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Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.

The Proton Exchange Membrane (PEM) water electrolyzer is considered one of the promising energy storing means for harnessing variable renewable energy sources to produce hydrogen. Understanding the internal fluid dynamics, which are often challenging to directly observe experimentally, has prompted the use of numerical models to investigate two-phase flow within PEM water electrolyzers. In this study, we provide a comprehensive review of prior research focusing on two-phase modeling of PEM electrolyzers, encompassing both components at mesoscopic scales and the full electrolyzer at the macroscopic level. We delve into the specifics of various modeling approaches for two-phase flow at different scales and summarize and discuss the current state of the art in the field. Presently, two-phase models for the full electrolyzer predominantly employ a macroscopic homogeneous assumption. However, mesoscopic and microscopic models capable of tracking phase interfaces are limited to components. Challenges persist in integrating various modeling scales into a comprehensive electrolyzer model, particularly in coupling two-phase flow between the channels and porous media. Future efforts should focus on developing multi-scale models and simulating two-phase flow under fluctuating input conditions. Additionally, given the structural similarities between PEM water electrolyzers and PEM fuel cells, we compare and discuss differences in two-phase modeling between the two technologies. This work offers the insights for researchers in the field of modeling of PEM water electrolyzers and even fuel cells.

Abstract Background HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors. Methods We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW). Results The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings. Conclusions HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment.

To improve the prediction accuracy of chaotic time series and reconstruct a more reasonable phase space structure of the prediction network, we propose a convolutional neural network (CNN)-long short-term memory (LSTM) prediction model based on the incremental attention mechanism. Firstly, a traversal search is conducted through the traversal layer for finite parameters in the phase space. Then, an incremental attention layer is utilized for parameter judgment based on the dimension weight criteria (DWC). The phase space parameters that best meet DWC are selected and fed into the input layer. Finally, the constructed CNN-LSTM network extracts spatiotemporal features and provides the final prediction results. The model is verified using Logistic, Lorenz, and sunspot chaotic time series, and the performance is compared from the two dimensions of prediction accuracy and network phase space structure. Additionally, the CNN-LSTM network based on incremental attention is compared with LSTM, CNN, recurrent neural network (RNN), and support vector regression (SVR) for prediction accuracy. The experiment results indicate that the proposed composite network model possesses enhanced capability in extracting temporal features and achieves higher prediction accuracy. Also, the algorithm to estimate the phase space parameter is compared with the traditional CAO, false nearest neighbor, and C–C, three typical methods for determining the chaotic phase space parameters. The experiments reveal that the phase space parameter estimation algorithm based on the incremental attention mechanism is superior in prediction accuracy compared with the traditional phase space reconstruction method in five networks, including CNN-LSTM, LSTM, CNN, RNN, and SVR.

China’s coal-fired power plants emit over 5.7 billion tons of CO2 annually. To realize the dual carbon goals in time, it is necessary to reduce the carbon emissions of coal-fired power plants. Microalgae carbon fixation can efficiently absorb CO2 through photosynthesis and convert it into biomass, which is a highly promising technology for carbon reduction in coal-fired power plants. Light guide tubes can flexibly change the light distribution in a photobioreactor, while optical fibers can transmit light centrally with low light loss. Therefore, a microalgae photobioreactor with an optical fiber/light guide tube is proposed to expand the light-receiving area of the microalgae suspension, increase the light-harvesting of microalgal cells, and promote carbon fixation via microalgae photosynthesis. The optical simulation software was used to trace the propagation of light in the optical fiber/light guide tube, and the light intensity distribution of the tube wall was obtained. Microalgae cultivation experiments were conducted in various photobioreactors and under different input light energy conditions. The change trends of biomass yield, carbon sequestration rate, and chlorophyll content were obtained, and the impact of built-in optical fiber /light guide tubes on carbon fixation via microalgae was investigated. Results indicated that the light intensity emitted from the optical fiber terminal decreased precipitously from 30 mm to 140 mm along the side of the light guide tube. Additionally, the tube exhibited a concentrated light-emitting range. Adding a conical reflector to reflect the transmitted light at the tube bottom and designing a stepped optical fiber to emit input light from different steps can optimize the light-emitting effect of the light guide tube and make the light distribution in the microalgae photobioreactor more uniform, so that the microalgal cells far away from the light source area can receive the light energy to photosynthesize and fix carbon. At a light input of 3.3 W/L, the minimum light intensity on the side surface of the light guide comprising a two-stage stepped optical fiber and conical reflector was 47 μmol/(m2·s). The average light intensity was 64 μmol/(m2·s), representing a 2.6-fold increase compared to the light guide tube lacking both the optical fiber and any enhancements beyond its top section. After seven days of cultivation, the microalgae concentration in the stepped fiber photobioreactor (SF-PBR) could reach 1.9 g/L, which was 46.2% higher than that of the photobioreactor inserted with flat-end fiber optic light guide (FF-PBR) and 111.1% higher than that of the photobioreactor with only top-fed light (LG-PBR). When the light input was escalated to 5.0 W/L, a high microalgae concentration of 2.8 g/L was achieved at 7 d. Meanwhile, the average carbon sequestration rate of 608.3 mg/(L·d) was obtained, exhibiting 1.9-fold augmentation compared to the control LG-PBR.

Traumatic brain injury is a serious medical condition that can be attributed to falls, motor vehicle accidents, sports injuries and acts of violence, causing a series of neural injuries and neuropsychiatric symptoms. However, limited accessibility to the injury sites, complicated histological and anatomical structure, intricate cellular and extracellular milieu, lack of regenerative capacity in the native cells, vast variety of damage routes, and the insufficient time available for treatment have restricted the widespread application of several therapeutic methods in cases of central nervous system injury. Tissue engineering and regenerative medicine have emerged as innovative approaches in the field of nerve regeneration. By combining biomaterials, stem cells, and growth factors, these approaches have provided a platform for developing effective treatments for neural injuries, which can offer the potential to restore neural function, improve patient outcomes, and reduce the need for drugs and invasive surgical procedures. Biomaterials have shown advantages in promoting neural development, inhibiting glial scar formation, and providing a suitable biomimetic neural microenvironment, which makes their application promising in the field of neural regeneration. For instance, bioactive scaffolds loaded with stem cells can provide a biocompatible and biodegradable milieu. Furthermore, stem cells-derived exosomes combine the advantages of stem cells, avoid the risk of immune rejection, cooperate with biomaterials to enhance their biological functions, and exert stable functions, thereby inducing angiogenesis and neural regeneration in patients with traumatic brain injury and promoting the recovery of brain function. Unfortunately, biomaterials have shown positive effects in the laboratory, but when similar materials are used in clinical studies of human central nervous system regeneration, their efficacy is unsatisfactory. Here, we review the characteristics and properties of various bioactive materials, followed by the introduction of applications based on biochemistry and cell molecules, and discuss the emerging role of biomaterials in promoting neural regeneration. Further, we summarize the adaptive biomaterials infused with exosomes produced from stem cells and stem cells themselves for the treatment of traumatic brain injury. Finally, we present the main limitations of biomaterials for the treatment of traumatic brain injury and offer insights into their future potential.

Macrophages play a central role in immunological responses to metallic species associated with the localized corrosion of metallic implants, and mediating in peri-implant inflammations. Herein, the pathways of localized corrosion-macrophage interactions were systematically investigated on 316L stainless steel (SS) implant metals. Electrochemical monitoring under macrophage-mediated inflammatory conditions showed a decreased pitting corrosion resistance of 316L SSs in the presence of RAW264.7 cells as the cells would disrupt biomolecule adsorbed layer on the metal surface. The pitting potentials were furtherly decreased when the RAW264.7 cells were induced to the M1 pro-inflammatory phenotype by the addition of lipopolysaccharide (LPS), and pitting corrosion preferentially initiated at the peripheries of macrophages. The overproduction of aggressive ROS under inflammatory conditions would accelerate the localized corrosion of 316L SS around macrophages. Under pitting corrosion condition, the viability and pro-inflammatory polarization of RAW264.7 cells were region-dependent, lower viability and more remarkable morphology transformation of macrophages in the pitting corrosion region than the pitting-free region. The pitting corrosion of 316L SS induced high expression of CD86, TNF-α, IL-6 and high level of intracellular ROS in macrophages. Uneven release of metallic species (Fe2+, Cr3+, Ni2+, etc) and uneven distribution of surface overpotential stimulated macrophage inflammatory responses near the corrosion pits. A synergetic effect of localized corrosion and macrophages was revealed, which could furtherly promote localized corrosion of 316L SS and macrophage inflammatory reactions. Our results provided direct evidence of corrosion-macrophage interaction in metallic implants and disclosed the pathways of this mutual stimulation effect.

Centrifugal granulation is one key step to enable waste heat recovery from the molten slag in the iron and steel industry. Yet, it remains unknown about the granulation characteristics of molten slag with different chemical compositions, especially at high throughput. In this work, we provided an experimental study on centrifugal granulation with four types of molten slags. The stage-specific centrifugal granulation was recorded and analyzed at first. Both effects of atomizer configuration and chemical compositions on granulation were investigated in detail. The cup-type atomizer favors film-mode disintegration and possesses better anti-adhesion capacity although the final granule size was not strongly affected by the atomizer configuration. Most importantly, centrifugal granulation has been demonstrated with appreciable adaptability to composition-specific blast furnace (BF) slag with binary basicity of 0.9–1.3. The present study not only sheds light on the modest effect of the chemical composition of molten slag on centrifugal granulation characteristics, but also gains credit for the adaptivity of CGATER.

Hawthorn fruits of different varieties have varied nutritional composition, sensory properties etc., thus required for different processing for product development. Due to the limitations of traditional analytical methods of time-consuming, destructive sample preparation, and high cost ect., non-destructive techniques for variety identification are needed which would benefit for large scale production of foods with hawthorn fruits. In this study, a total of 240 hawthorn fruit samples from four different varieties were subjected for near-infrared spectroscopy analysis and the collected spectral data were pre-processed by different algorithms. In order to achieve non-destructive identification of hawthorn varieties, natural language processing (NLP) model was applied for data analysis, including long short-term memory (LSTM), gated recurrent unit (GRU) neural network, logistic regression, native Bayes, decision trees, and k-nearest neighbors. The results showed that the two deep learning models both had the best discrimination effect on the spectral preprocessed by principal component analysis (PCA) with the accuracy of the validation set and test set reached 99.46%±0.00% and 100%±0.00%. While, the logistic regression model showed excellent discrimination ability for hawthorn fruit spectra but poor discrimination ability for the difference of second order (D2) pretreatment spectra (accuracy of 96.65% in the validation set and 89.58% in the test set). The naive Bayes model also showed excellent discrimination effect on the spectra processed by PCA, and the accuracy of the validation set was 95.65%, and the accuracy of the test set was 95.83%. Results gained in this study confirmed the feasibility of applying NLP to the near-infrared non-destructive identification of hawthorn fruits.

Intensification of biofuel production processes could play a critical role in boosting the economic and environmental features of the whole process. A novel bionic flow-induced peristaltic reactor with a high conversion rate is constructed to realize efficient biofuel production from high-concentration high-viscosity fluids. It is experimentally verified through biodiesel production from soybean oil. Experimental results show that the conversion efficiency is up to 89.9% at 10 s in the peristaltic reactor, which is 38.4% higher than that in the rigid tube reactor. Furthermore, a three-dimensional peristaltic model is conducted to understand the mechanism of heat and mass transfer enhancement. The simulation results show that an increase in peristaltic amplitude strengthens the mixing of the bionic peristaltic reactor by 92.5-100.8%. The temperature distribution in the bionic peristaltic reactor is more uniform than in the traditional rigid tube reactor. The results demonstrate that the conversion rate of soybean oil in the bionic flow-induced peristaltic reactor is 528.82% min-1, which is 17-60 times higher than other intensified reactors operating in either continuous or batch modes.

Abstract Background Improvement of health literacy constitutes a cornerstone to improving public health. However, the overall health literacy of Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) in the southwest Sichuan Province of China has kept extremely low for a long time. How to improve health literacy of the Yi nationality residents is key to be urgently solved. Notably, Family Branch System is a distinctive patrilineal bloodline organization of Yi nationality, which plays an important role in the daily life of Yi nationality. Meanwhile, Contracted Family Doctor Services is conducted in Liangshan Prefecture. Therefore, this study proposes an intervention model of health education based on Family Branch System and Contracted Family Doctor Services, which is a Family-based Improvement for Health Literacy among the Yi nationality (FAMILY) in Liangshan, when improving traditional Innovative Care for Chronic Conditions Framework (ICCC) framework. Methods An open cohort stepped wedge cluster randomized trial design is used to implement health literacy education interventions including project preparation, core group building, promotion within family branch and competition between family branches while using Contracted Family Doctor Services as control measure. The study will be conducted among Yi nationality residents in Meigu County and Yanyuan County, with health literacy level of residents as the primary outcome. Finally, mixed-effects model and causal inference method will be used to evaluate intervention effect. Discussion This study highlights family, using the unique Family Branch System and Contracted Family Doctor Services in Liangshan Prefecture to design intervention among improved ICCC framework, and combines the mixed-effects model with complier average causal effects (CACE) to estimate the intervention effect under non-compliance for the first time. Besides, other key technologies to be adopted include construction of electronic questionnaire quality control system, with quality control based on artificial intelligence. This trial contributes to exploring an effective way to improve health literacy of Yi nationality residents in Liangshan Prefecture, which will provide reference for other areas, especially poor areas, to improve residents’ health literacy. Trial registration ISRCTN11299863 on June 1, 2022; https://www.isrctn.com/ .

Located in the hilly and mountainous central area of the national ecological security strategic pattern (described as “two ecological barriers and three green belts”), southern Jiangxi is an important ecological barrier in southeast China and a pilot area for the national mountains-rivers-forests-farmlands-lakes-grasslands restoration projects. In recent years, the rapid economic development of the southern Jiangxi region and the rapid changes in land use, agricultural intensification, and population urbanization have severely tested this ecosystem on which people depend for their survival. Currently, studies of ecosystems and their interactions from a single spatial perspective have sprung up, but only a few studies have comprehensively analyzed different spatial scales to facilitate the sustainable development of regional ecosystems. Multi-scale studies should be carried out to quantitatively understand the relationship between ecosystem services (ESs) and socio-natural drivers, in an attempt to find a suitable scale to assess regional ESs or to achieve complementary advantages by combining multi-scales so as to conduct hierarchical management of ESs. Therefore, to better understand the interplay between ESs and to achieve the goals of sustainable development, we quantitatively analyzed the evolutionary patterns, trade-offs, and synergies of ESs. In our analysis, we also looked at bundling ESs and their drivers for seven ecosystem services at the township and watershed scales for 2000–2020 in southern Jiangxi. Crop production, meat production, water yield, carbon storage, soil retention, habitat quality, and forest recreation services were specifically quantified, and redundancy analysis was used to explore the influence degree of precipitation, temperature, elevation, slope, GDP, and population density on ESs. The results showed that most ESs have increased in southern Jiangxi, indicating spatial and temporal heterogeneity. The scale effect of trade-off and synergy showed that the spatial variation was similar, but the amplitude of variation was different. Compared with the watershed scale, the overall bundle of ESs in southern Jiangxi is better identified and clustered at the township scale. In addition, Cluster 4 at the township scale and Cluster 3 at the watershed scale can comprehensively identify high-value areas of ecosystem services in the study area. The rapid growth of GDP and population density caused by rapid urbanization were the main driving factors of the difference in ESs between the two scales in southern Jiangxi. Our results provide recommendations for governance and restoration of regional ecosystem services and support for conducting a comprehensive analysis of spatio-temporal evolutionary mechanisms and interactions of ecosystem services at different scales.

Abstract Background It is of great challenge to raise the public coronavirus disease 2019 (COVID-19) related health literacy (CRHL) in impoverished regions due to the limits of poor infrastructure, large proportion of vulnerable groups, etc. However, those limits cannot be solved in the short term. Therefore, this study chose Liangshan Yi Autonomous Prefecture, one of the poorest areas in China, as a pilot, to reveal the quantitative relationships among different dimensions under the COVID-19 health education framework, clarify the key points for health promotion, and provide specific suggestions for COVID-19 health education strategy in impoverished regions. Methods A cross-sectional questionnaire survey was conducted in five regions of Liangshan Yi Autonomous Prefecture in 2020. There were 2,100 individuals sampled by multi-stage method. This survey mainly measured the four dimensions: CRHL, COVID-19 related tense psychological reactions (CRTPR), COVID-19 related information report acquisition (CRIRA), and general health literacy (GHL). The multivariate logistic regression was used to explore the influence of demographic characteristics on each dimension. Furthermore, to quantify the relationships among different dimensions, this study employed the structural equation model (SEM), and analyzed the mediating effects of CRHL and CRIRA as well as the moderating effects of regional characteristic variables. Results The CRHL played an important role in promoting COVID-19 health education, reaching 52.5% in Liangshan Yi Autonomous Prefecture. The GHL (β = 0.336) and age (β = 0.136) had statistically positive impacts on CRHL. The CRHL affected CRTPR negatively (β = − 0.198) and CRIRA positively (β = 0.052). The CRHL played significant mediating roles among the four dimensions (P

Abstract Background Continuous surveillance of death can measure health status of the population, reflect social development of a region, thus promote health service development in the region and improve the health level of local residents. Liangshan Yi Autonomous Prefecture was a poverty-stricken region in Sichuan province, China. While at the end of 2020, as the announcement of its last seven former severely impoverished counties had shaken off poverty, Liangshan declared victory against poverty. Since it is well known that the mortality and cause of death structure will undergo some undesirable changes as the economy develops, this study aimed to reveal the distribution of deaths, as well as analyze the latest mortality and death causes distribution characteristics in Liangshan in 2020, so as to provide references for the decision-making on health policies and the distribution of health resources in global poverty-stricken areas. Methods Liangshan carried out the investigation on underreporting deaths among population in its 11 counties in 2018, and combined with the partially available data from underreporting deaths investigation data in 2020 and the field experience, we have estimated the underreporting rates of death in 2020 using capture-recapture (CRC) method. The crude mortality rate, age-standardized mortality rate, proportion and rank of the death causes, potential years of life lost (PYLL), average years of life lost (AYLL), potential years of life lost rate (PYLLR), standardized potential years of life lost (SPYLL), premature mortality from non-communicable diseases (premature NCD mortality), life expectancy and cause-eliminated life expectancy were estimated and corrected. Results In 2020, Liangshan reported a total of 16,850 deaths, with a crude mortality rate of 608.75/100,000 and an age-standardized mortality rate of 633.50/100,000. Male mortality was higher than female mortality, while 0-year-old mortality of men was lower than women’s. The former severely impoverished counties’ age-standardized mortality and 0-year-old mortality were higher than those of the non-impoverished counties. The main cause of death spectrum was noncommunicable diseases (NCDs), and the premature NCD mortality of four major NCDs were 14.26% for the overall population, 19.16% for men and 9.27% for women. In the overall population, the top five death causes were heart diseases (112.07/100,000), respiratory diseases (105.85/100,000), cerebrovascular diseases (87.03/100,000), malignant tumors (73.92/100,000) and injury (43.89/100,000). Injury (64,216.78 person years), malignant tumors (41,478.33 person years) and heart diseases (29,647.83 person years) had the greatest burden on residents in Liangshan, and at the same time, the burden of most death causes on men were greater than those on women. The life expectancy was 76.25 years for overall population, 72.92 years for men and 80.17 years for women, respectively, all higher than the global level (73.3, 70.8 and 75.9 years). Conclusions Taking Liangshan in China as an example, this study analyzed the latest death situation in poverty-stricken areas, and proposed suggestions on the formulation of health policies in other poverty-stricken areas both at home and abroad.

The porous liquid (PLs) is a new material containing both permanent porosity of porous materials and liquid fluidity of solvent at room temperature, which has shown a great potential in gas separation. In this study, a novel type ? porous liquids were prepared using 2-methylimidazole zinc salt (ZIF-8) modified by tetraethylenepentamine (TEPA) as the main units and 1-Ethyl-3-methylimidazolium Bis(trifluoro-methanesulfonyl)-imide ([EMlm][NTf2]) as the sterically hindered solvent. The effect of amine loading on the CO2 absorption performance of PLs was investigated. When amine load was 30 wt%, 30TEPA@ZIF-8 not only had the pore structure inside but also effectively increased the CO2 absorption capacity of PLs. When the effect of different parameters on CO2 absorption capacity was investigated, it was found that the optimal adsorption temperature was 60 °C, and the optimal concentration of the main units was7.5 wt%. After five cycles, the absorbent's cycle efficiency and desorption efficiency were more than 98 %. All the results indicate that the prepared PLs in this paper had an application potential in CO2 capture.

This article presents an evaluation of the performance of a membrane-less organic-based flow battery using low-cost active materials, zinc and benzoquinone, which was scaled up to 1600 cm2, resulting in one of the largest of its type reported in the literature. The charge–discharge cycling of the battery was compared at different sizes and current densities, and its performance was evaluated under various mass transport and operating conditions. The results showed that the round-trip coulombic and voltage efficiencies were over 90% and 85%, respectively, for the laboratory-scale (1 cm2 electrode) cell, but these performances tended to deteriorate with the scaled-up (1600 cm2 electrode) cell due to inadequate mass transfer and sediment coverage of quinone, as well as the formation of a passivation film on the zinc anode. Despite this, the scaled-up batteries exhibited high coulombic and voltage efficiencies of up to 99% and 68.5%, respectively, at a current density of 10 mA cm−2. The capital cost of this system is also estimated to be several times lower than those of commercially available all-vanadium flow batteries and zinc bromide flow batteries for demand charge management applications.

Zinc-based hybrid-flow batteries are considered as a promising alternative to conventional electrochemical energy-storage systems for medium- to large-scale applications due to their high energy densities, safety, and abundance. However, the performance of these batteries has been limited by issues such as dendritic growth and passivation of zinc anodes during charge–discharge cycling. To address this challenge, a variety of two- and three-dimensional zinc anodes have been investigated. While two-dimensional zinc anodes have been extensively studied, there has been limited investigation into three-dimensional zinc anodes for hybrid-flow batteries. This study highlights the potential of three-dimensional zinc anodes to mitigate overpotentials and improve the mass transport of active species to promote negative electrode reactions. The performance of a membraneless flow battery based on low-cost zinc and organic quinone was herein evaluated using experimental and numerical approaches. Specifically, the use of zinc fiber was shown to yield an average coulombic efficiency of approximately 90% and an average voltage efficiency of approximately 82% over the course of 100 cycles at a current density of 30 mA cm−2. These results indicate the viability of using zinc fiber anodes to improve the performance of existing hybrid-flow batteries.

Abstract Flexibly and precisely manipulating 3D droplet transportation is a fundamental challenge for broad implications in diagnostics, drug delivery, bioengineering, etc. Herein, a light method is developed for manipulating a droplet to make it behave like a submarine. This light method enables flexible 3D transportation, stable suspension, and floating of a droplet, which can be freely altered. It is demonstrated that the localized photothermal effect induced thermocapillary flow in the water droplet/oil phase is responsible for energizing and manipulating the droplet. With such remarkable motility, the light‐fueled submarine‐like droplet successfully realizes various functions such as the acid‐base detection, particle capture and transportation, and target crystal collection, dissolution and transportation. It is demonstrated that the light‐fueled submarine‐like droplet shows promising perspective for long‐sought precise droplet manipulation in various applications.

A model of investment casting of a titanium alloy gearbox based on the ProCAST software was established in this work, and the simulated result was used to optimize the casting process. The flow and temperature field of casting were simulated based on an actual pouring process. Casting defects and the solidification process were analyzed. The results show that the defects can be predicted by the simulation result exactly, and the simulated temperature field is in accordance with the actual process. Shrinkage and porosity are observably alleviated by remodelling the casting mould. The casting temperature field and solidification simulation results show that the casting defects arise from hot spots and heat accumulation. The temperature-time curve of different representative location nodes of casting further confirms the defect simulation results. In addition, the use of low-cost alloy elements reduces raw material costs. Compared with TC4 alloy, the mechanical properties of the casting remain unchanged.

Aluminum fumarate metal organic frameworks (AlFu MOFs) pellet was successfully prepared with outstanding porous structure and its CO2 adsorption performance was investigated. As the binder mass increased, the pellet mechanical strength rose while the CO2 adsorption capacity reduced. The chosen AlFu pellet with 2.5wt% carboxymethyl cellulose sodium (CMC) binder retained the micro-morphology characteristics with a specific surface area of 726.06 m2/g and micropore volume of 0.33 cm3/g. The adsorption performance of CO2 by the pellets was studied at different partial pressures and temperatures. The results showed that the adsorption capacity of CO2 in AlFu pellet was increased with lower adsorption temperature and higher CO2 partial pressure, the maximum adsorption amount was 1.26 mmol/g at 35 °C and 1.0 bar. The CO2 adsorption kinetics and the limiting factors for adsorption rate were analyzed. Compared with pseudo-second order model the pseudo-first order kinetic model can better describe the CO2 physical adsorption behavior of AlFu pellet. The rate-limiting kinetic analysis revealed that the CO2 adsorption rate was determined by film diffusion and intra-particle diffusion rather than inter-particle diffusion.

The condensation of moist air is a common process in industry and increase its heat transfer coefficient is of great importance for improving energy efficiency. This study used 3-D finned tube to enhance moist air condensation, and the condensation process was calculated through numerical method aligned with Diffusion Layer model and Eulerian Wall Film model. The total heat transfer, sensible heat transfer and latent heat transfer during the condensation process were discussed. The results indicated that 3-D finned tube increased heat transfer amount and the condensation was mainly on fin surface. Besides, the influence of 3-D fin height was also obtained. The results indicated that the increase of fin height in circumferential direction can increase heat transfer in the tail of tube, and sensible heat transfer process was more sensitive to the area increment.

Tigernut has been recognized as a promising resource for edible oil and starch. However, the research on the quality characteristics of tigernut from different regions is lagging behind, which limits the application of tigernut in food industry. Tigernut tubers were obtained from six major growing regions in China, and the physicochemical properties of their main components, oil and starch, were characterized. Tigernut tubers from Baoshan contained the most oil (30.12%), which contained the most ß-carotene (130.4 µg/100 g oil) due to high average annual temperature. Gas chromatography analysis and fingerprint analysis results indicated that tigernut oil (TNO) consists of seven fatty acids, of which oleic acid is the major component. Changchun TNO contained the least total tocopherols (6.04 mg/100 g oil) due to low average annual temperature. Tigernut tubers from Chifeng (CF) contained the most starch (34.85%) due to the large diurnal temperature range. Xingtai starch contained the most amylose (28.4%). Shijiazhuang starch showed the highest crystallinity (19.5%). Anyang starch had the highest pasting temperature (76.0°C). CF starch demonstrated superior freeze-thaw stability (syneresis: 50%) due to low mean annual precipitation. The results could be further applied to support tigernut industries and relevant researchers that looks for geographical origin discrimination and improvements on tigernut quality, with unique physicochemical and technological properties. [ABSTRACT FROM AUTHOR]