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This paper provides an overview of rubber bitumen (RB) modification mechanisms, factors affecting storage stability, and characterization methods. The focus is on summarizing the methods to improve the storage stability of RB. Results indicate that the modification of RB primarily involves swelling and degradation. The settling velocity of crumb rubber (CR) is influenced by the particle size, density, and bitumen viscosity. To evaluate the storage stability of modified bitumen, widely applicable and preferred methods include softening point and rheological property tests. The storage stability of RB can be improved by increasing the swelling rate of CR, promoting crosslinking between CR and bitumen, and reducing CR agglomeration. Commonly used improvement methods include CR selection, the Terminal Blend (TB) curing process, adding modifiers, solubilization blending, the screw extrusion process (SEP), chemical reagent activation, and physical energy activation. The TB curing and SEP are more suitable for engineering-scale applications and yield improved results. However, high production temperatures may compromise the mechanical properties of CR, leading to drawbacks such as high energy consumption and environmental pollution, a problem requiring further exploration. Utilizing bitumen analogs rich in aromatic fractions as solubilizers for CR pretreatment has emerged as an effective option, offering advantages such as simplicity, resource conservation, and favorable improvements. Future research should focus on a deeper investigation of these processes. [Display omitted] • Methods to improve the compatibility of crumb rubber with bitumen are summarized. • Different characterization methods for storage stability are evaluated. • Reducing the crosslink density of rubber improves rubber bitumen storage stability. • Solubilization blending can be considered a sustainable and capable approach. [ABSTRACT FROM AUTHOR]

Image dehazing is an improtant image pre-processing step for many computer vision tasks with many proposed methods using convolutional neural networks. Ordinary Differential Equations (ODE) are a powerful mathematical tool in social and natural science, leading to better understanding, prediction, and use of information systems. Because prior knowledge has demonstrated its effectiveness in many practical domains, we design a Visual Attention Network (VAN) and an ODE-inspired Network (ODEN) based on prior knowledge. Then, we develop a multi-model fuzzy fusion strategy, which integrates results predicted by the prior-based Visual Attention Network (VAN) and the ODE-inspired Network (ODEN) into a single network to leverage their respective strengths in improving the dehazing performance. First, to utilize the haze-related prior for dehazing, the VAN removes haze with the help of the haze attention map. Then, to improve performance of stacked residual blocks inspired by the first-order Euler method in ODE-based methods, the ODEN is built by only 3 Runge–Kutta Modules (RKM), each of which not only is related to the stable fourth-order Runge–Kutta method implemented in the Runge–Kutta Block (RKB), but also combines the RKB with an attention mechanism. Finally, an attention based fusion mechanism is used to fuse results estimated by the ODEN and the VAN based on the multi-level features extracted by a pretrained ResNeXt. The experimental results demonstrate that the proposed method outperforms existing state-of-the-art methods in terms of visual effects and accuracy. The average PSNR and SSIM on three public datasets are 31.36 and 0.9766, respectively, which are better than the compared state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The diffusion bonding of YG8 cemented carbide and 40Cr steel was performed using spark plasma sintering with Ni powder as the interlayer. The influence of bonding temperatures ranging from 700 to 1100 °C on the bonding interface morphology, mechanical properties, and failure mechanism of the joints was studied. By calculating the diffusion coefficients of Ni and Fe and observing the changes in the interface morphology, the pores at the Ni/40Cr interfaces were identified as Kirkendall voids formed because of the unbalanced diffusion of Ni and Fe. The diffusion activation energy of Ni in Fe was 87.37 kJ/mol, and that of Fe in Ni was 58.08 kJ/mol. The use of a pulsed current significantly reduced the diffusion activation energy, making diffusion easier. The bending strength of the joints increased sharply in the range from 700 to 900 °C, subsequently increased slowly, and tended to stabilise in the range from 900 to 1100 °C. The highest bending strength of 1080 MPa was achieved for the joint bonded at 1100 °C, which was attributed to the improved bonding of the YG8/Ni and Ni/40Cr interfaces and the resulting effects of the interlayer plastic constraint. The thickness of the Co Ni diffusion zone at the YG8/Ni interface appeared to form a decisive factor in determining the failure locations of the joints. As the bonding temperature increased, the improved diffusion of Co and Ni enhanced the metallurgical bonding of the YG8/Ni interface, and the fracture position shifted from the polished surface of the YG8 base material (700 °C) to the Ni interlayer (1100 °C). • Effect of bonding temperature on the welding of YG8/40Cr joints is studied. • The welding morphology and failure mechanism of YG8/40Cr joints are investigated. • The bending strength of YG8/40Cr joint in this work reaches up to 1080 MPa. [ABSTRACT FROM AUTHOR]

• Traditional two-way coupled Euler-Lagrange(EL) underestimates the drag force and fails in supersonic flow laden finite-size particles. • An upward weighted average method is implemented for E to L coupling to well restore the actual and undisturbed gas-phase quantities acting on particles. • An upward mix-gaussian function is proposed for L to E coupling to reproduce the shock and wake zone of particle in terms of the kernel widths commended. • The modified method not only allows to track arbitrary finite-size particles, but also improves the accuracy of classical PSIC-EL in supersonic flow. In Euler-Lagrange (EL) framework, the Gauss kernel (GK) is usually introduced to avoid Dirac source disturbance of traditional particle-in-cell (PIC) method in subsonic regime. This work investigates the applicability and limitations of PIC-two-way coupling and GK for finite-size particles subjected to supersonic and dilute regime. Results indicate that the source disturbance of GK always peaks at the symmetric center of GK causing a suboptimal shock and ignoring wake in supersonic regime. Meanwhile, classical PIC-interpolation underestimates the drag force on particles due to shock and finite-size effects. To circumvent those issues, a modified coupling method utilizing upstream weighting averaged method and mix-gaussian kernel is proposed to optimize Euler-to-Lagrange coupling and Lagrange-to-Euler coupling, respectively. The modified method not only allows for accurate tracking of arbitrary finite-size particles in supersonic flows but also restores the undisturbed laden flow quantities exerting on particles. Shock and wake zone are reproduced before and after the particle based on recommended parameters. Furthermore, the modified method is validated using a particle-pair exposed to supersonic flow referred from Utkin's experiment(Utkin et al., 2021), and shows excellent agreement. Providing new insight into comprehending for two-way coupled Euler-Lagrange to simulate finite-size particles laden by supersonic flow. Dimensionless pressure and streamwise velocity using different two-way coupling methods [Display omitted] [ABSTRACT FROM AUTHOR]

To satisfy the demand for thrust control on solid rocket motors and solid ramjet engines, numerical simulation of the effect of high-voltage electric fields on the combustion characteristics of polymethyl methacrylate (PMMA) under lateral inflow was undertaken. The mechanism of the effect of electric fields on the regression rate and mass flow rate of PMMA was analyzed. The results show that PMMA mass flow rate can increase by about 54% when subjected to positive voltages. The PMMA mass flow rate can not only increase by about 5.5% but also decrease by about 14% under the action of negative voltages. When the oxygen mass fraction is 54.5% at 0.101 MPa, the effect of electric fields on PMMA mass flow is weakened as the lateral velocity increases. When the inflow velocity is 1.95 m s−1 and oxygen mass fraction is 23.2%, the effect of electric fields on PMMA mass flow is decreased as the pressure rises. The effect of electric fields on PMMA regression rate is mainly due to the electric-field-induced volumetric body force. It will result in large-scale bulk flow movement, known as ionic wind, which changes the distribution of species and affects the heat of reaction, thus causing the changes in flame temperature, finally altering the thermal feedback to the solid phase. • Electric fields can change PMMA regression rate and mass flow rate. • The change of PMMA mass flow rate was closely related to applied voltages. • The change of the regression rate was due to electric body force. [ABSTRACT FROM AUTHOR]

Due to great demands on solid rocket motors and solid ramjets for thrust control, a study of the effect of high-voltage electric fields on the regression rate of polymethyl methacrylate (PMMA) has been undertaken. The flame shape was recorded by a CMOS camera. The regression rate of PMMA was measured. A numerical model of fluid-solid coupling, which is based on experiment and considers physico-chemical phenomena associated with the flame-field interaction process, has been developed to explain experimental observations. In order to reduce the computational workload, the radiation loss, including the soot radiation is not considered in the numerical simulation. The mechanism of the effect of electric fields on the regression rate of PMMA is analysed. The numerical simulation shows that the change of the regression rate of a PMMA tip under the action of electric fields is consistent with experimental results. Studies show that electric fields can change the regression rate of PMMA, increasing it by about 38%. The regression rate on the burning surface is increased when subjected to positive electric fields. Under a negative electric field, part of the burning surface is subjected to an increased regression rate, and some thereof is subjected to a decreased regression rate. The effect of electric fields on the regression rate of PMMA is mainly due to the interaction of buoyancy and the electric field induced volumetric body forces. • Electric fields can change the regression rate of PMMA. • The change of the regression rate was closely related to applied voltage. • The change of the regression rate was due to the action of buoyancy and"ionic wind". [ABSTRACT FROM AUTHOR]

Biological traits analysis (BTA) can help identify the effect of various contaminants on functional trait composition of macrobenthos. However, the effects of bioavailable heavy metals on functional traits of macrobenthos communities remain to be examined. We sampled macrobenthos communities and assessed environmental variables over gradients of heavy metal pollution in Swan Lagoon, China. The RLQ and fourth-corner approaches were used to investigate the response of functional traits to heavy metal pollution. Our findings suggested that macrobenthic functional traits can be used to distinguish the effects of heavy metals and other environmental variables and isolate the corresponding species associated with heavy metal contamination. The macrobenthos at highly contaminated sites comprised taxa of sub-surface deposit-feeders, second-order opportunistic species, and tube-builders, mainly represented by the polychaeta Cirriformia tentaculata and Cirratulus chrysoderma. At less contaminated sites, indifferent species, species attached to seagrass, and crawlers were observed. The results confirm that BTA can provide new insights into the response of macrobenthic functional traits to heavy metal pollution in coastal lagoons. Image 1 • Macrobenthos functional trait responses to heavy metal pollution have rarely been assessed. • Functional traits can differentiate the effects of heavy metals and other environmental variables. • Heavy metal pollution may cause clear functional trait changes in macrobenthic communities. [ABSTRACT FROM AUTHOR]

This study was performed to determine the distribution and chemical fractions of five heavy metals (Cd, Cr, Cu, Pb, and Zn) in sediment from three sampling areas in Swan Lagoon, and their relation to the physiochemical properties of sediment were explored. The results revealed that Cd in sediment from the sand part (SP), muddy sand part (MSP) and sand muddy part (SMP) were potentially highly susceptible and bioavailable since the exchangeable fractions were 21.0%, 27.4%, and 32.1%, respectively, of the total concentrations. A portion of Pb and Zn were observed as reducible fractions owing to their affinity to Fe-Mn; they were able to complex with Fe-Mn oxides and oxyhydroxides in the sediment. A large amount of Cu in the oxidizable fraction may be due to the fact that Cu can easily form stable complexes with organic matter. Cr was overwhelmingly found in the residual fraction, suggesting that Cr was strongly bound in mineral lattices. Enrichment factors (EF) indicated that Cd in three sampling areas suffered severe enrichment, whereas other metals were present in only minor amounts. In addition, Cd may pose a medium to high risk in the MSP and SMP based on risk assessment codes. According to the mean probable effects level quotient, the samples from the MSP and SMP had a 21% probability of toxicity. The multivariate statistical analysis suggested that sediment texture (d0.5, sand and silt), Fe-Mn, and the total organic carbon (TOC) influenced the distribution of the studied metals and their chemical fractions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Numerical and experimental studies on multi-stage Tesla valve (MSTV) flow field. • Changes in the flow directions can affect the characteristics of MSTV flow field. • An inlet commutation strategy based on Tesla valve flow field is proposed. • Net power is enhanced over the entire current density range. The net power of a proton exchange membrane fuel cell (PEMFC) is affected by both output power and parasitic power. A Tesla valve flow field is designed to improve the net power of PEMFC. As a valve with no-moving-part, Tesla valve allows the forward and reverse flow of fluid, and a change in the flow direction can greatly affect the characteristics of the valve. In this research, the transport characteristics and output performance of reverse and forward flow for multi-stage Tesla valve (MSTV) flow field in PEMFC are numerically simulated and experimentally studied. The results indicate that the forward and reverse flow of the MSTV flow field show significantly different characteristics in terms of velocity distribution, pressure distribution and oxygen mass fraction. Meanwhile, the pressure drop of the MSTV flow fields is one to two orders of magnitude lower compared to the conventional serpentine flow field (CSFF). Compared with the conventional parallel flow field (CPFF), the peak net power of MSTV flow field for reverse and forward flow can be increased by 19.89% and 3.90%; compared with CSFF, the peak net power of MSTV flow field for reverse flow can be increased by 12.19%. Furthermore, considering parasitic power generated by pressure drop, an inlet commutation strategy based on MSTV flow field has been proposed to enhance the net power of PEMFC under all working conditions. [ABSTRACT FROM AUTHOR]

• An abnormal in-plane thermal conductivity anisotropy of bilayer α-phase tellurene is found. • κ⊥ / κ∥ of 2L-aTe is 1.174, in sharp contrast to bulk Te for which κ// / κ⊥ is 0.435. • Phonon transport properties and lattice structure change are analyzed to explain the anomalous thermal conductivity anisotropy. • Covalent-like quasi-bonding and its electronic origins are discussed to uncover the physical mechanism. In layered materials, it is well known that the cross-plane or cross-chain (CC) thermal conductivity is lower than that of the in-plane or along-chain direction due to weaker bonding in the cross-plane or CC directions. In this work, surprisingly, we predict using first-principles that the CC thermal conductivity κ ⊥ is higher than the along-chain thermal conductivity κ ∥ with a κ ⊥ / κ ∥ ratio of 1.174 in bilayer α -phase tellurene (2L-αTe), an emerging 2D material that has recently drawn extensive interest due to its intriguing electronic, thermoelectronic, and piezoelectronic properties. Also, the room-temperature κ ⊥ and κ ∥ of 2L-αTe are 5.69 W/mK and 4.85 W/mK, which are 251% and 31% enhanced from that of bulk Te, respectively. A detailed analysis of lattice structure, phonon spectra, and electron properties of 2L-αTe and bulk Te is provided. We find that the larger lattice shrink in CC direction and the change in band angle lead to stiffened phonons and weaker anharmonicity, which in turn yield higher phonon group velocity and longer phonon lifetime in CC direction for 2L-αTe, resulting in the enhanced thermal conductivity and the anomolus thermal anisotropy. Crystal orbital Hamiltan population (COHP) and electron localization function (ELF) analysis demonstrate the enhancement of the strength of "covalent-like quasi-bonding" (CLQB) in CC direction of 2L-αTe, which is accompanied by the lattice shrink in CC direction and the change of band angle. Our study identifies a case of unexpected anisotropic thermal transport in 2D materials, and sheds light on the improvement of thermal conductivity isotropy in 2D materials for the thermal management of electronic devices. [ABSTRACT FROM AUTHOR]

Asphalt pavements are widely used in road engineering owing to their good skid resistance, ease of maintenance, and high driving comfort. However, large amounts of toxic fumes are produced during petroleum asphalt heating, asphalt mixture preparation, and pavement construction. This review clarifies the fuming mechanisms and hazards of asphalt fumes with the aim of promoting the application of fume-suppression asphalt(s) and reducing the emission levels of asphalt fumes. First, starting from the fuming mechanisms of hot asphalt, the composition and hazards of asphalt fumes are described. Second, existing indoor and on-site asphalt fume testing methods are discussed. Finally, the inhibitory effects and mechanisms of different types of fume suppressants are discussed separately to provide a reference for the popularization and application of fume-suppression asphalt. The review shows that the existing descriptions of the fume-generation mechanisms are based on physical phenomena, and there is a lack of systematic research at the chemical level. An indoor asphalt fume test is usually conducted using a fume-generation and collection device, where the main test object is an asphalt binder. Therefore, it is difficult to simulate real fuming conditions in these tests. A field testing mainly evaluates the concentrations of different types of asphalt fumes, and there is a lack of standardization of asphalt fume test methods and emission specifications. Existing asphalt fume suppressants mainly include polymers, flame retardants, warm mixing agents, adsorbents, and nanomaterials; traditional fume suppressants such as polymers, flame retardants, and warm mix agents have poor fume-suppression effects or reduce the pavement performance. Meanwhile, nanomaterial-based fume suppressants have good fume-suppression and improved pavement performance to some extent; however, they are still in the early stages of exploration. Therefore, future research should focus on asphalt fume-generation mechanisms, asphalt fume-evaluation methods and specifications, and environmentally friendly nanomaterial-based fume suppressants. [Display omitted] • The asphalt fuming mechanism in different construction stages were summarized. • The test methods of asphalt fume were discussed in detail from the perspective of indoor test and field test. • The inhibitory effect, mechanism and working performance of different fume suppressants were classified and summarized. [ABSTRACT FROM AUTHOR]

Because a greater proportion of large-scale electric vehicles (EVs) are connected to the grid, their stochastic charging load has a significant impact on the power quality and economic operation of the distribution network. However, a random charging load can be transformed into flexible demand response resources through intelligent control of the EV charging process. Therefore, a bi-level optimization model for EV charging is proposed in this study based on the real-time charging price according to the regional grid load, providing more flexible charging strategies for EVs. First, the framework for a bi-level optimization control strategy for EV charging based on the load is developed. Based on the regional grid load, the charging price of each period is optimized in accordance with the load elasticity coefficient of the real-time charging price. Second, an upper-level EV charging price optimization model and a lower-level EV charging load optimization model are established. Third, an optimal control strategy for the scheduling of EV charging is developed, which considers the charging cost of EV users as the objective function and the standard deviation and peak-valley difference of the regional grid load as validation functions. Finally, using a regional power grid in China as the simulation object, the daily operation data of the grid are used to analyze and verify the proposed model. The simulation results demonstrate that the optimized real-time charging price can better respond to the regional grid load, smooth the regional grid load curve, reduce the peak-valley difference, promote clean energy consumption, and further lower the charging cost for EV users. • A framework of the bi-level optimization for electric vehicle charging is proposed. • Load elasticity coefficient of real-time charging price is introduced. • Real-time charging price model following the load of the power grid is constructed. • Impacts of real-time charging price change on electric vehicle load are analyzed. • Flexible charging strategies are provided for electric vehicle users. [ABSTRACT FROM AUTHOR]

Waste crumb rubber (CR) can be used in asphalt pavement construction to develop eco-friendly and sustainable pavements. The objective of this study was to investigate the reaction mechanism, high-temperature properties, thermal stability, and volatiles released by CR-modified asphalt (CRMA) activated using microwaves (i.e., ACRMA). The chemical characteristics determined via Fourier-transform infrared spectroscopy revealed that mainly physical reactions occurred in the CRMA before and after activation; however, the swelling reaction in the ACRMA was more efficient than that in the CRMA. These results were confirmed by gel permeation chromatography and atomic force microscopy. The high-temperature performance of the ACRMA was slightly better than that of the CRMA. Additionally, according to stress creep and recovery test results, the microwave activation reduced the stress sensitivity of the rubber-modified asphalt. Thermogravimetric curves indicated that the microwave activation reduced the decomposition temperature of the rubber-modified asphalt. Moreover, the total amount of released volatiles for the base asphalt was significantly larger than that for rubber-modified asphalts, indicating that the CR suppressed the total amount of released volatile gases from the asphalt during the pyrolysis of asphalt. But the addition of CR can increase the release of some toxic gases in CRMA and increase the toxicological potential of asphalt fumes. However, in the initial pyrolysis of rubber asphalts, microwave treatment can reduce the generation of toxic gases. In the later stages of this process, the introduction of rubber particles before and after activation has little effect on the released volatiles. [ABSTRACT FROM AUTHOR]

Effective and durable photocatalysts are essential for the decomposition of persistent contaminants and the generation of hydrogen peroxide. In this study, we successfully constructed an S-type heterojunction by in situ growing Bi 2 O 3 nanocrystals and NH 2 -MIL-101(Fe) onto surface-modified g-C 3 N 4. The process of charge transfer in the S-type heterojunction was confirmed using ISI-XPS, DFT calculations, capture experiments, and EPR signals. The combined influence of the heterojunction and MOF demonstrated remarkable photocatalytic performance in the breakdown of tetracycline (TC) and the generation of hydrogen peroxide (H 2 O 2). In the enhanced setup (10%–NH 2 –MIL-101(Fe)@MCN/Bi 2 O 3), full degradation of TC was accomplished within 50 min under visible light exposure. Additionally, a notable H 2 O 2 yield of 655.63 μmol/g was attained, all achieved without the necessity of sacrificial agents or supplementary oxygen. Based on the outcomes of the dual functionality, the exceptional performance of the ternary composite material can be ascribed to the collaborative influence of the heterojunction and MOF. This collaborative effect expands the light absorption range in the visible region, suppresses the recombination of electron-hole pairs, and enhances the photocatalytic redox ability. The system demonstrates significant potential in the efficient in situ production of H 2 O 2 and removal of recalcitrant organic pollutants in pure water. [Display omitted] • A novel NH 2 -MIL-101(Fe)@MCN/Bi 2 O 3 photocatalyst was synthesized. • Effective charge carrier separation and utilization were achieved through the synergistic effects of the S-type heterojunction and MOF. • High efficiency in the degradation of pollutants and generation of H 2 O 2 under visible light. [ABSTRACT FROM AUTHOR]

The spray characteristics of liquid jets in supersonic crossflow at different injection jet-gas momentum ratios are investigated numerically. The compressible two-phase flow large eddy simulation (LES) method is based on the Eulerian-Lagrangian scheme. The average droplet volume fraction is defined to quantify spray concentration distribution, which can also reflect the oscillation boundary of the spray. The LES predicted the spray boundaries at different injection jet-gas momentum ratios in the central and cross-sectional planes, which agree reasonably well with the experiment. Two sets of counter-rotating vortex pair (CVP) are in the gas-liquid mixing region. As injection momentum ratio q increases, the upper CVP increases. Still, the absolute size of the wall CVP remains almost unchanged, which means that the relative size of the wall CVP to the upper CVP becomes smaller. As q increases, the spray's overall distribution position is generally upward, and the number of droplets entering the near-wall region becomes small. Thus, droplet-wall interactions are weakened. The spray body increases with the increase of q , while the spray foot decreases gradually. In the central plane, the coherent structures near the wall are mainly composed of splashed droplets, and this phenomenon gradually weakens as q increases. Although the increase of q can increase the total droplet mass flow rate, the proportion of the droplet mass flow rate in the near-wall region to the total mass flow rate decreases, and the droplet mass flow rate in the near-wall region decreases. [ABSTRACT FROM AUTHOR]

Abstract We applied a hot rolling direct quenching and partitioning (HDQ&P) process to a low-C low-Si Al-added steel and obtained a Q&P steel containing 40 vol % of ferrite. Microstructure characterization was performed by means of SEM, EBSD, TEM and XRD. Atomic-scale characterization of carbon partitioning among the phases was carried out by atom probe tomography (APT). The carbon distribution in the retained austenite and near the martensite/retained austenite interfaces was quantitatively analyzed to study its partitioning behavior. The macroscopic strain distribution evolution across the tensile sample surface was investigated using macro digital image correlation (DIC) analysis. Combining these results with joint micro-DIC and EBSD analysis during quasi in-situ tensile testing, we investigated the strain partitioning among the different phases and the TRIP effect. Coupling of these results enabled us to reveal the relation among carbon partitioning, strain partitioning and the TRIP effect. The large blocky retained austenite with a side length of about 300–600 nm located near the ferrite/martensite (F/M) interfaces has low stability and transforms to martensite during the early deformation stages, i.e. at average strain below 21%. The retained austenite films in the centers of the martensite regions are more stable. The carbon distribution in both, the martensite and the retained austenite are inhomogeneous, with 0.5–2.0 at. % in the martensite and 4.0–7.5 at. % in the retained austenite. Strong carbon concentration gradients of up to 1.1 at. %/nm were observed near the martensite/retained austenite interfaces. The large blocky retained austenite (300–600 nm in side length) near the F/M interfaces has 1.5–2.0 at. % lower carbon content than that in the narrow retained austenite films (20–150 nm in thickness). The ferrite is soft and deforms prior to the martensite. The strain distribution in ferrite and martensite is inhomogeneous, varying by up to 20% within the same phase at an average strain of about 20%. Ferrite deformation is the main origin of ductility of the material. The balance between ferrite fraction and martensite morphology controls the TRIP effect and its efficiency in reaching a suited combination of strength and ductility. Reducing the ferrite volume fraction and softening the martensite by coarsening and polygonization can enhance the strain carried by the martensite, thus promoting more retained austenite in the martensite regions enabling a TRIP effect. The enhancement of the TRIP effect and the decrease of the strain contrast between ferrite and martensite jointly optimize the micromechanical deformation compatibility of the adjacent phases, thus improving the material's ductility. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

As an important means to reduce CO 2 emissions from coal-fired power plants, CCUS project has received more and more attention. In this paper, the comprehensive benefits of CCUS project in coal-fired power plants are defined as economic benefits, environmental benefits and energy benefits, and comprehensive evaluation and prediction analysis of CCUS project in coal-fired power plants are made from these three aspects. The goodness-of-fit of the constructed comprehensive evaluation model can reach 0.99, and the ratio of economic, environmental and energy benefits is about 5: 9: 1. Among them, the best scenario of policy influence, economic development and technological progress can promote CCUS project with benefits of 6.51%, 6.56% and 13.07% respectively. Through case analysis, it can be calculated that when the service life of CCUS project reaches 21.7 years, the investment cost can be recovered from the economic benefits. In the prediction model, the goodness of fit of the economic benefit prediction model is up to 0.95, in which the carbon capture cost of CCUS technology, operation and maintenance cost and carbon price fluctuation play a major role. The goodness of fit of the environmental benefit prediction model can reach 0.90, in which the carbon capture capacity of CCUS project and the world environmental situation are the main influencing factors, and the goodness of fit of the energy benefit prediction model can reach up to 0.95, which is mainly affected by the energy consumption level of CCUS project. The research results show that CCUS project of coal-fired power plants at home and abroad has a good development prospect and remarkable comprehensive benefits. This paper puts forward relevant policy suggestions that are beneficial to the development of CCUS project in coal-fired power plants, with a view to providing empirical evidence for the evaluation and decision-making of CCUS project in coal-fired power plants. • A comprehensive evaluation and prediction system of CCUS projects in coal-fired power plants is established. • In this paper, neural network is used for benefit accounting and evaluation. Meanwhile, machine learning is used for benefit prediction, with a good degree of fitting and high accuracy of the model.Neural network and machine learning are used to forecast and estimate the benefits. • The analysis method is universal and can be used to study CCUS projects in other industries. [ABSTRACT FROM AUTHOR]