Phase-contrast Magnetic Resonance Angiography of Foot at Ultra-high field 5T System: Visualization of Distal Small Vessels and Enhancement by Warm Water Immersion.

BACKGROUND: Ultra-high field strength MR system has been proved to offer improved visualization of the distal intracranial vessels and branches, but its effectiveness on peripheral vasculatures was not investigated. We aim to assess the visualization of lower-extremity vessels using three-dimensional phase contrast MR angiography (3D PC-MRA) at 5T field-strength through the feet with warm water immersion (WWI). METHODS: Participants were prospectively recruited and underwent 3T, 5T 3D PC-MRA on feet with and without WWI (water temperature between 40 to 45 ℃ for a duration of 10minutes). Patients with suspected lower-extremity vessel diseases underwent CTA for lesion identification. Signal-to-noise ratio (SNR), subjective scoring, quantitative vessel segmentation and flow velocity were performed to assess vessel visualization before and after WWI. Friedman's test was conducted to determine statistical significance. RESULTS: Out of thirty participants (mean age, 46.2±5.9; males, 20; lower-extremity vessel disease, 10), 900 vessel segments were available for evaluation. 5T images showed significantly higher scores of image quality and foot vessel visualization than 3T (all P <.05). WWI further improved the visualizing scores (percentage of score 3: 40.2% vs 66.2%, P =.008), SNR (44.27 vs 67.78, P <.001), total branch count (151.92 ± 29.17 vs 225.63 ± 16.76; P <.001), and the flow velocity (0.72 ± 0.03 vs 0.48 ± 0.11cm/s; P <.001). CONCLUSION: 3D PC-MRA at 5T effectively visualizes foot vessels in patients with lower-extremity disease. Furthermore, WWI can significantly enhance the depiction of distal and small vessels.

AI-Driven Electrolyte Additive Selection to Boost Aqueous Zn-Ion Batteries Stability.

In tackling the stability challenge of aqueous Zn-ion batteries (AZIBs) for large-scale energy storage, the adoption of electrolyte additive emerges as a practical solution. Unlike current trial-and-error methods for selecting electrolyte additives, a data-driven strategy is proposed using theoretically computed surface free energy as a stability descriptor, benchmarked against experimental results. Numerous additives are calculated from existing literature, forming a database for machine learning (ML) training. Importantly, this ML model relies solely on experimental values, effectively addressing the challenge of large solvent molecule models that are difficult to handle with quantum chemistry computation. The interpretable linear regression algorithm identifies the number of heavy atoms in the additive molecule and the liquid surface tension as key factors. Artificial intelligence (AI) clustering categorizes additive molecules, identifying regions with the most significant impact on enhancing battery stability. Experimental verification successfully confirms the exceptional performance of 1,2,3-butanetriol and acetone in the optimal region. This integrated methodology, combining theoretical models, data-driven ML, and experimental validation, provides insights into the rational design of battery electrolyte additives.

Toward High-Energy-Density Aqueous Zinc-Iodine Batteries: Multielectron Pathways.

Aqueous zinc-iodine batteries (ZIBs) based on the reversible conversion between various iodine species have garnered global attention due to their advantages of fast redox kinetics, good reversibility, and multielectron conversion feasibility. Although significant progress has been achieved in ZIBs with the two-electron I-/I2 pathway (2eZIBs), their relatively low energy density has hindered practical application. Recently, ZIBs with four-electron I-/I2/I+ electrochemistry (4eZIBs) have shown a significant improvement in energy density. Nonetheless, the practical use of 4eZIBs is challenged by poor redox reversibility due to polyiodide shuttling during I-/I2 conversion and I+ hydrolysis during I2/I+ conversion. In this Review, we thoroughly summarize the fundamental understanding of two ZIBs, including reaction mechanisms, limitations, and improvement strategies. Importantly, we provide an intuitive evaluation on the energy density of ZIBs to assess their practical potential and highlight the critical impacts of the Zn utilization rate. Finally, we emphasize the cost issues associated with iodine electrodes and propose potential closed-loop recycling routes for sustainable energy storage with ZIBs. These findings aim to motivate the practical application of advanced ZIBs and promote sustainable global energy storage.

Highly plastic Zn-0.3Ca alloy for guided bone regeneration membrane: Breaking the trade-off between antibacterial ability and biocompatibility.

A common problem for Zn alloys is the trade-off between antibacterial ability and biocompatibility. This paper proposes a strategy to solve this problem by increasing release ratio of Ca2+ ions, which is realized by significant refinement of CaZn13 particles through bottom circulating water-cooled casting (BCWC) and rolling. Compared with conventionally fabricated Zn-0.3Ca alloy, the BCWC-rolled alloy shows higher antibacterial abilities against E. coli and S. aureus, meanwhile much less toxicity to MC3T3-E1 cells. Additionally, plasticity, degradation uniformity, and ability to induce osteogenic differentiation in vitro of the alloy are improved. The elongation up to 49 %, which is the highest among Zn alloys with Ca, and is achieved since the sizes of CaZn13 particles and Zn grains are small and close. As a result, the long-standing problem of low formability of Zn alloys containing Ca has also been solved due to the elimination of large CaZn13 particles. The BCWC-rolled alloy is a promising candidate of making GBR membrane.

Anti-Swelling Microporous Membrane for High-Capacity and Long-Life Zn-I2 Batteries.

Zinc-iodine (Zn-I2) batteries are gaining popularity due to cost-effectiveness and ease of manufacturing. However, challenges like polyiodide shuttle effect and Zn dendrite growth hinder their practical application. Here, we report a cation exchange membrane to simultaneously prevent the polyiodide shuttle effect and regulate Zn2+ deposition. Comprised of rigid polymers, this membrane shows superior swelling resistance and ion selectivity compared to commercial Nafion. The resulting Zn-I2 battery exhibits a high Coulombic efficiency of 99.4 % and low self-discharge rate of 4.47 % after 48 h rest. By directing a uniform Zn2+ flux, the membrane promotes a homogeneous electric field, resulting in a dendrite-free Zn surface. Moreover, its microporous structure enables pre-adsorption of additional active materials prior to battery assembly, boosting battery capacity to 287 mAh g-1 at 0.1 A g-1. At 2 A g-1, the battery exhibits a steady running for 10,000 cycles with capacity retention up to 96.1 %, demonstrating high durability of the membrane. The practicality of the membrane is validated via a high-loading (35 mg cm-2) pouch cell with impressive cycling stability, paving a way for membrane design towards advanced Zn-I2 batteries.

Machine Learning Big Data Set Analysis Reveals C-C Electro-Coupling Mechanism.

Carbon-carbon (C-C) coupling is essential in the electrocatalytic reduction of CO2 for the production of green chemicals. However, due to the complexity of the reaction network, there remains controversy regarding the underlying reaction mechanisms and the optimal direction for catalyst material design. Here, we present a global perspective to establish a comprehensive data set encompassing all C-C coupling precursors and catalytic active site compositions to explore the reaction mechanisms and screen catalysts via big data set analysis. The 2D-3D ensemble machine learning strategy, developed to target a variety of adsorption configurations, can quickly and accurately expand quantum chemical calculation data, enabling the rapid acquisition of this extensive big data set. Analyses of the big data set establish that (1) asymmetric coupling mechanisms exhibit greater potential efficiency compared to symmetric coupling, with the optimal path involving the coupling CHO with CH or CH2, and (2) C-C coupling selectivity of Cu-based catalysts can be enhanced through bimetallic doping including CuAgNb sites. Importantly, we experimentally substantiate the CuAgNb catalyst to demonstrate actual boosted performance in C-C coupling. Our finding evidence the practicality of our big data set generated from machine learning-accelerated quantum chemical computations. We conclude that combining big data with complex catalytic reaction mechanisms and catalyst compositions will set a new paradigm for accelerating optimal catalyst design.

Lipid nanoparticles encapsulating curcumin for imaging and stabilization of vulnerable atherosclerotic plaques via phagocytic "eat-me" signals.

Curcumin potentiates the stabilization of atherosclerotic plaques by polarizing macrophages, but its non-specific targeting hinders its clinical application. We aim to harness multifunctional lipid nanoparticles (MLNPs) to facilitate the imaging and targeted delivery of curcumin specifically to inflammatory macrophages, counteracting vulnerable plaques and mitigating the risk of ischemic events. Cholesteryl-9-carboxynonanoate-(125I­iron oxide nanoparticle/Curcumin)-lipid-coated nanoparticles [9-CCN-(125I-ION/Cur)-LNPs], namely MLNPs, are designed to carry hybrid imaging agents. These agents combine 125I-ION with lipids containing phagocytic 'eat-me' signals, inducing macrophages to engulf the MLNPs. Our research demonstrates that the designed MLNPs accurately accumulate at unstable plaques and are precisely visualized and highlighted by both SPECT and MRI. Furthermore, MLNPs achieve high efficiency in delivering 125I-ION and curcumin to macrophages, ultimately leading to significant M1-to-M2 macrophage polarization. These real-time imaging and polarization capabilities of plaques have immediate clinical applicability and may pave the way for novel therapies to stabilize unstable atherosclerotic plaques.

Protein Interfacial Gelation toward Shuttle-Free and Dendrite-Free Zn-Iodine Batteries.

Aqueous zinc-iodine (Zn-I2) batteries hold potential for large-scale energy storage but struggle with shuttle effects of I2 cathodes and poor reversibility of Zn anodes. Here, an interfacial gelation strategy is proposed to suppress the shuttle effects and improve the Zn reversibility simultaneously by introducing silk protein (SP) additive. The SP can migrate bidirectionally toward cathode and anode interfaces driven by the periodically switched electric field direction during charging/discharging. For I2 cathodes, the interaction between SP and polyiodides forms gelatinous precipitate to avoid the polyiodide dissolution, evidenced by excellent electrochemical performance, including high specific capacity and Coulombic efficiency (CE) (215 mAh g-1 and 99.5% at 1 C), excellent rate performance (≈170 mAh g-1 at 50 C), and extended durability (6000 cycles at 10 C). For Zn anodes, gelatinous SP serves as protective layer to boost the Zn reversibility (99.7% average CE at 2 mA cm-2) and suppress dendrites. Consequently, a 500 mAh Zn-I2 pouch cell with high-loading cathode (37.5 mgiodine cm-2) and high-utilization Zn anode (20%) achieves remarkable energy density (80 Wh kg-1) and long-term durability (>1000 cycles). These findings underscore the simultaneous modulation of both cathode and anode and demonstrate the potential for practical applications of Zn-I2 batteries.

Developing Cathode Films for Practical All-Solid-State Lithium-Sulfur Batteries.

The development of all-solid-state lithium-sulfur batteries (ASSLSBs) toward large-scale electrochemical energy storage is driven by the higher specific energies and lower cost in comparison with the state-of-the-art Li-ion batteries. Yet, insufficient mechanistic understanding and quantitative parameters of the key components in sulfur-based cathode hinders the advancement of the ASSLSB technologies. This review offers a comprehensive analysis of electrode parameters, including specific capacity, voltage, S mass loading and S content toward establishing the specific energy (Wh kg-1) and energy density (Wh L-1) of the ASSLSBs. Additionally, this work critically evaluates the progress in enhancing lithium ion and electron percolation and mitigating electrochemical-mechanical degradation in sulfur-based cathodes. Last, a critical outlook on potential future research directions is provided to guide the rational design of high-performance sulfur-based cathodes toward practical ASSLSBs.

Aqueous Zinc-Iodine Pouch Cells with Long Cycling Life and Low Self-Discharge.

Aqueous zinc batteries are practically promising for large-scale energy storage because of cost-effectiveness and safety. However, application is limited because of an absence of economical electrolytes to stabilize both the cathode and anode. Here, we report a facile method for advanced zinc-iodine batteries via addition of a trace imidazolium-based additive to a cost-effective zinc sulfate electrolyte, which bonds with polyiodides to boost anti-self-discharge performance and cycling stability. Additive aggregation at the cathode improves the rate capacity by boosting the I2 conversion kinetics. Also, the introduced additive enhances the reversibility of the zinc anode by adjusting Zn2+ deposition. The zinc-iodine pouch cell, therefore, exhibits industrial-level performance evidenced by a ∼99.98% Coulombic efficiency under ca. 0.4C, a significantly low self-discharge rate with 11.7% capacity loss per month, a long lifespan with 88.3% of initial capacity after 5000 cycles at a 68.3% zinc depth-of-discharge, and fast-charging of ca. 6.7C at a high active-mass loading >15 mg cm-2. Highly significant is that this self-discharge surpasses commercial nickel-metal hydride batteries and is comparable with commercial lead-acid batteries, together with the fact that the lifespan is over 10 times greater than reported works, and the fast-charging performance is better than commercial lithium-ion batteries.

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality. The limited temporal resolution also causes patient discomfort and introduces artifacts in the images, further diminishing their overall quality and diagnostic value. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have so far not been made publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. The 'CMRxRecon' dataset contains raw k-space data and auto-calibration lines. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community.

The role of electrocatalytic materials for developing post-lithium metal||sulfur batteries.

The exploration of post-Lithium (Li) metals, such as Sodium (Na), Potassium (K), Magnesium (Mg), Calcium (Ca), Aluminum (Al), and Zinc (Zn), for electrochemical energy storage has been driven by the limited availability of Li and the higher theoretical specific energies compared to the state-of-the-art Li-ion batteries. Post-Li metal||S batteries have emerged as a promising system for practical applications. Yet, the insufficient understanding of quantitative cell parameters and the mechanisms of sulfur electrocatalytic conversion hinder the advancement of these battery technologies. This perspective offers a comprehensive analysis of electrode parameters, including S mass loading, S content, electrolyte/S ratio, and negative/positive electrode capacity ratio, in establishing the specific energy (Wh kg-1) of post-Li metal||S batteries. Additionally, we critically evaluate the progress in investigating electrochemical sulfur conversion via homogeneous and heterogeneous electrocatalytic approaches in both non-aqueous Na/K/Mg/Ca/Al||S and aqueous Zn||S batteries. Lastly, we provide a critical outlook on potential research directions for designing practical post-Li metal||S batteries.

Electrocatalytic Acetylene Hydrogenation in Concentrated Seawater at Industrial Current Densities.

Electrocatalytic acetylene hydrogenation to ethylene (E-AHE) is a promising alternative for thermal-catalytic process, yet it suffers from low current densities and efficiency. Here, we achieved a 71.2 % Faradaic efficiency (FE) of E-AHE at a large partial current density of 1.0 A cm-2 using concentrated seawater as an electrolyte, which can be recycled from the brine waste (0.96 M NaCl) of alkaline seawater electrolysis (ASE). Mechanistic studies unveiled that cation of concentrated seawater dynamically prompted unsaturated interfacial water dissociation to provide protons for enhanced E-AHE. As a result, compared with freshwater, a twofold increase of FE of E-AHE was achieved on concentrated seawater-based electrolysis. We also demonstrated an integrated system of ASE and E-AHE for hydrogen and ethylene production, in which the obtained brine output from ASE was directly fed into E-AHE process without any further treatment for continuously cyclic operations. This innovative system delivered outstanding FE and selectivity of ethylene surpassed 97.0 % and 97.5 % across wide-industrial current density range (≤ 0.6 A cm-2), respectively. This work provides a significant advance of electrocatalytic ethylene production coupling with brine refining of seawater electrolysis.

Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Advanced cathodes for aqueous Zn batteries beyond Zn2+ intercalation.

Aqueous zinc (Zn) batteries have attracted global attention for energy storage. Despite significant progress in advancing Zn anode materials, there has been little progress in cathodes. The predominant cathodes working with Zn2+/H+ intercalation, however, exhibit drawbacks, including a high Zn2+ diffusion energy barrier, pH fluctuation(s) and limited reproducibility. Beyond Zn2+ intercalation, alternative working principles have been reported that broaden cathode options, including conversion, hybrid, anion insertion and deposition/dissolution. In this review, we report a critical assessment of non-intercalation-type cathode materials in aqueous Zn batteries, and identify strengths and weaknesses of these cathodes in small-scale batteries, together with current strategies to boost material performance. We assess the technical gap(s) in transitioning these cathodes from laboratory-scale research to industrial-scale battery applications. We conclude that S, I2 and Br2 electrodes exhibit practically promising commercial prospects, and future research is directed to optimizing cathodes. Findings will be useful for researchers and manufacturers in advancing cathodes for aqueous Zn batteries beyond Zn2+ intercalation.

How surface-to-volume ratio affects degradation of magnesium: in vitro and in vivo studies.

Despite the many studies carried out over the past decade to determine the biodegradation performance of magnesium and its alloys, few studies focused on the effect of altered surface area to volume ratio on in vitro and in vivo degradation rate and osteogenesis. Here, high purity magnesium cylindrical rods with gradient of surface area to volume ratio were processed by excavating different numbers of grooves on the side surface. The immersion test in SBF solution and the rat femoral condylar bone defect model were used to evaluate the degradation of magnesium rods in vitro and in vivo, respectively. We demonstrated that, the increased number of grooves on the HP magnesium surface represented a decrease in the percentage of residual volume over time, not necessarily an increase in absolute degradation volume or a regular change in corrosion rate. Furthermore, there were strong linear correlations between the relative degradation volume and the initial surface-to-volume ratio of HP magnesium rods both in vitro and in vivo. The difference in the slope of this relationship in vitro and in vivo might help to determine the possible range of in vivo degradation rates via in vitro data. In addition, the corrosion rate is more suitable for evaluating bone formation surrounding the different HP magnesium rods. Our findings in this work may facilitate adjusting the in vivo degradation and osteogenesis of different kinds of orthopedic implants made of the same magnesium-based material, and thus, accelerate the clinical popularization and application.

Recent advancement on photocatalytic plastic upcycling.

More than 8 billion tons of plastics have been generated since 1950. About 80% of these plastics have been dumped in landfills or went into natural environments, resulting in ever-worsening contamination. Among various strategies for waste plastics processing (e.g., incineration, mechanical recycling, thermochemical conversion and electrocatalytic/photocatalytic techniques), photocatalysis stands out as a cost-effective, environmentally benign and clean technique to upcycle plastic waste at ambient temperature and pressure using solar light. The mild reaction conditions for photocatalysis enable the highly selective conversion of plastic waste into targeted value-added chemicals/fuels. Here, we for the first time summarize the recent development of photocatalytic plastic upcycling based on the chemical composition of photocatalysts (e.g., metal oxides, metal sulfides, non-metals and composites). The pros and cons of various photocatalysts have been critically discussed and summarized. At last, the future challenges and opportunities in this area are presented in this review.

Developing high-power Li||S batteries via transition metal/carbon nanocomposite electrocatalyst engineering.

The activity of electrocatalysts for the sulfur reduction reaction (SRR) can be represented using volcano plots, which describe specific thermodynamic trends. However, a kinetic trend that describes the SRR at high current rates is not yet available, limiting our understanding of kinetics variations and hindering the development of high-power Li||S batteries. Here, using Le Chatelier's principle as a guideline, we establish an SRR kinetic trend that correlates polysulfide concentrations with kinetic currents. Synchrotron X-ray adsorption spectroscopy measurements and molecular orbital computations reveal the role of orbital occupancy in transition metal-based catalysts in determining polysulfide concentrations and thus SRR kinetic predictions. Using the kinetic trend, we design a nanocomposite electrocatalyst that comprises a carbon material and CoZn clusters. When the electrocatalyst is used in a sulfur-based positive electrode (5 mg cm-2 of S loading), the corresponding Li||S coin cell (with an electrolyte:S mass ratio of 4.8) can be cycled for 1,000 cycles at 8 C (that is, 13.4 A gS-1, based on the mass of sulfur) and 25 °C. This cell demonstrates a discharge capacity retention of about 75% (final discharge capacity of 500 mAh gS-1) corresponding to an initial specific power of 26,120 W kgS-1 and specific energy of 1,306 Wh kgS-1.

Local reaction environment in electrocatalysis.

Beyond conventional electrocatalyst engineering, recent studies have unveiled the effectiveness of manipulating the local reaction environment in enhancing the performance of electrocatalytic reactions. The general principles and strategies of local environmental engineering for different electrocatalytic processes have been extensively investigated. This review provides a critical appraisal of the recent advancements in local reaction environment engineering, aiming to comprehensively assess this emerging field. It presents the interactions among surface structure, ions distribution and local electric field in relation to the local reaction environment. Useful protocols such as the interfacial reactant concentration, mass transport rate, adsorption/desorption behaviors, and binding energy are in-depth discussed toward modifying the local reaction environment. Meanwhile, electrode physical structures and reaction cell configurations are viable optimization methods in engineering local reaction environments. In combination with operando investigation techniques, we conclude that rational modifications of the local reaction environment can significantly enhance various electrocatalytic processes by optimizing the thermodynamic and kinetic properties of the reaction interface. We also outline future research directions to attain a comprehensive understanding and effective modulation of the local reaction environment.