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Detecting hydrogen leaks remains a pivotal challenge demanding robust solutions. Among diverse detection techniques, the fiber-optic method distinguishes itself through unique benefits, such as its distributed measurement properties. The adoption of hydrogen-sensitive materials coated on fibers has gained significant traction in research circles, credited to its operational simplicity and exceptional adaptability across varied conditions. This manuscript offers an exhaustive investigation into hydrogen-sensitive materials and their incorporation into fiber-optic hydrogen sensors. The research profoundly analyzes the sensor architectures, performance indicators, and the spectrum of sensing materials. A detailed understanding of these sensors' potentials and constraints emerges through rigorous examination, juxtaposition, and holistic discourse. Furthermore, this analysis judiciously assesses the inherent challenges tied to these systems, simultaneously highlighting potential pathways for future innovation. By spotlighting the hurdles and opportunities, this paper furnishes a view on hydrogen sensing technology, particularly related to optical fiber-based applications. [ABSTRACT FROM AUTHOR]

Ships and other mobile pollution sources emitted massive ultrafine and low-resistivity particles containing black carbon (BC), which were harmful to human health and were difficult to capture by conventional electrostatic precipitators (ESPs). In this study, nanoscale carbon black was adopted as simulated particles (SP) with similar physicochemical properties for black carbon emitted from ships (SP-BC) to investigate the feasibility of using an ESP with square-grooved collecting plates for the removal of SP-BC at low backpressures. The increased applied voltage significantly improved the total collection of SP-BC whereas may also promote the conversion of relatively larger particle size SP-BC into nano-size below 20 nm. The outlet number concentration of SP-BC under 27 kV at 130°C was three times that of the inlet. While the reduction of the flow rate could strengthen the capture of SP-BC below 20 nm, and under the combined action of low flow rate and maximum applied voltage, the collection efficiency of 20-100 nm SP-BC could exceed 90%. In addition, the escape and capture characteristics of SP-BC under long-term rapping were revealed. The square-grooved collecting plate could effectively restrain the re-entrainment of collected SP-BC generated by rapping, and the nanoscale SP-BC was trapped in the grooves after rapping. The results could provide insights into the profound removal of massive nanoscale black carbon emissions from mobile sources. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-stage circulation integrated SO 2 and CO 2 capture, coupled with NH 3 recovery. • Over 99.5% SO 2 and 70% CO 2 was captured with desorption duty of 2.48 GJ/t CO 2. • Adaptable strategies balanced efficiency and economy amid complex conditions. Amidst growing environmental concerns stemming from fossil fuel combustion, which releases a considerable amount of pollutants and greenhouse gas. In an effort to mitigate the costs of existing combustion flue gas desulfurization and CO 2 capture systems, a new multi-stage circulation (MSC) process for integrating capture of CO 2 and SO 2 using ammonia-based absorbents was proposed. Different functional zones were interconnected using ammonia (NH 3) and potassium carbonate (K 2 CO 3) blended solution as the absorbent, enabling efficient SO 2 capture in the 1st stage, CO 2 enrichment in the 2nd stage, CO 2 capture enhancement in the 3rd stage and recovery of escaped NH 3 in the 4th stage. Experimental results demonstrated the effectiveness of NH 3 /K 2 CO 3 solution in enhancing CO 2 capture efficiency. The overall CO 2 capture efficiency varied between 95.4 % and 84.1 % at inlet CO 2 concentrations ranging from 5 % to 30 %. Under typical combustion flue gas conditions of 622 ppm SO 2 and 15 vol% CO 2 , the process exhibited a SO 2 removal efficiency exceeding 99.5 %, with CO 2 capture efficiency surpassing 70 %. Furthermore, the CO 2 desorption duty was determined to be 2.48 GJ/t CO 2. 13C NMR results confirmed that simultaneous absorption of CO 2 and SO 2 led to the accumulation of SO 2 in the liquid phase, reducing the CO 2 loading in rich solvent. To address these challenges, coupled optimization strategies was proposed, ensuring high capture efficiency and low CO 2 desorption duty under the complex and variable conditions of flue gas parameters, SO 2 concentration, and CO 2 concentration. [ABSTRACT FROM AUTHOR]

The demand for gases detection has promoted extensive research into gas sensors. Sensor arrays can be used as electronic olfaction units for complex gas detection and identification. However, the gas sensing properties are affected by various factors. The multi-dimensional nature of those interactions is crucial for creating a sensor array with diverse responses, but it is also challenging to fabricate an array considering all these parameters, particularly in miniaturization. In this paper, we present a framework that can take multiple factors into consideration and help to fabricate an optimal array for gas identification. 32 sensors including different MOS materials (SnO 2 , In 2 O 3 , WO 3), morphologies (microsphere, nanoparticle, nanoflake), doped/loaded metals (Pd, Pt, Ce, Ru, Rb), and operational temperatures (250℃∼370℃) are discussed. A material-temperature-analyte-response database was then established by storing their response characteristics towards low ppm concentrations of ammonia, ethyl acetate, toluene, methanol, ethanol, and acetone. An optimized array was then constructed out of 10,518,300 possible combinations of materials and operational temperatures. Results showed improvements in discrimination ability and the optimized array integrated into the chip can provide vector signals with high selectivity, completely recognizing all the 6 target gases and even for their multi-component mixture after linear discriminant analysis transformation. [Display omitted] • An on-chip microarray platform considering multiple factors. • An effective and operational method to reasonably optimize the array. • A highly selective array capable of distinguish different gases and mixtures. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

• A normal behavior model of slurry circulating pump is established. • K-means algorithm is used to realize the operational condition recognition. • Memory matrix adaptive to varying operating condition are constructed. • The condition monitoring method can realize the early fault warning of the slurry circulating pump. The slurry circulating pump, a crucial component of wet flue gas desulfurization (WFGD) systems, often encounters faults such as impeller and bearing box damage due to limestone slurry's intense abrasion, corrosion, and cavitation. The various operating conditions, including frequent switching and rapid frequency variations of the slurry circulating pump will make the working environment worse undoubtedly. To ensure the process safety and operation efficiency of the WFGD system, this study proposed a condition monitoring (CM) method based on a novel multivariate state estimation technique (MSET), which can realize the fault early warning of the slurry circulating pump. To improve the accuracy of the conventional MSET, a memory matrix (MM) construction method based on K-means algorithm is proposed, which can provide a MM that varies with the operating condition of real-time observed vectors. In typical cases of predicting the pump's B-phase current under normal conditions, the root mean square error (RMSE) of our method is 0.25 A, much smaller than that of the conventional MSET method (2.08 A). On the other hand, the computation time of our method remains short (about 20 s) compared to other models (e.g., MEST aided with K-nearest neighbour model needs about 19,000 s) adaptive to varying conditions for over 3000 samples. Also, the proposed CM method can effectively provide early fault warning for impeller damage and bearing box damage of the slurry circulating pump, with 8 days and 1 day in advance, respectively. This can win enough time to inspection & maintenance before troubleshooting. [ABSTRACT FROM AUTHOR]

Equilibrium capacity expansion is an effective tool to help regulators predict the generation evolution of power systems by analyzing the decision-making of generation companies (Gencos). With the development of carbon markets (CMs) and electricity markets (EMs), Gencos' decisions in these two markets (encompassing investment and bidding decisions related to carbon emission allowances and electricity) are deeply intertwined through market clearing results. However, existing studies mainly focus on equilibrium capacity expansion with fixed carbon prices and usually ignore the realistic clearing process of CMs, which cannot simulate Gencos' coupled decision-making and accurately predict generation evolution under the CMs and EMs. This paper proposes a two-level equilibrium capacity expansion model for power systems which considers the coupled decisions of Gencos between CMs and EMs. At the upper level, multiple Gencos' coupled decision models are proposed based on their interaction with market clearing results. At the lower levels, CMs and EMs are respectively cleared to determine the varying carbon and electricity prices. Furthermore, the developed equilibrium capacity expansion model is reformulated as an equilibrium problem with equilibrium constraints (EPEC), which is solved by a diagonalization-based solution procedure. Finally, a provincial power system of southeast China is used to validate the performance of the proposed framework. The results illustrate that under CMs and EMs, non-fossil energy would account for 81.3% of total capacity and 73.88% of total generation in 2050. Compared to the existing model using fixed carbon prices, the consideration of realistic carbon market clearing will promote the installation of renewable energies and improve social welfare. The proposed model can provide beneficial references for regulators to perceive the evolution of power systems in CMs and EMs. • A two-level equilibrium capacity expansion model for power systems is proposed. • A novel coupled decision model for Gencos in CMs and EMs is developed. • The proposed model is solved by a diagonalization based solution procedure. • The results can guide the transition of power systems under the CMs and EMs. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-stage circulation process enhanced CO 2 capture/regeneration performance. • The CO 2 loading of the rich MEA solvent was up to 0.514 mol CO 2 /mol amine. • The CO 2 regeneration duty reached 2.02 GJ/t CO 2 using NH 3 /K 2 CO 3 solution. One of the major barriers in industrial applications of solvent-based CO 2 capture is the significant energy consumption required for absorbent regeneration. In this study, a novel multi-stage circulation (MSC) CO 2 absorption process was proposed, which implemented independent regulation of each stage, resulting in enhanced CO 2 capture performance and reduction of CO 2 regeneration duty. The MSC absorber was designed with four stages from bottom to top, each serving distinct functions, including CO 2 enrichment, CO 2 main absorption, CO 2 capture efficiency enhancement and aerosol capture. Simulation of the MSC process achieved a rich ethanolamine (MEA) solvent CO 2 loading of 0.512–0.570 mol CO 2 /mol amine, which was 8.1 %–9.9 % higher than typical process. The effects of test duration, amine solution flow rates, reaction temperatures and inlet CO 2 concentrations on CO 2 absorption performance were studied using the MSC experimental platform. The CO 2 regeneration duty reduced by over 13.2 % of the MSC process compared to a typical process using 25 wt% MEA solution and by over 22.9 % using piperazine (PZ)/N-methyldiethanolamine (MDEA) solution. Furthermore, the utilization of NH 3 /K 2 CO 3 solution achieved an energy consumption reduction of over 41.7 %, resulting in a CO 2 regeneration duty as low as 2.02 GJ/t CO 2 (1.84 GJ/t CO 2 , subtracting the heat loss). Meanwhile, potential strategies for optimizing parameters of MSC process were proposed to address the complex and volatile conditions. [ABSTRACT FROM AUTHOR]

Developing efficient water splitting electrocatalysts plays a critical role in lowering the energy cost for hydrogen production, which requires accurate evaluation of the catalytic performance especially under industrially relevant conditions. In this work, we design a two-chamber electrolyzer testing system simulating practical water electrolyzer system to enable catalytic performance evaluation under industrially relevant conditions. A one-step electrodeposition method is used to synthesize binary and ternary Ni alloy HER catalysts and the catalytic electrodes are screened and optimized with the two-chamber electrolyzer testing system. A voltage of 1.64 V without iR compensation at a current density of 200 mA/cm2 is obtained with continuous operation for 70 h. Different HER activity trend is observed from conventional three-electrode experiments with low-concentration alkaline electrolytes at room temperature and the two-chamber electrolyzer measurements, further supporting the importance of catalytic performance evaluation under industrially relevant conditions. The electrodeposition synthesis method is further used to prepare large-area catalytic electrodes over 400 cm2 with good uniformity. • Ni-alloy HER catalysts are characterized under industrially relevant conditions with a home-build electrolyzer system. • Electrolyzer with an electrodeposited NiMo HER catalyst exhibits a remarkably low voltage of 1.64 V at 200 mA/cm2. • Different activity trends of HER catalysts are observed under industrially relevant conditions and three-electrode tests. • Ni-alloy catalysts with an active area over 400 cm2 are successfully synthesized with excellent performance uniformity. [ABSTRACT FROM AUTHOR]

• The SO 2 absorption into a droplet falling freely is investigated numerically. • The deformation and internal circulation occur during droplet falling and facilitate the mass transfer of gas-droplet. • A modified mass transfer coefficient of gas phase is proposed. The SO 2 absorption into a droplet falling freely is investigated numerically based on a detailed three-dimensional mode in this work. Gas-liquid multiphase flow simulations coupled with interphase mass transfer are performed using the coupled Level-set and Volume of Fluid method (CLSVOF) to trace the gas-droplet interface. The results of simulation reveal that droplet would deform and deviate from the standard sphere during falling, with an approximately 5.6 % increase in surface area under the discussed working conditions. The evolution mechanism of the internal circulation in the droplet is clarified: the increase in the relative velocity of gas-droplet facilitates the formation and intensification of the internal circulation in the droplet. As the internal circulation develops into the stable stage, the convective mass transport would dominate the mass transfer process and promote the mass transfer. The distribution laws of the local mass transfer rate and coefficient over the droplet surface are found analogous to the typical case of heat transfer around a sphere. Finally, considering the effects of both droplet deformation and internal circulation on mass transfer concurrently, the variation of Sh as a function of Reynolds number is obtained, which appears the same trend but yields slightly higher values compared to the results of empirical correlations. [Display omitted] [ABSTRACT FROM AUTHOR]