Reverse Separation of Carbon Dioxide and Acetylene in Two Isostructural Copper Pyridine-Carboxylate Frameworks.

Separating acetylene from carbon dioxide is important but highly challenging due to their similar molecular shapes and physical properties. Adsorptive separation of carbon dioxide from acetylene can directly produce pure acetylene but is hardly realized because of relatively polarizable acetylene binds more strongly. Here, we reverse the CO2 and C2H2 separation by adjusting the pore structures in two isoreticular ultramicroporous metal-organic frameworks (MOFs). Under ambient conditions, copper isonicotinate (Cu(ina)2), with relatively large pore channels shows C2H2-selective adsorption with a C2H2/CO2 selectivity of 3.4, whereas its smaller-pore analogue, copper quinoline-5-carboxylate (Cu(Qc)2) shows an inverse CO2/C2H2 selectivity of 5.6. Cu(Qc)2 shows compact pore space that well matches the optimal orientation of CO2 but is not compatible for C2H2. Neutron powder diffraction experiments confirmed that CO2 molecules adopt preferential orientation along the pore channels during adsorption binding, whereas C2H2 molecules bind in an opposite fashion with distorted configurations due to their opposite quadrupole moments. Dynamic breakthrough experiments have validated the separation performance of Cu(Qc)2 for CO2/C2H2 separation.

Dielectrophoresis: Measurement technologies and auxiliary sensing applications.

Dielectrophoresis (DEP), which arises from the interaction between dielectric particles and an aqueous solution in a nonuniform electric field, contributes to the manipulation of nano and microparticles in many fields, including colloid physics, analytical chemistry, molecular biology, clinical medicine, and pharmaceutics. The measurement of the DEP force could provide a more complete solution for verifying current classical DEP theories. This review reports various imaging, fluidic, optical, and mechanical approaches for measuring the DEP forces at different amplitudes and frequencies. The integration of DEP technology into sensors enables fast response, high sensitivity, precise discrimination, and label-free detection of proteins, bacteria, colloidal particles, and cells. Therefore, this review provides an in-depth overview of DEP-based fabrication and measurements. Depending on the measurement requirements, DEP manipulation can be classified into assistance and integration approaches to improve sensor performance. To this end, an overview is dedicated to developing the concept of trapping-on-sensing, improving its structure and performance, and realizing fully DEP-assisted lab-on-a-chip systems.

Efficient Capture and Electroreduction of Dilute CO2 into Highly Pure and Concentrated Formic Acid Aqueous Solution.

High-purity CO2 rather than dilute CO2 (15 vol %, CO2/N2/O2 = 15:80:5, v/v/v) similar to the flue gas is currently used as the feedstock for the electroreduction of CO2, and the liquid products are usually mixed up with the cathode electrolyte, resulting in high product separation costs. In this work, we showed that a microporous conductive Bi-based metal-organic framework (Bi-HHTP, HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) can not only efficiently capture CO2 from the dilute CO2 under high humidity but also catalyze the electroreduction of the adsorbed CO2 into formic acid with a high current density of 80 mA cm-2 and a Faradaic efficiency of 90% at a very low cell voltage of 2.6 V. Importantly, the performance in a dilute CO2 atmosphere was close to that under a high-purity CO2 atmosphere. This is the first catalyst that can maintain exceptional eCO2RR performance in the presence of both O2 and N2. Moreover, by using dilute CO2 as the feedstock, a 1 cm-2 working electrode coating with Bi-HHTP can continuously produce a 200 mM formic acid aqueous solution with a relative purity of 100% for at least 30 h in a membrane electrode assembly (MEA) electrolyzer. The product does not contain electrolytes, and such a highly concentrated and pure formic acid aqueous solution can be directly used as an electrolyte for formic acid fuel cells. Comprehensive studies revealed that such a high performance might be ascribed to the CO2 capture ability of the micropores on Bi-HHTP and the lower Gibbs free energy of formation of the key intermediate *OCHO on the open Bi sites.

Pupal and Adult Experience Affect Adult Response to Food Odour Components in the Flower-Visiting Butterfly Tirumala limniace.

Butterflies have the ability to learn to associate olfactory information with abundant food sources during foraging. How the co-occurrence of both food and food odours affects the learning behaviour of adults and whether butterflies perceive the odour of their surroundings and develop a preference for that odour during the pupal stage have rarely been tested. We examined the effect of experience with food odour components (α-pinene and ethyl acetate) during the pupal and adult stages on the foraging behaviour of the flower-visiting butterfly Tirumala limniace. We found that α-pinene exposure during the pupal stage changed the foraging preference of newly emerged adults. T. limniace exhibits olfactory learning in the adult stage, and adult learning may influence their previous pupal memory. Moreover, adults' odour preference did not continue to increase over multiple training times. The learning ability of adults for floral odours (α-pinene) was greater than that for non-floral odours (ethyl acetate). In contrast to previous studies, we found that males learned odours more efficiently than females did. This could be attributed to differences in antennal sensilla, affecting sensitivity to compounds and nectar demand between males and females. Our study provides further insight into how olfactory learning helps flower-visiting butterflies use food odours to forage better.

Analysis of the Distribution Pattern of Remaining Oil and Development Potential after Weak Gel Flooding in the Offshore LD Oilfield.

The LD oilfield is one of the representative offshore oilfields. After weak gel flooding, the recovery rate is significantly improved. However, the oilfield is then in a medium- to high-water content stage, presenting a complex distribution of the remaining oil. The measures for further enhanced oil recovery (EOR) are uncertain. As a result, it is necessary to clarify the distribution pattern and development potential of the remaining oil during the high-water content period after weak gel flooding. In this study, an online nuclear magnetic resonance (NMR) oil displacement experiment and microscopic oil displacement experiment were conducted, and the mechanisms of weak gel flooding and the distribution pattern of the remaining oil were clarified in the LD oilfield. Additionally, high-multiple water flooding and numerical simulation experiments were conducted to analyze the development potential after weak gel flooding. The results show that the effect of weak gel flooding was more significant in the core of 1500 mD, with an increase in oil recovery of 9% compared to 500 mD. At a permeability of 500 mD, the degree of crude oil mobilization in micropores and small pores caused by weak gel flooding was improved by 29.64% and 23.48%, respectively, compared with water flooding. At 1500 mD, the degree of crude oil mobilization in small pores caused by weak gel flooding was increased by 37.79% compared to water flooding. After weak gel flooding, the remaining oil was primarily distributed in medium and large pores. Microscopically, the remaining oil was dominated by cluster residual oil, accounting for 16.49%, followed by columnar, membranous, and blind-end residual oil. High multiple water flooding experiments demonstrated that weak gel flooding could significantly reduce development time. The ultimate oil recovery efficiency of 500 mD and 1500 mD reached 71.85% and 80.69%, respectively. Numerical simulation results show that the ultimate oil recovery efficiency increased from 62.04% to 71.3% after weak gel flooding. This indicated that the LD oilfield still had certain development potential after weak gel flooding. The subsequent direction for enhanced oil recovery focuses mainly on mobilizing oil in medium pores or clustered remaining oil. This will play a crucial role in further exploring methods for utilizing the remaining oil and increasing the recovery rate.

Large Span Sizes and Irregular Shapes Target Detection Methods Using Variable Convolution-Improved YOLOv8.

In this work, an object detection method using variable convolution-improved YOLOv8 is proposed to solve the problem of low accuracy and low efficiency in detecting spanning and irregularly shaped samples. Aiming at the problems of the irregular shape of a target, the low resolution of labeling frames, dense distribution, and the ease of overlap, a deformable convolution module is added to the original backbone network. This allows the model to deal flexibly with the problem of the insufficient perceptual field of the target corresponding to the detection point, and the situations of leakage and misdetection can be effectively improved. In order to solve the issue that small target detection is susceptible to image background and noise interference, the Sim-AM (simple parameter-free attention mechanism) module is added to the backbone network of YOLOv8, which enhances the attention to the underlying features and, thus, improves the detection accuracy of the model. More importantly, the Sim-AM module does not need to add parameters to the original network, which reduces the computation of the model. To address the problem of complex model structures that can lead to slower detection, the spatial pyramid pooling of the backbone network is replaced with focal modulation networks, which greatly simplifies the computation process. The experimental validation was carried out on the scrap steel dataset containing a large number of targets of multiple shapes and sizes. The results showed that the improved YOLOv8 network model improves the AP (average precision) by 2.1%, the mAP (mean average precision value) by 0.8%, and reduces the FPS (frames per second) by 5.4, which meets the performance requirements of real-time industrial inspection.

Molecular-Sieving Separation of Methanol/Benzene Azeotrope by a Flexible Metal-Organic Framework.

Separation of methanol/benzene azeotrope mixtures is very challenging not only by the conventional distillation technique but also by adsorbents. In this work, we design and synthesize a flexible Ca-based metal-organic framework MAF-58 consisting of cheap raw materials. MAF-58 shows selective methanol-induced pore-opening flexibility. Although the opened pores are large enough to accommodate benzene molecules, MAF-58 shows methanol/benzene molecular sieving with ultrahigh experimental selectivity, giving 5.1 mmol g-1 high-purity (99.99%+) methanol and 2.0 mmol g-1 high-purity (99.97%+) benzene in a single adsorption/desorption cycle. Computational simulations reveal that the preferentially adsorbed, coordinated methanol molecules act as the gating component to selectively block the diffusion of benzene, offering a new gating adsorption mechanism.

RAS Dataset: A 3D Cardiac LGE-MRI Dataset for Segmentation of Right Atrial Cavity.

The current challenge in effectively treating atrial fibrillation (AF) stems from a limited understanding of the intricate structure of the human atria. The objective and quantitative interpretation of the right atrium (RA) in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) scans relies heavily on its precise segmentation. Leveraging the potential of artificial intelligence (AI) for RA segmentation presents a promising solution. However, the successful implementation of AI in this context necessitates access to a substantial volume of annotated LGE-MRI images for model training. In this paper, we present a comprehensive 3D cardiac dataset comprising 50 high-resolution LGE-MRI scans, each meticulously annotated at the pixel level. The annotation process underwent rigorous standardization through crowdsourcing among a panel of medical experts, ensuring the accuracy and consistency of the annotations. Our dataset represents a significant contribution to the field, providing a valuable resource for advancing RA segmentation methods.

Solution Processing Silicon Heterojunction Photocathode for Efficient and Stable Hydrogen Production.

Efficient and stable photocathodes are crucial for the development of photoelectrochemical (PEC) water-splitting devices. Silicon heterojunction (SHJ) solar cell is one of the most advanced photovoltaic cells. However, due to the instability of its outermost indium tin oxide (ITO) layers in the electrolyte, a protective layer needs to be introduced on its surface. Previously reported high-quality protective layers almost all involved the use of expensive thin film manufacturing techniques such as atomic layer deposition (ALD). In this work, for the first time, a new strategy is proposed of modifying SHJ-based photocathode with yttrium hydroxide (Y(OH)3) through two-step solution methods to simultaneously improve the stability and activity. The optimized SHJ photocathode exhibits a high applied bias photon-to-current efficiency (ABPE) of 8.4% under simulated 100 mW cm-2 (1 Sun) with an AM 1.5G filter in 0.5 m KOH. Furthermore, the obtained SHJ photocathode demonstrates excellent stability of at least 110 h at 0.3 V versus RHE. In this work, combining facile direct current magnetron sputtering with a solution treatment technique provides a novel design strategy, which lowers the threshold for preparing high-quality protective layer, and paves the way for developing economic, efficient, and stable SHJ-based PEC devices.

Can Sb(III)-oxidizing prokaryote also oxidize As(III) under aerobic and anaerobic conditions, and vice versa?

Sb(III) and As(III) share similar chemical features and coexist in the environment. However, their oxidase enzymes have completely different sequences and structures. This raises an intriguing question: Could Sb(III)-oxidizing prokaryotes (SOPs) also oxidize As(III), and vice versa? Regarding this issue, previous investigations have yielded unclear, incorrect and even conflicting data. This work aims to address this matter. First, we prepared an enriched population of SOPs that comprises 55 different AnoA genes, lacking AioAB and ArxAB genes. We found that these SOPs can oxidize both Sb(III) and As(III) with comparable capabilities. To further confirm this finding, we isolated three cultivable SOP strains that have AnoA gene, but lack AioAB and ArxAB genes. We observed that they also oxidize both Sb(III) and As(III) under both anaerobic and aerobic conditions. Secondly, we obtained an enriched population of As(III)-oxidizing prokaryotes (AOPs) from As-contaminated soils, which comprises 69 different AioA genes, lacking AnoA gene. We observed that the AOP population has significant As(III)-oxidizing activities, but lack detectable Sb(III)-oxidizing activities under both aerobic and anaerobic conditions. Therefore, we convincingly show that SOPs can oxidize As(III), but AOPs cannot oxidize Sb(III). These findings clarify the previous ambiguities, confusion, errors or contradictions regarding how SOPs and AOPs oxidize each other's substrate.

Rapid and Visual Detection of Volatile Amines Based on Their Gas-Solid Reaction with Tetrachloro-p-Benzoquinone.

The detection of volatile amines is necessary due to the serious toxicity hazards they pose to human skin, respiratory systems, and nervous systems. However, traditional amines detection methods require bulky equipment, high costs, and complex measurements. Herein, we report a new simple, rapid, convenient, and visual method for the detection of volatile amines based on the gas-solid reactions of tetrachloro-p-benzoquinone (TCBQ) and volatile amines. The gas-solid reactions of TCBQ with a variety of volatile amines showed a visually distinct color in a time-dependent manner. Moreover, TCBQ can be easily fabricated into simple and flexible rapid test strips for detecting and distinguishing n-propylamine from other volatile amines, including ethylamine, n-butyamine, n-pentamine, n-butyamine and dimethylamine, in less than 3 s without any equipment assistance.

Dielectrophoretic characterization and selection of non-spherical flagellate algae in parallel channels with right-angle bipolar electrodes.

Non-spherical flagellate algae play an increasingly significant role in handling problematic issues as versatile biological micro/nanorobots and resources of valuable bioproducts. However, the commensalism of flagellate algae with distinct structures and constituents causes considerable difficulties in their further biological utilization. Therefore, it is imperative to develop a novel method to realize high-efficiency selection of non-spherical flagellate algae in a non-invasive manner. Enthused by these, we proposed a novel method to accomplish the selection of flagellate algae based on the numerical and experimental investigation of dielectrophoretic characterizations of flagellate algae. Firstly, an arbitrary Lagrangian-Eulerian method was utilized to study the electro-orientation and dielectrophoretic assembly process of spindle-shaped and ellipsoid-shaped cells in a uniform electric field. Secondly, we studied the equilibrium state of spherical, ellipsoid-shaped, and spindle-shaped cells under positive DEP forces actuated by right-angle bipolar electrodes. Thirdly, we investigated the dielectrophoretic assembly and escape processes of the non-spherical flagellate algae in continuous flow to explore their influences on the selection. Fourthly, freshwater flagellate algae (Euglena, H. pluvialis, and C. reinhardtii) and marine ones (Euglena, Dunaliella salina, and Platymonas) were separated to validate the feasibility and adaptability of this method. Finally, this approach was engineered in the selection of Euglena cells with high viability and motility. This method presents immense prospects in the selection of pure non-spherical flagellate algae with high motility for chronic wound healing, bio-micromotor construction, and decontamination with advantages of no sheath, strong reliability, and shape-insensitivity.

Integrative analyses of genetic characteristics associated with skeletal endothelial cells.

The osseous vascular endothelium encompasses a vast intricate framework that regulates bone remodeling. Osteoporosis, an age-associated systemic bone disease, is characterized by the degeneration of the vascular architecture. Nevertheless, the precise mechanisms underpinning the metamorphosis of endothelial cells (ECs) with advancing age remain predominantly enigmatic. In this study, we conducted a systematic analysis of differentially expressed genes (DEGs) and the associated pathways in juvenile and mature femoral ECs, utilizing data sourced from the Gene Expression Omnibus (GEO) repositories (GSE148804) and employing bioinformatics tools. Through this approach, we successfully discerned six pivotal genes, namely Adamts1, Adamts2, Adamts4, Adamts14, Col5a1, and Col5a2. Subsequently, we constructed a miRNA-mRNA network based on miRNAs displaying differential expression between CD31hiEMCNhi and CD31lowEMCNlow ECs, utilizing online repositories for prediction. The expression of miR-466i-3p and miR-466i-5p in bone marrow ECs exhibited an inverse correlation with age. Our in vivo experiments additionally unveiled miR-466i-5p as a pivotal regulator in osseous ECs and a promising therapeutic target for age-related osteoporosis.

The impact of micropolymorphism in Anpl-UAA on structural stability and peptide presentation.

Micropolymorphism significantly shapes the peptide-binding characteristics of major histocompatibility complex class I (MHC-I) molecules, affecting the host's resistance to pathogens, which is particularly pronounced in avian species displaying the "minimal essential MHC" expression pattern. In this study, we compared two duck MHC-I alleles, Anpl-UAA*77 and Anpl-UAA*78, that exhibit markedly different peptide binding properties despite their high sequence homology. Through mutagenesis experiments and crystallographic analysis of complexes with the influenza virus-derived peptide AEAIIVAMV (AEV9), we identified a critical role for the residue at position 62 in regulating hydrogen-bonding interactions between the peptide backbone and the peptide-binding groove. This modulation affects the characteristics of the B pocket and the stability of the loop region between the 310 helix and the α1 helix, leading to significant changes in the structure and stability of the peptide-MHC-I complex (pMHC-I). Moreover, the proportion of different residues at position 62 among Anpl-UAAs may reflect the correlation between pAnpl-UAA stability and duck body temperature. This research not only advances our understanding of the Anpl-UAA structure but also deepens our insight into the impact of MHC-I micropolymorphism on peptide binding.

Construction of ß-Oximino Phosphorodithioates via (2,2,6,6-Tetramethylpiperidin-1-yl)oxyl-Promoted Difunctionalization of Alkenes with tert-Butyl Nitrite, P4S10, and Alcohols.

A (2,2,6,6-tetramethylpiperidin-1-yl)oxyl-mediated difunctionalization of alkenes with tert-butyl nitrite, P4S10, and alcohols has been developed for the synthesis of ß-oximino phosphorodithioates. The reaction goes through a radical pathway with the successive installation of phosphorodithioate and an oxime group. This four-component protocol offers a practical approach to constructing a variety of ß-oximino phosphorodithioates in moderate to good yields with favorable functional group tolerance.

Preliminary construction of a microecological evaluation model for uranium-contaminated soil.

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Hemodynamics of ventricular-arterial coupling under enhanced external counterpulsation: An optimized dual-source lumped parameter model.

BACKGROUND AND OBJECTIVE: Enhanced external counterpulsation (EECP) is a mechanically assisted circulation technique widely used in the rehabilitation and management of ischemic cardiovascular diseases. It contributes to cardiovascular functions by regulating the afterload of ventricle to improve hemodynamic effects, including increased diastolic blood pressure at aortic root, increased cardiac output and enhanced blood perfusion to multiple organs including coronary circulation. However, the effects of EECP on the coupling of the ventricle and the arterial system, termed ventricular-arterial coupling (VAC), remain elusive. We aimed to investigate the acute effect of EECP on the dynamic interaction between the left ventricle and its afterload of the arterial system from the perspective of ventricular output work. METHODS: A neural network assisted optimization algorithm was proposed to identify the ordinary differential equation (ODE) relation between aortic root blood pressure and flow rate. Based on the optimized order of ODE, a lumped parameter model (LPM) under EECP was developed taking into consideration of the simultaneous action of cardiac and EECP pressure sources. The ventricular output work, in terms of aortic pressure and flow rate cooperated with the LPM, was used to characterize the VAC of ventricle and its afterload. The VAC subjected to the principle of minimal ventricular output work was validated by solving the Euler-Poisson equation of cost function, ultimately determining the waveforms of aortic pressure and flow rate. RESULTS: A third-order ODE can precisely describe the hemodynamic relationship between aortic pressure and flow rate. An optimized dual-source LPM with three energy-storage elements has been constructed, showing the potential in probing VAC under EECP. The LPM simulation results demonstrated that the VAC in terms of aortic pressure and flow rate yielded to the minimal ventricular output work under different EECP pressures. CONCLUSIONS: The ventricular-arterial coupling under EECP is subjected to the minimal ventricular output work, which can serve as a criterion for determining aortic pressure and flow rate. This study provides insight for the understanding of VAC and has the potential in characterizing the performance of the ventricular and arterial system under EECP.

Microfluidic impedance cytometry with flat-end cylindrical electrodes for accurate and fast analysis of marine microalgae.

Marine microalgae play an increasingly significant role in addressing the issues of environmental monitoring and disease treatment, making the analysis of marine microalgae at the single-cell level an essential technique. For this, we put forward accurate and fast microfluidic impedance cytometry to analyze microalgal cells by assembling two cylindrical electrodes and microchannels to form a three-dimensional detection zone. Firstly, we established a mathematical model of microalgal cell detection based on Maxwell's mixture theory and numerically investigated the effects of the electrode gap, microalgal positions, and ion concentrations of the solution on detection to optimize detection conditions. Secondly, 80 µm stainless steel wires were used to construct flat-ended cylindrical electrodes and were then inserted into two collinear channels fabricated using standard photolithography techniques to form a spatially uniform electric field to promote the detection throughput and sensitivity. Thirdly, based on the validation of this method, we measured the impedance of living Euglena and Haematococcus pluvialis to study parametric influences, including ion concentration, cell density and electrode gap. The throughput of this method was also investigated, which reached 1800 cells per s in the detection of Haematococcus pluvialis. Fourthly, we analyzed live and dead Euglena to prove the ability of this method to detect the physiological status of cells and obtained impedances of 124.3 Ω and 31.0 Ω with proportions of 15.9% and 84.1%, respectively. Finally, this method was engineered for the analysis of marine microalgae, measuring living Euglena with an impedance of 159.61 Ω accounting for 3.9%, dead Euglena with an impedance of 36.43 Ω accounting for 10.1% and Oocystis sp. with an impedance of 55.00 Ω accounting for about 81.0%. This method could provide a reliable tool to analyze marine microalgae for monitoring the marine environment and treatment of diseases owing to its outstanding advantages of low cost, high throughput and high corrosion resistance.

NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods.

Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. However, existing quality assessment methods like PSNR, SSIM, and LPIPS are not tailored for the scenes with dense viewpoints synthesized by NVS and NeRF variants, thus, they often fall short in capturing the perceptual quality, including spatial and angular aspects of NVS-synthesized scenes. Furthermore, the lack of dense ground truth views makes the full reference quality assessment on NVS-synthesized scenes challenging. For instance, datasets such as LLFF provide only sparse images, insufficient for complete full-reference assessments. To address the issues above, we propose NeRF-NQA, the first no-reference quality assessment method for densely-observed scenes synthesized from the NVS and NeRF variants. NeRF-NQA employs a joint quality assessment strategy, integrating both viewwise and pointwise approaches, to evaluate the quality of NVS-generated scenes. The viewwise approach assesses the spatial quality of each individual synthesized view and the overall inter-views consistency, while the pointwise approach focuses on the angular qualities of scene surface points and their compound inter-point quality. Extensive evaluations are conducted to compare NeRF-NQA with 23 mainstream visual quality assessment methods (from fields of image, video, and light-field assessment). The results demonstrate NeRF-NQA outperforms the existing assessment methods significantly and it shows substantial superiority on assessing NVS-synthesized scenes without references. An implementation of this paper are available at https://github.com/VincentQQu/NeRF-NQA.

Utilisation of carbon dioxide and nitrate for urea electrosynthesis with a Cu-based metal-organic framework.

It is important and challenging to utilise CO2 and NO3- as a feedstock for electrosynthesis of urea. Herein, we reported a stable 2D metal-organic framework (MOF) Cu-HATNA, possessing planar CuO4 active sites, as an efficient electrocatalyst for coupling CO2 and NO3- into urea, achieving a high yield rate of 1.46 g h-1 gcat-1 with a current density of 44.2 mA cm-1 at -0.6 V vs. RHE. This performance surpasses most of the previously reported catalysts, revealing the great prospects of MOFs in sustainable urea synthesis.