Search Results (16)

The electrochemical decomposition of HI_x solution presents a promising alternative to overcome the challenges associated with HI thermal decomposition in the sulfur–iodine (S-I) cycle. In this study, constant current electrolysis and LSV tests were carried out for HI_x solution using an H-type electrolyzer at different current densities and anode solution compositions. The results showed that during the process of HI electrolysis, the dominant factor of voltage variation gradually changed from electrochemical polarization to ohmic polarization as the current density increased. When the I₂ concentration in the HI solution approached saturation, a voltage step occurred in the constant current electrolysis, reaching a maximum amplitude of 127.69%. The analysis indicated that the voltage step was related to the I₂ deposition on the electrode and PEM, which led to the simultaneous increase in activation polarization and ohmic polarization overpotential. The increase in I₂ concentration decreased the limiting diffusion current density; I₂ supersaturation led to the formation of an insoluble iodine film on the electrode surface, ultimately terminating the electrochemical reaction. This study provides guidance for the development of HI_x solution electrolysis technology for hydrogen production. Full article

In the thermochemical sulfur–iodine water splitting cycle for hydrogen production, the hydrogen iodide (HI) decomposition reaction serves as the rate-determining step, and its high efficiency relies on the precise design of active sites on the catalyst. This paper combines experimental characterization with density functional theory (DFT) calculations, focusing on activated carbon catalysts. By regulating the types and contents of oxygen-containing functional groups through H₂ reduction treatment at different temperatures, the influence of oxygen-containing functional groups on HI decomposition was investigated. The results show that H₂ reduction treatment can gradually remove oxygen-containing functional groups such as carboxyl, hydroxyl, and carbonyl groups on the surface of activated carbon without significantly affecting the pore structure. Catalytic activity tests conducted under the typical reaction temperature of 500 °C confirmed that as the content of oxygen-containing functional groups decreases, the HI decomposition efficiency increases. DFT calculations further revealed the role of oxygen-containing functional groups: they inhibit the chemisorption of reactant HI on unsaturated carbon atoms and alter the desorption activation energy of product H₂, thereby affecting the overall reaction process. This study provides important theoretical guidance and experimental basis for designing efficient HI decomposition catalysts. Full article

This paper reports the latest update to and a 24 h continuous operation test of the CEU’s thermochemical iodine–sulfur cycle water-splitting system with a maximum H₂ hydrogen production capacity of 1500 L/h. To address challenges such as high energy consumption and severe corrosion in traditional processes, the system was updated and optimized by introducing a small-cycle design, simulated using Aspen Plus software, achieving a thermal efficiency of 53%. Specifically, the key equipment improvements included a three-stage H₂SO₄ decomposition reactor and an HI decomposition reactor with heat recovery, resolving issues of severe corrosion when H₂SO₄ boils and reducing heat loss. During 24 h continuous operation in January 2025, the system achieved a peak hydrogen production rate of 1536 L/h and a long-term stable rate of approximately 300 L/h, with hydrogen purity reaching up to 98.75%. This study validates the potential for the scaling up of iodine–sulfur cycle hydrogen production technology, providing engineering insights for efficient and clean hydrogen energy production. Full article

Serpentine (Mg₃Si₂O₅(OH)₄), like quartz, dolomite and magnesite minerals, is a versatile mineral group characterized by silica and magnesium silicate contents with multiple polymorphic phases. Among the phases composed of antigorite, lizardite, and chrysotile, lizardite and chrysotile are the most prevalent phases in the serpentinites studied here. The formation process of serpentinites, which arise from the hydrothermal alteration of peridotites, influences the ratio of light rare earth elements (LREE) to heavy rare earth elements (HREE). In serpentinites, the ratio of light rare earth elements (LREE)/heavy rare earth elements (HREE) provides insights into formation conditions, geochemical evolution, and magmatic processes. The depletion of REE compositions in serpentinites indicates high melting extraction for fore-arc/mantle wedge serpentinites. The studied serpentinites show a depletion in REE concentrations compared to chondrite values, with HREE exhibiting a lesser degree of depletion compared to LREE. The high ΣLREE/ΣHREE ratios of the samples are between 0.16 and 4 ppm. While Ce shows a strong negative anomaly (0.1–12), Eu shows a weak positive anomaly (0.1–0.3). This indicates that fluid interacts significantly with rock during serpentinization, and highly incompatible elements (HIEs) gradually become involved in the serpentinization process. While high REE concentrations indicate mantle wedge serpentinites, REE levels are lower in mid-ocean ridge serpentinites. The enrichment of LREE in the analyzed samples reflects melt/rock interaction with depleted mantle and is consistent with rock–water interaction during serpentinization. The gradual increase in highly incompatible elements (HIEs) suggests that they result from fluid integration into the system and a subduction process. The large differential thermal analysis (DTA) peak at 810–830 °C is an important sign of dehydration, transformation reactions and thermal decomposition, and is compatible with H₂O phyllosilicates in the mineral structure losing water at this temperature. In SEM images, chrysotile, which has a fibrous structure, and lizardite, which has a flat appearance, transform into talc as a result of dehydration with increasing temperature. Therefore, the sudden temperature drop observed in DTA graphs is an indicator of crystal form transformation and CO₂ loss. In this study, the mineralogical and structural properties and the formation of serpentinites were examined for the first time using thermo-gravimetric analysis methods. In addition, the mineralogical and physical properties of serpentinites can be recommended for industrial use as additives in polymers or in the adsorption of organic pollutants. As a result, the high refractory nature of examined serpentine suggests that it is well-suited for applications involving high temperatures. This includes industries such as metallurgy and steel production, glass manufacturing, ceramic production, and the chemical industry. Full article

In the process industrial systems, flow control valves are deemed vital components that ensure the system’s safe operation. Hence, detecting faults in control valves is of significant importance. However, the stable operating conditions of flow control valves are prone to change, resulting in a decreased effectiveness of the conventional fault detection method. In this paper, an online fault detection approach considering the variable operating conditions of flow control valves is proposed. This approach is based on residual analysis, combining LightGBM online model with Seasonal and Trend decomposition using Loess (STL). LightGBM is a tree-based machine learning algorithm. In the proposed method, an online LightGBM is employed to establish and continuously update a flow prediction model for control valves, ensuring model accuracy during changes in operational conditions. Subsequently, STL decomposition is applied to the model’s residuals to capture the trend of residual changes, which is then transformed into a Health Index (HI) for evaluating the health level of the flow control valves. Finally, fault occurrences are detected based on the magnitude of the HI. We validate this approach using both simulated and real factory data. The experimental results demonstrate that the proposed method can promptly reflect the occurrence of faults through the HI. Full article

Topologically associated domains (TADs) represent essential units constituting chromatin’s intricate three-dimensional spatial organization. TADs are stably present across cell types and species, and their influence on vital biological processes, such as gene expression, DNA replication, and chromosomal translocation, underscores their significance. Accordingly, the identification of TADs within the Hi-C interaction matrix is a key point in three-dimensional genomics. TADs manifest as contiguous blocks along the diagonal of the Hi-C interaction matrix, which are characterized by dense interactions within blocks and sparse interactions between blocks. An optimization method is proposed to enhance Hi-C interaction matrix data using the empirical mode decomposition method, which requires no prior knowledge and adaptively decomposes Hi-C data into a sum of multiple eigenmodal functions via exploiting the inherent characteristics of variations in the input Hi-C data. We identify TADs within the optimized data and compared the results with five commonly used TAD detection methods, namely the Directionality Index (DI), Interaction Isolation (IS), HiCKey, HiCDB, and TopDom. The results demonstrate the universality and efficiency of the proposed method, highlighting its potential as a valuable tool in TAD identification. Full article

Functional dissociation of brain neural activity induced by opening or closing the eyes has been well established. However, how the temporal dynamics of the underlying neuronal modulations differ between these eye conditions during movement-related behaviours is less known. Using a robotic-assisted motor imagery brain-computer interface (MI BCI), we measured neural activity over the motor regions with electroencephalography (EEG) in a stroke survivor during his longitudinal rehabilitation training. We investigated lateralized oscillatory sensorimotor rhythm modulations while the patient imagined moving his hemiplegic hand with closed and open eyes to control an external robotic splint. In order to precisely identify the main profiles of neural activation affected by MI with eyes-open (MIEO) and eyes-closed (MIEC), a data-driven approach based on parallel factor analysis (PARAFAC) tensor decomposition was employed. Using the proposed framework, a set of narrow-band, subject-specific sensorimotor rhythms was identified; each of them had its own spatial and time signature. When MIEC trials were compared with MIEO trials, three key narrow-band rhythms whose peak frequencies centred at ∼8.0 Hz, ∼11.5 Hz, and ∼15.5 Hz, were identified with differently modulated oscillatory dynamics during movement preparation, initiation, and completion time frames. Furthermore, we observed that lower and higher sensorimotor oscillations represent different functional mechanisms within the MI paradigm, reinforcing the hypothesis that rhythmic activity in the human sensorimotor system is dissociated. Leveraging PARAFAC, this study achieves remarkable precision in estimating latent sensorimotor neural substrates, aiding the investigation of the specific functional mechanisms involved in the MI process. Full article

Precise and dependable wind speed forecasting (WSF) enables operators of wind turbines to make informed decisions and maximize the use of available wind energy. This study proposes a hybrid WSF model based on outlier correction, heuristic algorithms, signal decomposition methods, and DLinear. Specifically, the hybrid model (HI-IVMD-DLinear) comprises the Hampel identifier (HI), the improved variational mode decomposition (IVMD) optimized by grey wolf optimization (GWO), and DLinear. Firstly, outliers in the wind speed sequence are detected and replaced with the HI to mitigate their impact on prediction accuracy. Next, the HI-processed sequence is decomposed into multiple sub-sequences with the IVMD to mitigate the non-stationarity and fluctuations. Finally, each sub-sequence is predicted by the novel DLinear algorithm individually. The predictions are reconstructed to obtain the final wind speed forecast. The HI-IVMD-DLinear is utilized to predict the real historical wind speed sequences from three regions so as to assess its performance. The experimental results reveal the following findings: (a) HI could enhance prediction accuracy and mitigate the adverse effects of outliers; (b) IVMD demonstrates superior decomposition performance; (c) DLinear has great prediction performance and is suited to WSF; and (d) overall, the HI-IVMD-DLinear exhibits superior precision and stability in one-to-four-step-ahead forecasting, highlighting its vast potential for application. Full article

Ethylene-Vinyl Acetate (EVA) copolymer was synthesized from ethylene and vinyl acetate at high temperatures and ultra-high pressures. In this condition, any reactor disturbances, such as process or mechanical faults, may trigger the run-away decomposition reaction. This paper proposes a procedure for constructing a conditional health status prediction structure that uses a virtual health index (HI) to monitor the reactor bearing’s remaining useful life (RUL). The piecewise linear remaining useful life (PL-RUL) model was constructed by machine learning regression methods trained on the vibration and distributed control system (DCS) datasets. This process consists of using Welch’s power spectrum density transformation and machine learning regression methods to fit the PL-RUL model, following a health status construction process. In this research, we search for and determine the optimum value for the remaining useful life period (T_RUL), a key parameter for the PL-RUL model for the system, as 70 days. This paper uses four-fold cross-validation to evaluate seven different regression algorithms and concludes that the Extremely randomized trees (ERTs) is the best machine learning model for predicting PL-RUL, with an average relative absolute error (RAE) of 0.307 and a Linearity of 15.064. The Gini importance of the ensemble trees is used to identify the critical frequency bands and prepare them for additional dimensionality reduction. Compared to two frequency band selection techniques, the RAE and Linearity prediction results can be further improved to 0.22 and 8.38. Full article

In this work, a novel structure of a hydrogen-membrane reactor coupling HI decomposition and CO₂ methanation was proposed, and it was based on the adoption of silica membranes instead of metallic, according to their ever more consistent utilization as nanomaterial for hydrogen separation/purification. A 2D model was built up and the effects of feed flow rate, sweep gas flow rate and reaction pressure were examined by CFD simulation. This work well proves the feasibility and advantage of the membrane reactor that integrates HI decomposition and CO₂ methanation reactions. Indeed, two membrane reactor systems were compared: on one hand, a simple membrane reactor without proceeding towards any CO₂ methanation reaction; on the other hand, a membrane reactor coupling the HI decomposition with the CO₂ methanation reaction. The simulations demonstrated that the hydrogen recovery in the first membrane reactor was higher than the methanation membrane reactor. This was due to the consumption of hydrogen during the CO₂ methanation reaction, occurring in the permeate side of the second membrane reactor system, which lowered the amount of hydrogen recovered in the outlet streams. After model validation, this theoretical study allows one to evaluate the effect of different operating parameters on the performance of both the membrane reactors, such as the pressure variation between 1 and 5 bar, the feed flow rate between 10 and 50 mm³/s and the sweep gas flow rate between 166.6 and 833.3 mm³/s. The theoretical predictions demonstrated that the best results in terms of HI conversion were 74.5% for the methanation membrane reactor and 67% for the simple membrane reactor. Full article

Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article, a combination of one-step-based method based on the generalized eigenvalue decomposition (GEVD), and a two-step-based method based on the adaptive generalized cross-correlation (GCC) by using the phase transform/maximum likelihood (PHAT/ML) filters along with a novel T-shaped circular distributed microphone array (TCDMA) is proposed for 3D multiple simultaneous SSL. In addition, the low computational complexity advantage of the GCC algorithm is considered in combination with the high accuracy of the GEVD method by using the distributed microphone array to eliminate spatial aliasing and thus obtain more appropriate information. The proposed T-shaped circular distributed microphone array-based adaptive GEVD and GCC-PHAT/ML algorithms (TCDMA-AGGPM) is compared with hierarchical grid refinement (HiGRID), temporal extension of multiple response model of sparse Bayesian learning with spherical harmonic (SH) extension (SH-TMSBL), sound field morphological component analysis (SF-MCA), and time-frequency mixture weight Bayesian nonparametric acoustical holography beamforming (TF-MW-BNP-AHB) methods based on the mean absolute estimation error (MAEE) criteria in noisy and reverberant environments on simulated and real data. The superiority of the proposed method is presented by showing the high accuracy and low computational complexity for 3D multiple simultaneous SSL. Full article

Polyurethanes (PU) are one of the most-used classes of synthetic polymers in Europe, having a considerable impact on the plastic waste management in the European Union. Therefore, they represent a major challenge for the recycling industry, which requires environmentally friendly strategies to be able to re-utilize their monomers without applying hazardous and polluting substances in the process. In this work, enzymatic hydrolysis of a polyurethane-polyester (PU-PE) copolymer using Humicola insolens cutinase (HiC) has been investigated in order to achieve decomposition at milder conditions and avoiding harsh chemicals. PU-PE films have been incubated with the enzyme at 50 °C for 168 h, and hydrolysis has been followed throughout the incubation. HiC effectively hydrolysed the polymer, reducing the number average molecular weight (M_n) and the weight average molecular weight (M_w) by 84% and 42%, respectively, as shown by gel permeation chromatography (GPC), while scanning electron microscopy showed cracks at the surface of the PU-PE films as a result of enzymatic surface erosion. Furthermore, Fourier Transform Infrared (FTIR) analysis showed a reduction in the peaks at 1725 cm⁻¹, 1164 cm⁻¹ and 1139 cm⁻¹, indicating that the enzyme preferentially hydrolysed ester bonds, as also supported by the nuclear magnetic resonance spectroscopy (NMR) results. Liquid chromatography time-of-flight/mass spectrometry (LC-MS-Tof) analysis revealed the presence in the incubation supernatant of all of the monomeric constituents of the polymer, thus suggesting that the enzyme was able to hydrolyse both the ester and the urethane bonds of the polymer. Full article

The sulfur-iodine (SI) cycle holds great promise as an alternative large-scale process for converting water into hydrogen without CO₂ emissions. A major issue regarding the long-term stability and activity of the catalysts is their poor sulfur deactivation resistance in the HI feeding process. In this work, the effect of Ru addition for enhancing the activity and sulfur resistance of SiO₂-supported Ni catalysts in the HI decomposition reaction has been investigated. The presence of H₂SO₄ molecules in the HI results in severe sulfur deactivation of the Ru-free Ni/SiO₂ catalysts by blocking the active sites. However, Ni–Ru/SiO₂ catalysts show higher catalytic activity without sulfur-poisoning by 25% and exhibit more superior catalytic performance than the Ru-free catalyst. The addition of Ru to the Ni/SiO₂ catalyst promotes the stability and activity of the catalysts. The experimental trends in activity and sulfur tolerance are consistent with the theoretical modeling, with the catalytic activities existing in the order Ni/SiO₂ < Ni–Ru/SiO₂. The effect of Ru on the improvement in sulfur resistance over Ni-based catalysts is attributed to electronic factors, as evidenced by theory modeling analysis and detailed characterizations. Full article

The thermochemical sulfur-iodine cycle is a potential method for hydrogen production, and the hydrogen iodide (HI) decomposition is the key step to determine the efficiency of hydrogen production in the cycle. To further reduce the irreversibility of various transmission processes in the HI decomposition reaction, a one-dimensional plug flow model of HI decomposition tubular reactor is established, and performance optimization with entropy generate rate minimization (EGRM) in the decomposition reaction system as an optimization goal based on finite-time thermodynamics is carried out. The reference reactor is heated counter-currently by high-temperature helium gas, the optimal reactor and the modified reactor are designed based on the reference reactor design parameters. With the EGRM as the optimization goal, the optimal control method is used to solve the optimal configuration of the reactor under the condition that both the reactant inlet state and hydrogen production rate are fixed, and the optimal value of total EGR in the reactor is reduced by 13.3% compared with the reference value. The reference reactor is improved on the basis of the total EGR in the optimal reactor, two modified reactors with increased length are designed under the condition of changing the helium inlet state. The total EGR of the two modified reactors are the same as that of the optimal reactor, which are realized by decreasing the helium inlet temperature and helium inlet flow rate, respectively. The results show that the EGR of heat transfer accounts for a large proportion, and the decrease of total EGR is mainly caused by reducing heat transfer irreversibility. The local total EGR of the optimal reactor distribution is more uniform, which approximately confirms the principle of equipartition of entropy production. The EGR distributions of the modified reactors are similar to that of the reference reactor, but the reactor length increases significantly, bringing a relatively large pressure drop. The research results have certain guiding significance to the optimum design of HI decomposition reactors. Full article

Peer-to-peer markets are especially suitable for the analysis of online ratings as they represent two-sided markets that match buyers to sellers and thus lead to reduced scope for opportunistic behavior. We decompose the online ratings by focusing on the customer’s decision-making process in a leading peer-to-peer ridesharing platform. Using data from the leading peer-to-peer ridesharing platform BlaBlaCar, we analyze 17,584 users registered between 2004 and 2014 and their online ratings focusing on the decomposition of the explicit determinants reflecting the variance of online ratings. We find clear evidence to suggest that a driver’s attitude towards music, pets, smoking, and conversation has a significantly positive influence on his received online ratings. However, we also show that the interaction of female drivers and their attitude towards pets has a significantly negative effect on average ratings. Full article