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The disposal of fly ash with high salt content has become an important bottleneck for the further application of municipal solid waste incineration (MSWI). In this study, the soluble salt content and composition of fly ash from different MSWI were analysed. The composition of fly ash was affected by incinerator type and flue gas cleaning system, especially the type of deacidification solvent. The soluble salt content in fly ash from MSW grate incinerator can be over 35.16%. Most of the soluble salt was calcium salt and chloride salt. The effect of washing parameters including liquid/solid (L/S) ratio and washing time on salt removal from fly ash were studied. Raw fly ash contained high chlorine (Cl) with the maximum of 19.83% and it can be significantly reduced by washing. Double-washing and secondary-washing had better performance than single-washing on salt removal. The secondary-washing did not only save water, but also reduced the energy cost during evaporation for crystallising soluble salt. Based on the analysis of variance (ANOVA), L/S ratio was the most principal factor for salt and Cl removal of fly ash by washing. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effect of acute kidney injury (AKI) duration and severity on long-term renal functional outcomes in patients undergoing partial nephrectomy (PN). Methods: Altogether 292 consecutive patients undergoing laparoscopic PN from 2010 to 2018 were identified in two medical centers. In addition, the AKI duration {transient AK [≤ 3d] or persistent AKI [> 3d]} was combined with AKI severity (stages) to elucidate their relationships with long-term functional results. Kaplan–Meier (KM) analysis was also used to compare among patients with no AKI, transient AKI, and persistent AKI. Moreover, the Cox-proportional hazards regression model was utilized to assess the risk factors for renal function deterioration. Results: Altogether 67 patients (22.9%) experienced postoperative AKI. 75% eGFR preserve rate during the follow-up was compared among patients with no AKI, transient AKI and persistent AKI using KM analysis and log-rank test, which revealed significant difference. After adjusting for age and warm ischemia time by multivariate model proportional hazards analysis, AKI duration and severity were identified as the risk factors (Stage 1-transient AKI vs. non-AKI: adjusted hazard ratio (HR) 4.361, 95% confidential interval (CI) [2.062–9.233], p < 0.001; stage 1-persistent AKI vs. non-AKI: adjusted HR 6.706, 95% CI [2.405–18.699], p < 0.001; stage 2/3-transient AKI vs. non-AKI: adjusted HR 8.949, 95% CI [1.571–50.963], p = 0.014; stage 2/3-persistent AKI vs. non-AKI: adjusted HR 13.453, 95% CI [11.353–133.798], p = 0.027). Conclusions: The AKI duration after PN is an important risk factor for long-term renal functional deterioration. Besides, AKI duration combined with AKI severity can be more comprehensive to understand the role of AKI on ultimately renal function. Trial registration: Chinese ClinicalTrials: ChiCTR2000034080. [ABSTRACT FROM AUTHOR]

Porous SiO 2 mesoscale tubes (SiO 2 -pMT) impregnated with carbon in the pores within their tube walls were successfully prepared for the first time by making use of the Fe3+ assisted anchoring of dopamine (DA) on the surface of SiO 2 as carbon source, and thereby endowed with highly enhanced anode performances for Li-ion batteries. Typically, a reversible specific capacity of 512.8 mAh g−1 was achieved after 500 cycles at 1 A g−1 when the SiO 2 -pMT impregnated with carbon by Fe3+ assistance was used as anode material, which is about 10 times that of SiO 2 -pMT with no carbon impregnation and 25% higher than that of the SiO 2 -pMT with carbon impregnated at double the concentration of dopamine but in the absence of Fe3+ cations. It has been found that the carbon impregnation of the SiO 2 -pMT may be achieved more easily and homogeneously with the assistance of Fe3+ cations and, as a result, 3-dimensional porous carbon-networks with higher connectivity can be built up, which greatly facilitate the transport of electrons to more potential reaction sites where Li-ions are available and provide fast channel for Li-ions diffusion, leading to enhanced electrochemical kinetics, as unveiled by the differential capacity curves and electrochemical impedance spectra acquired at different intervals during the initial cycle. Furthermore, as shown by XPS data, such benefitial assistance of Fe3+ cations is believed to arise from their coupling effects between the phenolic hydroxyl groups of dopamine molecules and the surface of SiO 2 through the chemical bondings of C-O-Fe and Fe-O-Si. Fe3+-assisted carbon impregnation of porous SiO 2 mesoscale tubes (SiO 2 -pMT) with dopamine as carbon source (via path 1) leading to remarkable enhancement in carbon content, structural homogeneity, and anode performance in Li-ion battery in contrast to that achieved with no Fe3+-assistance (via path 2). [Display omitted] • Fe3+ was firstly introduced into dopamine for the fabrication of SiO 2 -pMT@iC. • The carbon impregnation was achieved more homogeneously with the assistance of Fe3+. • The coupling effect of Fe3+ exists through the chemical bonds of C-O-Fe and Fe-O-Si. • High connected porous carbon network enable SiO 2 -pMT@iC with enhanced performance. [ABSTRACT FROM AUTHOR]

The utilization of Mg Li alloy has garnered significant attention due to its potential for various applications. However, its vulnerability to corrosion remains a challenge that should be overcome for widespread use. In response to this challenge, we present a skin-inspired self-healing coating, applied to micro-arc oxidation (MAO)-treated Mg Li alloy. The coating is composed of epoxy resin, polyvinyl alcohol (PVA) and tannic acid (TA). Like the animal skin, epoxy resin acts as the epidermis, which blocks the invasion of the external corrosive species. Even being damaged by the mechanical effect, the inner PVA and TA polymer connects by hydrogen bonding, which exhibits a swelling effect in aqueous medium to heal the damage area. Even water penetrates into the underneath substrate, TA as the corrosion inhibitor will react with Mg2+ to form tannate as the inner layer to prohibit further corrosion. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy and atomic force microscopy are utilized to characterize the microstructure, chemical composition and topology of the coating. Corrosion protection experiments demonstrate that the MAO-PVA/TA-epoxy coating exhibits high anti-corrosion ability compared to MAO-PVA/TA and MAO coating. The |Z| 0.01Hz value of 1.13 × 109 Ω cm2 is two and six orders of magnitude higher than the other two coatings. An in-depth comprehension of the self-healing process is achieved through ex situ examination utilizing SEM and energy-dispersive spectroscopy techniques. For real-time observation of the self-healing process of the coating, we employ a scanning vibrating electrode technique and a three-dimensional digital microscope. The reported coating, endowed with self-healing capabilities, holds tremendous promise for expanding the scope of applications for Mg Li alloy in the realm of science and engineering. • A skin-inspired sandwiched coating is prepared for shielding Mg Li alloy from corrosion. • The skin-inspired coating exhibits high self-healing property under external attack. • The self-healing is based on polymer swelling, H-bonding formation and Mg-tannic acid coordination. [ABSTRACT FROM AUTHOR]

This study is devoted to analytically establish macro–micro quantitative relationships for creep characteristics of a rheological particle assembly, contributing to a more comprehensive insight into the interplay between different scales. To represent the various rheological behaviour in microscopic for a hexagonal close-packed (HCP) circular particle assembly, the contact responses are assumed as viscoelastic models. By extending the traditional homogenization method to the Laplace domain, the macroscopic one/two-dimensional creep equations of the rheological particle assembly, expressed with the microscopic contact parameters in a closed-form manner, are innovatively identified. It is found that the macroscopic creep behaviour is not always consistent with the microscopic one and in general exhibits more complex creep characteristics. The parametric analysis presents the quantitative influence of contact parameters on macroscopic creep behaviour. Extending the one-dimensional case to three dimensions (3D), the relaxation moduli as well as creep compliance, expressed in closed-form by contact parameters, are obtained in 3D viscoelastic constitutive equations. Distinct viscoelastic behaviours are observed for macroscopic shear and bulk responses. The proposed macro–micro quantitative relations of creep characteristics in this study benefit to deeply understand the macro–micro relations of viscoelastic properties, providing an alternative approach to calibrate microscopic parameters when involving the DEM simulations. [ABSTRACT FROM AUTHOR]

Accurate photovoltaic (PV) power forecast is crucial for carbon neutrality. Current researches on PV power forecast mainly focus on using temporal information from single PV station, and the spatial information in multiple PV power stations are often neglected. To address this problem, this paper introduces Moran index to verify the spatial autocorrelation of PV power for the first time, uses Granger causality test and transfer entropy to reveal the spatial information gain in PV power forecast for the first time, and proposes a novel spatial–temporal probabilistic PV forecast method using deep Graph Gated Recurrent Unit (GraphGRU) network-based spatial–temporal multi-task learning and Kernel Density Estimation (KDE). Deep GraphGRU combines the advantages of Graph Convolutional Network (GCN) in spatial feature extraction and the advantages of Gated Recurrent Unit (GRU) network in temporal feature extraction, and thus has strong ability to extract spatial–temporal information in historical data of multiple different PV power stations. Through GraphGRU, temporal dependency information extracted from historical data of multiple PV stations can promote each other to improve the forecast accuracy of each PV stations. KDE is used for estimating the joint probabilistic density function and giving the spatial–temporal probabilistic confidence interval of PV power. Experiments were performed in the five-year actual PV power data from 11 provinces of Belgium and the three-year solar irradiation data from 12 places in China to verify the superiorities of the proposed method. Comparison with conventional spatial–temporal and temporal forecast methods show that the proposed GraphGRU-based spatial–temporal forecast method can extract the spatial–temporal information from multiple PV power stations well and significantly outperform conventional temporal forecast methods. [ABSTRACT FROM AUTHOR]

• Developed a universal gas turbine circumferential temperature distribution model for combustion system fault detection. • Revealed the influence modes of interference factors and faults on EGT distribution. • Proposed a combustion system fault detection method based on EGT dispersion. • Validated the effectiveness of the revealed rules and proposed method with actual operational data. The gas turbine combustion system operates under harsh conditions, and any faults such as nozzle clogging, cracks, etc. can endanger the downstream components and cause catastrophic accidents. Thus, monitoring the combustion system status and detecting its performance degradation timely are crucial for gas turbine safety. The current predominant method for monitoring involves analyzing exhaust gas temperature (EGT) dispersion, utilizing thermocouples placed at the turbine outlet to indirectly assess combustion system performance. However, the EGT is affected not only by faults but also by various non-fault disturbances, such as operational conditions, atmospheric variations, compressor performance degradation, and uneven hot gas mixing and rotating. To improve the sensitivity of fault detection, it is necessary to investigate how various factors affect the EGT dispersion and differentiate between EGT changes due to interference and those due to combustion system faults. However, using actual operational data from gas turbines to analyze and reveal these impact mechanisms is challenging. Therefore, this paper develops a gas turbine model for combustion system fault detection that accurately reflects the uneven circumferential distribution of EGT. The model incorporates a multi-combustor burner, a multi-channel turbine, and a module for simulating the mixing and rotating of the hot gas. Using this model, simulations are conducted to study the effects of non-fault interference factors, such as variations in ambient temperature, fuel flow changes, and compressor performance degradation, on EGT distribution. Additionally, simulations are conducted to analyze the effects of faults, including combustor cracks, uneven fuel distribution, and the coupling of interferences with faults, on EGT distribution. By comparing the normal and abnormal modes, the study reveals the different EGT responses due to non-fault interferences and combustion system faults. Based on these findings, a fault detection method for coupled conditions is proposed. The research results provide a basis for the fault detection of combustion system, enabling practitioners to reduce interference in fault detection and to increase the detection sensitivity. [ABSTRACT FROM AUTHOR]

The commonly used trial-and-error approach on selecting appropriate inter-particle parameters in DEM simulations incurs criticism such as user dependence and high computational cost. This study proposes a new framework based on a multi-fidelity residual neural network (MR-NN) as an alternative for calibrating inter-particle parameters in rock-like bonded granular materials. The model is first trained using low-fidelity data (LF) to focus on capturing the main underpinning correlations between macroscopic elastic and strength parameters with inter-particle parameters of contact models, where the LF data is generated from micro-macro quantitative relations. Subsequent training on sparser high-fidelity (HF) data is then used to calibrate and refine the model, in which the HF data is generated from DEM simulations for rock. Feedforward neural network (FNN) is considered as the baseline algorithm for training models. The trained MR-NN with the same LF data is finally used to predict the inter-particle parameters of calcarenite and granite in DEM simulations to examine its feasibility and generalization ability. Furthermore, the robustness of the framework is verified by discussing the effect of LF data on the performance of MR-NN. All results demonstrate that the proposed method can provide a fast and accurate determination of inter-particle parameters for DEM simulation. [ABSTRACT FROM AUTHOR]

The high contents of Ni, Co, and Mn in the retired cathode of ternary lithium-ion battery (rCTLIB) make it a promising raw precursor for preparing value-added reactive materials. However, most strategies for valorizing the rCTLIB highly depend on chemical leaching of Ni, Co, and Mn through complex procedures that involve the use of harsh liquids. Valorizing the rCTLIB through simple physical pathways is highly promising. Chemical looping combustion (CLC) is an innovative technology for producing energy from fossil fuels while inherently separating the resulting CO 2 into a nearly pure stream for subsequent permanent storage or utilization. In this study, high-performance oxygen carrier (OC) materials for the CLC of syngas have been successfully synthesized using a facile and scalable method that physically pelletizes the rCTLIB with Al 2 O 3 binder. Performance tests show that the H 2 and CO conversions in CLC of syngas exceed 90% for all prepared OCs. This performance is comparable to that of popularly employed OCs based on supported oxides. Moreover, the obtained OCs physically prepared from the rCTLIB demonstrate high stability with respect to reactivity and oxygen transport capacity, indicating a high potential for valorizing the rCTLIB into high-performance materials for applications involving CO 2 capture. [Display omitted] • A new strategy towards the valorization of retired cathode has been established. • High-performance oxygen carrier is synthesized non-chemically from retired cathode. • The oxygen carrier has been used for the chemical looping combustion of syngas. • Introducing Al 2 O 3 binder and pre-cycling Li improves the cyclic stability. • The optimized oxygen carrier exhibits syngas conversion over 90%. [ABSTRACT FROM AUTHOR]

Communication and interaction with machines are changing our ways of life. However, developing an acoustic interface that simultaneously features waterproofness, wearability, high fidelity, and high accuracy for human–machine interaction remains a grand challenge. Herein, a waterproof acoustic sensor (WAS) as a wearable translation interface to communicate with machines is reported. Owing to the sound‐response ability of internal microparticles, the WAS holds a significantly broad frequency response range of 0.1–20 kHz, covering almost the entire human audible range. The WAS is stable against human perspiration, shows omnidirectional response, and displays an excellent frequency detection resolution of 0.0001 kHz. With a collection of compelling features, the WAS can serve as a wearable acoustic human–machine interface and a high‐fidelity auditory platform for music recording. Moreover, the WAS‐based acoustic interface holds a remarkable 98% accuracy for speech recognition with the assistance of an artificial intelligence algorithm. Finally, the WAS‐based acoustic interface demonstrates speaker verification and identification for implementation in highly secure biometric authentication systems and wireless control of an intelligent car using speech recognition. Such a WAS‐based acoustic interface represents the advancement of high‐fidelity translation platforms for human–machine interactions toward practical applications, including the Internet of Things, assistive technology, and intelligent recognition systems. [ABSTRACT FROM AUTHOR]

Spinel configuration is a kind of broadly considered host candidate when designing persistent luminescence (PersL) materials due to the easy generation of vacancies and anti‐site defects. Here, a new strategy of defect enrichment for the activation of PersL is proposed, and in contrast to the spinel configuration, it is demonstrated that the crystal structure of near inverse spinel ensures more numerous defects to activate the near‐infrared (NIR) PersL of Fe3+. Fe3+‐doped MgGa2O4 displays the PersL band in the range of 600 to 900 nm and possesses a super‐long PersL duration time >15 h. The optical analysis and the calculation of density functional theory unravel that the near inverse spinel structure can lower the carrier transfer barriers to accelerate the formation of carrier trap states within the bandgap. Therefore, more numerous defects in this structure may participate in the trapping and de‐trapping process by comparison with the normal spinel configuration. These findings are expected to accelerate the development of new PersL materials through Fe3+ doping toward versatile biological applications in NIR window. [ABSTRACT FROM AUTHOR]

Spinel configuration is a kind of broadly considered host candidate when designing persistent luminescence (PersL) materials due to the easy generation of vacancies and anti‐site defects. Here, a new strategy of defect enrichment for the activation of PersL is proposed, and in contrast to the spinel configuration, it is demonstrated that the crystal structure of near inverse spinel ensures more numerous defects to activate the near‐infrared (NIR) PersL of Fe3+. Fe3+‐doped MgGa2O4 displays the PersL band in the range of 600 to 900 nm and possesses a super‐long PersL duration time >15 h. The optical analysis and the calculation of density functional theory unravel that the near inverse spinel structure can lower the carrier transfer barriers to accelerate the formation of carrier trap states within the bandgap. Therefore, more numerous defects in this structure may participate in the trapping and de‐trapping process by comparison with the normal spinel configuration. These findings are expected to accelerate the development of new PersL materials through Fe3+ doping toward versatile biological applications in NIR window. [ABSTRACT FROM AUTHOR]