Ligand modulation of active center to promote lead-free Cs_(2)AgInCl_(6)photocatalytic CO_(2)reduction

Metal halide perovskites(MHP)are potential candidates for the photocatalytic reduction of CO_(2)due to their long photogenerated carrier lifetime and charge diffusion length.However,the conventional long-chain ligand impedes the adsorption and activation of CO_(2)molecules in practical applications.Here,a ligand modulation technology is employed to enhance the photocatalytic CO_(2)reduction activity of lead-free Cs_(2)AgInCl_(6)microcrystals(MCs).The Cs_(2)AgInCl_(6)MCs passivated by Oleic acid(OLA)and Octanoic acid(OCA)are used for photocatalytic CO_(2)reduction.The results show that the surface defects and electronic properties of Cs_(2)AgInCl_(6)MCs can be adjusted through ligand modulation.Compared with the OLA-Cs_(2)AgInCl_(6),the OCA-Cs_(2)AgInCl_(6)catalyst demonstrated a significant improvement in the catalytic yield of CO and CH_(4).The CO and CH_(4)catalytic yields of OCA-Cs_(2)AgInCl_(6)reached 171.88 and34.15μmol g^(-1)h^(-1)which were 2.03 and 12.98 times higher than those of OLA-Cs_(2)AgInCl_(6),and the total electron consumption rate of OCA-Cs_(2)AgInCl_(6)was 615.2μmol g^(-1)h^(-1)which was 3.25 times higher than that of OLA-Cs_(2)AgInCl_(6).Furthermore,in situ diffuse reflectance infrared Fourier transform spectra revealed the enhancement of photocatalytic activity in Cs_(2)AgInCl_(6)MCs induced by ligand modulation.This study illustrates the potential of lead-free Cs_(2)AgInCl_(6)MCs for efficient photocatalytic CO_(2)reduction and provides a ligand modulation strategy for the active promotion of MHP photocatalysts.

Mechanical and Electrical Properties of Some Sn-Zn Based Lead-Free Quinary Alloys

Although there are many lead-free soldering alloys on the market, none of them have ideal qualities. The researchers are combining binary alloys with a variety of additional materials to create the soldering alloys’ features. The eutectic Sn-9Zn alloy is among them. This paper investigated the mechanical and electrical properties of Sn-9Zn-x (Ag, Cu, Sb);{x = 0.2, 0.4, and 0.6} lead-free solder alloys. The mechanical properties such as elastic modulus, ultimate tensile strength (UTS), yield strength (YS), and ductility were examined at the strain rates in a range from 4.17 10−3 s−1 to 208.5 10−3 s−1 at room temperature. It is found that increasing the content of the alloying elements and strain rate increases the elastic modulus, ultimate tensile strength, and yield strength while the ductility decreases. The electrical conductivity of the alloys is found to be a little smaller than that of the Sn-9Zn eutectic alloy.

Large Energy Capacitive High-Entropy Lead-Free Ferroelectrics

Advanced lead-free energy storage ceramics play an indispensable role in next-generation pulse power capacitors market.Here,an ultrahigh energy storage density of~13.8 J cm^(-3)and a large efficiency of~82.4%are achieved in high-entropy lead-free relaxor ferroelectrics by increasing configuration entropy,named high-entropy strategy,realizing nearly ten times growth of energy storage density compared with low-entropy material.Evolution of energy storage performance and domain structure with increasing configuration entropy is systematically revealed for the first time.The achievement of excellent energy storage properties should be attributed to the enhanced random field,decreased nanodomain size,strong multiple local distortions,and improved breakdown field.Furthermore,the excellent frequency and fatigue stability as well as charge/discharge properties with superior thermal stability are also realized.The significantly enhanced comprehensive energy storage performance by increasing configuration entropy demonstrates that high entropy is an effective but convenient strategy to design new high-performance dielectrics,promoting the development of advanced capacitors.

Photo-and Electrocatalytic CO_(2)Reduction Based on Stable Lead-Free Perovskite Cs2PdBr6

All-inorganic lead-free palladium(Pd)halogen perovskites with prominent optoelectronic properties provide admirable potential for selective photo-and electroreduction of CO_(2).But it remains unachieved for effectively converting the CO_(2)to CO with high selectivity on Pd-based perovskites driven by solar light or electricity.Herein,high-quality Cs_(2)PdBr_(6)microcrystals and nanocrystals were synthesized through a facile antisolvent method.Among all the reported pure-phase perovskites,the Cs_(2)PdBr_(6)nanocrystals synthesized at 50℃performed the highest effectiveness on CO_(2)to CO conversion generating 73.8μmol g^(-1)of CO yield with 100%selectivity under visible light illumination(λ>420 nm)for 3 h.Meanwhile,for the first time,we report a new application of lead-free perovskites,in which they are applied to electrocatalysis of CO_(2)reduction reaction.Noticeably,they showed significant electrocatalytic activity(Faradaic yield:78%for CO)and operation stability(10 h).And the surface reaction intermediates were dynamically monitored and precisely unraveled according to the in situ diffuse reflectance infrared Fourier transform spectra investigation.In combination with the density functional theory calculation,the reaction mechanism and pathways were revealed.This work not only provides significant strategies to enhance the photocatalytic performance of perovskites,but also shows excellent potential for their application in electrocatalysis.

Efficient Environment-friendly Lead-free Tin Perovskite Solar Cells Enabled by Incorporating 4-Fluorobenzylammonium Iodide Additives

Development of tin(Sn)-based perovskite solar cells(PSCs)largely lags behind that of lead counterparts due to fast crystallization process of Sn perovskite and numerous defects in both bulk and surface of Sn perovskite films.Herein,this work reports a facile strategy of introducing 4-fluorobenzylammonium iodide(FBZAI)as additives into Sn perovskite precursor to synergistically modulate the roles of benzylamine and fluorine in Sn-based PSCs.Incorporation of FBZAI can increase crystallinity,passivate defects,and inhibit the oxidation of Sn^(2+),leading to suppression of nonradiative recombination and enhancement of charge transport and collection in devices.As a result,the best-performing Sn-based PSC with the FBZAI additive achieves the maximum PCE of 13.85%with the enhanced fill factor of 77.8%and open-circuit voltage of 0.778 V.Our unencapsulated device exhibits good stability by maintaining 95%of its initial PCE after 160 days of storage.

Air-Stable,Eco-Friendly RRAMs Based on Lead-Free Cs_(3)Bi_(2)Br_(9)Perovskite Quantum Dots for High-Performance Information Storage

Development of lead-free halide perovskites that are innocuous and stable has become an attractive trend in resistive random access memory(RRAM)fields.However,their inferior memory properties compared with the lead-based analogs hinder their commercialization.Herein,the lead-free Cs_(3)Bi_(2)Br_(9)perovskite quantum dot(PQD)-based RRAMs are reported with outstanding memory performance,where Cs_(3)Bi_(2)Br_(9)quantum dots(QDs)are synthesized via a modified ligand-assisted recrystallization process.This is the first report of applying Cs_(3)Bi_(2)Br_(9)QDs as the switching layer for RRAM device.The Cs_(3)Bi_(2)Br_(9)QD device demonstrates nonvolatile resistive switching(RS)effect with large ON/OFF ratio of 105,low set voltage of-0.45 V,as well as good reliability,reproducibility,and flexibility.Concurrently,the device exhibits the notable tolerance toward moisture,heat and light illumination,and long-term stability of 200 days.More impressively,the device shows the reliable light-modulated RS behavior,and therefrom the logic gate operations including"AND"and"OR"are implemented,foreboding its prospect in logic circuits integrated with storage and computation.Such multifunctionality of device could be derived from the unique 2D layered crystal structure,small particle size,quantum confinement effect,and photoresponse of Cs_(3)Bi_(2)Br_(9)QDs.This work provides the strategy toward the high-performance RRAMs based on stable and eco-friendly perovskites for future applications.

Stable yellow light emission from lead-free copper halides single crystals for visible light communication

Yellow light-emitting diodes(LEDs) as soft light have attracted abundant attention in lithography room, museum and art gallery. However, the development of efficient yellow LEDs lags behind green and blue LEDs, and the available perovskites yellow LEDs suffer from the instability. Herein, a pressure-assisted cooling method is proposed to grow lead-free CsCu2I3single crystals, which possess uniform surface morphology and enhanced photoluminescence quantum yield(PLQY) stability, with only 10% PLQY losses after being stored in air after 5000 h.Then, the single crystals used for yellow LEDs without encapsulation exhibit a decent Correlated Color Temperature(CCT) of 4290 K, a Commission Internationale de l’Eclairage(CIE) coordinate of(0.38, 0.41), and an excellent 570-h operating stability under heating temperature of 100°C. Finally, the yellow LEDs facilitate the application in wireless visible light communication(VLC), which show a-3 dB bandwidth of 21.5 MHz and a high achievable data rate of 219.2 Mbps by using orthogonal frequency division multiplexing(OFDM) modulation with adaptive bit loading. The present work not only promotes the development of lead-free single crystals, but also inspires the potential of CsCu2I3in the field of yellow illumination and wireless VLC.

Research of Lead-free Na_(0.5)Bi_(0.5)TiO_(3)-BaTiO_(3)System Piezoelectric Ceramics

To reduce the coercive field of Na_(0.5)Bi_(0.5)TiO_(3),Ba TiO_(3)were added as dopant materials.Then the(1-x)Na_(0.5)Bi_(0.5)TiO_(3)-xBaTiO_(3)ceramic samples were produced in solid synthetic way.The optimum preparation condition and piezoelectric properties of the samples were investigated.The XRD results show that the fabric transites from rhombohedral to tetragonal gradually with the substitution of the Ba^(2+).The morphotropic phase boundaries(MPB)exists in the composition range of 0.06.

First Principle Study of Cesium-based Lead-free Halide Double Perovskites

Inorganic halide double perovskites A_(2)B'B"X_(6) have gained significant interests for their diverse composition,stable physicochemical properties,and potential for photoelectric applications.The influences of trivalent and monovalent cations on the formation energy,decomposition energy,electronic structure and optical properties of cesium-based lead-free Cs^(+)_(2)B'B"Br_(6) (B'=Na^(+),In^(+)Cu^(+),or Ag^(+);B"=Bi^(3),Sb^(3+),In^(3+)) are systematically studied.In view of the analysis and results of the selected double perovskites,for the double perovskites with different B-site trivalent cation,the band gap increases in the order of Cs_(2)AgInBr_(6),Cs_(2)AgSbBr_(6) and Cs_(2)AgBiBr_(6),with Cs_(2)AgBiBr_(6) possessing the highest thermodynamic stability.Therefore,the Bi-based perovskites are further studied to elucidate the effect of monovalent cation on their stability and electronics.Results show that the thermodynamic stability rises in the sequence of Cs_(2)NaBiBr_(6),Cs_(2)InBiBr_(6),Cs_(2)AgBiBr_(6) and Cs_(2)CuBiBr_(6).Notably,Cs_(2)CuBiBr_(6) exhibits a relatively narrow and appropriate band gap of 1.4634 eV,together with the highest absorption coefficient than other compounds,suggesting that Cs_(2)CuBiBr_(6) is a promising light absorbing material that can be further explored experimentally and be applied to optoelectronic devices.Our research offers theoretical backing for the potential optoelectronic application of cesium-based lead-free halide double perovskites in solar energy conversion.

Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Effect of Strain Rate on Tensile Behavior of Sn-9Zn-xAg-ySb;{(x, y) = (0.2, 0.6), (0.2, 0.8), (0.6, 0.2), (0.8, 0.2)} Lead-Free Solder Alloys

The tensile properties of Sn-9Zn-xAg-ySb;{(x, y) = (0.2, 0.6), (0.2, 0.8), (0.6, 0.2), (0.8, 0.2)} lead-free solders were investigated. All the test samples were annealed at 150°C for 1 hour. The tests are carried out at room temperature at the strain rate of 4.17 × 10-3 s-1, 20.85 × 10-3 s-1, and 208.5 × 10-3 s-1. It is seen that the tensile strength increases and the ductility decrease with increasing the strain rate over the investigated range. From the strain rate change test results, the strain sensitivity values are found in the range of 0.0831 to 0.1455 due to the addition of different alloying elements.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Dendritic spine degeneration:a primary mechanism in the aging process

Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

Correlation of Microbiological Stability with Redox Processes in White Wines

In this paper, the authors analyzed the correlation between the microbiological stability of white wines and the content of sulfur dioxide, which influences the main redox processes that take place in the technological stages of the wine. The consecutive, parallel and spontaneous development of several redox processes and their impact on the quality, microbiological and crystalline stability of white wines were examined. The reduction of additive and subtractive technological interventions, of the amounts of adjuvants (sulphurous anhydride) is essential for the production of organic wines.