distort the unit cell of NiO to alter the symmetry and enhance the polarization and internal electric field, in favor of efficient separation of charges. In addition, the highly dispersed erbium‐doped n‐type NiO can largely boost the adsorption and activation of CO2, and weaken the energy barrier for CO2 photoreduction reaction. Benefiting from the unique features, an optimal doping ratio (≈2%) with erbium atoms achieves a remarkable elevation in carrier separation efficiency and excellent CO2 photoreduction performance with a CO yield of 368 µmol g−1 h−1 in the Ru(byp)32+/ethanolamine electron‐agent generating system, which is 26.3‐fold and 3.9‐fold relative to traditional NiO and n‐type NiO, respectively. The obtained Er/NiO1−x photocatalyst and the unit cell dipole governing the internal electric field opens a new window for CO2 photoreduction in antiferromagnetic materials.

An All-In-One Multifunctional Touch Sensor with Carbon-Based Gradient Resistance Elements

Abstract: Carbon-based gradient resistance element structure is proposed for the construction of multifunctional touch sensor, which will promote wide detection and recognition range of multiple mechanical stimulations. Multifunctional touch sensor with gradient resistance element and two electrodes is demonstrated to eliminate signals crosstalk and prevent interference during position sensing for human-machine interactions. Biological sensing interface based on a deep-learning-assisted all-in-one multipoint touch sensor enables users to efficiently interact with virtual world. Human-machine interactions using deep-learning methods are important in the research of virtual reality, augmented reality, and metaverse. Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes, signal crosstalk, propagation delay, and demanding configuration requirements. Here, an all-in-one multipoint touch sensor (AIOM touch sensor) with only two electrodes is reported. The AIOM touch sensor is efficiently constructed by gradient resistance elements, which can highly adapt to diverse application-dependent configurations. Combined with deep learning method, the AIOM touch sensor can be utilized to recognize, learn, and memorize human-machine interactions. A biometric verification system is built based on the AIOM touch sensor, which achieves a high identification accuracy of over 98% and offers a promising hybrid cyber security against password leaking. Diversiform human-machine interactions, including freely playing piano music and programmatically controlling a drone, demonstrate the high stability, rapid response time, and excellent spatiotemporally dynamic resolution of the AIOM touch sensor, which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.

Fabrication of heat-treated soybean protein isolate-EGCG complex nanoparticle as a functional carrier for curcumin

Abstract: In this study, soybean protein isolate (SPI) was first heat-treated to yield modified SPI (HSPI). Then SPI- and HSPI-epigallocatechin-3-gallate (EGCG) biopolymers (SPI-E and HSPI-E) were fabricated using an alkali covalent crosslinking method and their abilities to function as novel delivery carriers to load curcumin (Cur) were investigated. The particle size of loaded-Cur SPI-E and HSPI-E complex nanoparticles (SPI-E-C and HSPI-E-C) were all reduced and the zeta-potentials were all negative. FTIR and fluorescence spectra analysis indicated the presence of hydrogen bondings, hydrophobic interactions, and electrostatic interactions were the driving force for the formation of the carrier-Cur complex. Moreover, compared with SPI-E, HSPI-E had a high loading rate of Cur, improved bioaccessibility and scavenging capacity, smaller size, thinner sheet shape morphology, and stronger binding affinity. In its protective capacity as a delivery carrier, HSPI-E significantly improved the thermal stability, acid stability and controlled release characteristics of Cur, thereby overcoming the instability of a single protein carrier and possessing superior properties. These findings indicate that the HSPI-E polymer is a favorable carrier for delivering Cur and suit for development as a delivery polymer carrier to protect hydrophobic nutraceuticals and drugs with high-loading rate-performance and health-related functions without the use of crosslinkers. • Heat-treated soybean protein isolate-epigallocatechin-3-gallate (HSPI-E) as a carrier. • HSPI-E possessed strong forces with curcumin and high loading rate. • HSPI-E exhibited excellent stability and protect capacity for curcumin. • HSPI-E biopolymer might provide novel carrier for medical materials.

Effect of cobalt phosphide (CoP) vacancies on its hydrogen evolution activity via water splitting: a theoretical study.

Abstract: Defect engineering plays an important role in improving the performance of catalysts. To clarify the roles of Co and P vacancies in CoP for water splitting, a theoretical study based on density functional theory was carried out in this paper. The geometric and electronic structures, activity and stability of the CoP (101)B surface, CoP (101)B with the Co vacancy (Covac) and the P vacancy (Pvac) are investigated. The results indicate that the CoP (101)B surface with Pvac and Covac can enhance the electron transfer to the surface. The Pvac will upward shift the Co d-band center near the vacancy site, which promotes the adsorption of H on the Co atom. As a result, the bridge Co-Co sites near the vacancy become the active sites for the hydrogen evolution reaction (HER) (ΔGH* = 0.01 eV). The loss of the Co atom also results in an upward shift of its d-band center, which will enhance the H adsorption on the adjacent Co sites. The unevenly distributed electrons due to the presence of vacancies on the surface cause spontaneous dissociation of H2O molecules. Furthermore, the thermodynamic analysis and surface energy find that the CoP (101)B and (101)B facets with Covac and Pvac present good stability. The current work has shed light onto the mechanism of water splitting on the surface of phosphide with vacancies. Our study suggests that engineering vacancies on CoP is a feasible route to improve its catalytic activity.

Molecular Levels Unveil the Membrane Fouling Mitigation Mechanism of a Superpotent N-rGO Catalytic Ozonation Membrane: Interfacial Catalytic Reaction Pathway and Induced EfOM Transformation Reactions

Abstract: This study investigated the membrane fouling self-cleaning of N-doped reduced graphene oxide (N-rGO)-tailored ceramic membrane with ozone (N-rGO-CM-O/F) at the molecular level. Density functional theoretical (DFT) revealed the principle of interfacial catalytic reaction, and the transformation of foulants was probed using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and various spectroscopic techniques. Results showed that ozone could be aggregated on the N-rGO-CM surface and formed abundant • OH. This made humic acid-like substances blocking membrane pores to be sufficiently and preferentially removed in N-rGO-CM-O/F by 18-types reactions of catalytic ozonation. Conversely, CM-O/F preferentially removed protein-like substances that formed the cake layer. Due to the stronger catalytic ozonation ability and efficient fouling mitigation behavior, N-rGO-CM-O/F showed higher water flux as 1.96 times than that of CM-O/F. Overall, this study provided molecular insight into the mechanism of membrane fouling mitigation, which will facilitate the design and application of advanced catalytic membranes. • Pyridinic N and pyrrolic N as active sites of N-rGO-CM, enhanced • OH formation. • Graphite N of N-rGO-CM as co-catalytic site for enhanced molecular ozone reaction. • N-rGO-CM with ozone enables the rapid reduction of EfOM and property change. • N-rGO-CM with ozone preferentially removes EfOM that tends to clog membrane pores. • 18 specific EfOM transformation pathways achieve mitigation of membrane fouling.

Ultrafast water–fat separation using deep learning–based single‐shot MRI

Abstract: To present a deep learning–based reconstruction method for spatiotemporally encoded single‐shot MRI to simultaneously obtain water and fat images.

AMFR drives allergic asthma development by promoting alveolar macrophage–derived GM-CSF production

Abstract: This study demonstrates that E3 ubiquitin ligase autocrine motility factor receptor (AMFR) drives lung inflammation in asthma through promoting alveolar macrophage–derived GM-CSF production, and may emerge as a new potential drug target for asthma therapy.

Carbothermal Synthesis of Nano-iron-carbon Composites for Arsenate Removal from High-arsenic Acid Wastewater

Abstract: The current carbothermal method involves impregnation and reduction of ferric salt with the problems of low product activity and high cost, limiting the large-scale production and application of nano-zero-valent iron (nZVI). In this work, the nano-iron-carbon composites (CB-nZVI) were successfully synthesized at a high efficiency, low consumption and batch production process and showed a rapid and efficient As(V) removal from high-arsenic acid wastewater (pH<2 and As(V)> 5 g/L). More than 99.77% As(V) was removed by CB-nZVI under optimum reaction conditions of pH 1.7, initial As(V) concentration 5 g/L and nZVI dosage 11 g/L at 40 ℃ with approximately 11 mg/L As(V) still remained in the filtrate. A novel continuous two-stage treatment process was proposed with only 0.12 mg/L As(V) remained in the filtrate, which met the demands specified in Emission Standard of Pollutants for the Sulfuric Acid Industry issued by Ministry of Environmental Protection of China (GB26132–2010), and solid wastes were greatly reduced at the same time. The iron species distributed on the CB-nZVI core-shell structure possessed a high chemical reduction potential gradient driving force which resulted in the adsorbed As(V) would further be reduced to As(III) and As(0) and then diffusing across the thin oxide layer, leading to accumulating or immobilizing the arsenic at the CB-nZVI. Moreover, strongly acidic condition and Fe/C micro-electrolysis could accelerate the corrosion of CB-nZVI and generate iron oxides for As(V) adsorption. These results suggested that CB-nZVI has great potential for the disposal of strongly acidic wastewater with high concentration in the smelting industry.

Flexible and Highly Conductive Textiles Induced by Click Chemistry for Sensitive Motion and Humidity Monitoring.

Abstract: To date, multifunctional sensors have aroused widespread concerns owing to their vital roles in the healthcare area. However, there are still significant challenges in the fabrication of functionalized integrated devices. In this work, hydrophobic-hydrophilic patterns are constructed on polyester-spandex-blended knitted fabric surface by the chemical click method, enabling accurate deposition of functionalized materials for sensitive and stable motion and humidity sensing. Representatively, a conductive silver nanowire (Ag NW) network was deliberately deposited on only the designated hydrophilic fabric surface to realize accurate, repeatable, and stable motion sensing. Such a Ag NWs sensor recorded a low electrical resistance (below 60 Ω), stable resistance cycling response (over 2000 cycles), and fast response time to humidity (0.46 s) during the sensing evaluation. In addition to experimental sensing, real human motions, such as mouth-opening and joint-flexing (wrist and neck), could also be detected using the same sensor. Similar promising outputs were also obtained over the humidity sensor fabricated over the same chemical click method, except the sensing material was replaced with polydopamine-modified carboxylated carbon nanotubes. The resultant sensor exhibits excellent sensitivity to not only experimentally adjusted environment humidity but also to the moisture content of breath and skin during daily activities. On top of all these, both sensors were fabricated over highly flexible fabric that offers high wearability, promising great application potential in the field of healthcare monitoring.

Single-shot T2 mapping via multi-echo-train multiple overlapping-echo detachment planar imaging and multi-task deep learning.

Abstract: BACKGROUND Quantitative magnetic resonance imaging provides robust biomarkers in clinics. Nevertheless, the lengthy scan time reduces imaging throughput and increases the susceptibility of imaging results to motion. In this context, a single-shot T2 mapping method based on multiple overlapping-echo detachment (MOLED) planar imaging was presented, but the relatively small echo time range limits its accuracy, especially in tissues with large T2 . PURPOSE In this work we proposed a novel single-shot method, Multi-Echo-Train Multiple OverLapping-Echo Detachment (METMOLED) planar imaging, to accommodate a large range of T2 quantification without additional measurements to rectify signal degeneration arisen from refocusing pulse imperfection. METHODS Multiple echo-train techniques were integrated into the MOLED sequence to capture larger TE information. Maps of T2 , B1 , and spin density were reconstructed synchronously from acquired METMOLED data via multi-task deep learning. A typical U-Net was trained with 3000/600 synthetic data with geometric/brain patterns to learn the mapping relationship between METMOLED signals and quantitative maps. The refocusing pulse imperfection was settled through the inherent information of METMOLED data and auxiliary tasks. RESULTS Experimental results on the digital brain (structural similarity (SSIM) index = 0.975/0.991/0.988 for MOLED/METMOLED-2/METMOLED-3, hyphenated number denotes the number of echo-trains), physical phantom (the slope of linear fitting with reference T2 map = 1.047/1.017/1.006 for MOLED/METMOLED-2/METMOLED-3), and human brain (Pearson's correlation coefficient (PCC) = 0.9581/0.9760/0.9900 for MOLED/METMOLED-2/METMOLED-3) demonstrated that the METMOLED improved the quantitative accuracy and the tissue details in contrast to the MOLED. These improvements were more pronounced in tissues with large T2 and in application scenarios with high temporal resolution (PCC = 0.8692/0.9465/0.9743 for MOLED/METMOLED-2/METMOLED-3). Moreover, the METMOLED could rectify the signal deviations induced by the non-ideal slice profiles of refocusing pulses without additional measurements. A preliminary measurement also demonstrated that the METMOLED is highly repeatable (mean coefficient of variation (CV) = 1.65%). CONCLUSIONS METMOLED breaks the restriction of echo-train length to TE and implements unbiased T2 estimates in an extensive range. Furthermore, it corrects the effect of refocusing pulse inaccuracy without additional measurements or signal post-processing, thus retaining its single-shot characteristic. This technique would be beneficial for accurate T2 quantification. This article is protected by copyright. All rights reserved.

Design of Hierarchical Oxide‐Carbon Nanostructures for Trifunctional Electrocatalytic Applications

Abstract: The rational design of efficient trifunctional catalysts for oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and hydrogen evolution reaction (HER) is of significant importance for metal–air batteries and electrolyzers. Herein, a hierarchical carbon architecture that comprises of 1D tubes and 2D sheets supported on Ni–Co oxide is synthesized. The 1D–2D carbon nanostructures further support homogeneously dispersed Co/Ni–Nx centers, NiCo and its oxide nanoparticles that are beneficial for ORR, HER, and OER, respectively. The hierarchical nanostructures offer highly exposed surface that enables the maximum utility of active sites for different reactions and also provide a single platform that can be used as OER–ORR and OER‐HER bifunctional catalyst for metal– air batteries and electrolyzers, respectively. The catalyst displays a low ΔE (EJ(OER) = 10 − E½(ORR)) of 0.846 V for bifunctional OER–ORR and low potential of 1.54 V at 10 mA cm−2 for overall water splitting with appreciable durability for 40 h. Overall, the nanostructures exhibit remarkable activity and are durable for OER, ORR, and HER. Moreover, the study offers a pathway to expand the functionality of the non‐noble electrocatalyst and simultaneously offers a platform to prove that preferential active sites exist for different reactions.

Adaptable Singlet-Filtered Nuclear Magnetic Resonance Spectroscopy for Chemical and Biological Applications.

Abstract: Proton nuclear magnetic resonance (1H NMR) spectroscopy presents a powerful detection tool for studying chemical compositions and molecular structures. In practical chemical and biological applications, 1H NMR experiments are generally confronted with the challenge of spectral congestions caused by abundant observable components and intrinsic limitations of a narrow frequency distribution range and extensive J coupling splitting. Herein, a one-dimensional (1D) general NMR method is proposed to individually extract the signals of targeted proton groups based on their endogenous spin singlet states excited from J coupling interactions, and it is suitable for high-resolution detections on complex chemical and biological samples. The applicability of the proposed method is demonstrated by experimental observations on chemical solutions containing different coupled components, intact grape tissues subjected to crowded resonances, and in vitro pig brain with various metabolites. Moreover, the proposed method is further exploited for magnetic resonance spectroscopy applications by directly combining the spatial localization module, showing promise in in vivo biological metabolite studies.