Journal of Chemical Engineering and Energy Materials

Abstract In 2020, Cheng and his colleagues presented a paper entitled Al/Al2O3 direct bonding using transient eutectic liquid phase. In this research, they stated that ceramic base layers used in applications such as integrated circuit boards and diodes with high light emission. Directly bonded copper (DBC) layer is a ceramic layer that is widely used in electronic circuit boards for semiconductor modules, but the formation of CU2O at the interface causes a large deposition pressure. Therefore, the DBC layer has little strength against thermal cycling. Direct bonded aluminum (DBA), which uses aluminum as the metal circuit, used for ceramic layers. Although this combination not formed at the interface of ceramic and metal, but the bonded sample has good strength against thermal cycle. Khazaka et al. showed that in the work environment with thermal cycling, the DBA layer achieves better performance compared to the DBC layer. During thermal cycling tests from 55 to 250°C after 1500 cycles, no delamination of aluminum from the ceramic base metal plate observed. For conventional DBC technology, cracking or delamination occurs in DBC after 20 to 30 cycles. This improvement is due to the different plastic hardening behavior between aluminum and copper. To increase aluminum-ceramic bonding, the annealing temperature increased above the melting point of aluminum rather than the soaking effect. Increase and decrease the contact angle between aluminum and ceramic.

Abstract The durability of reinforced concrete infrastructure is critically threatened by cracking-induced corrosion, prompting the development of autonomous self-healing polymer-modified cementitious composites. This comprehensive review systematically examines the molecular engineering of polymer systems for concrete self-healing, focusing on the mechanistic understanding of inhibitor release kinetics and service life prediction. Superabsorbent polymers (SAPs) have demonstrated remarkable efficacy, achieving up to 97% reduction in autogenous shrinkage and complete crack healing through internal curing and promoted autogenous healing mechanisms . Microbial self-healing systems utilizing bacteria-induced calcium carbonate precipitation have achieved crack healing depths exceeding 40 mm, with healing efficiency directly correlated to crack width and bacterial metabolic activity . Polymeric corrosion inhibitors incorporating functional groups (-COOH, -NH₂, -SO₃H) exhibit inhibition efficiencies exceeding 90% through chemisorption mechanisms, with the neutralizing cation critically influencing performance through distinct adsorption pathways . Smart microcapsule systems demonstrate pH-responsive release behavior, with release rates increasing at lower pH values characteristic of corrosion initiation environments . Advanced computational approaches including generalized Polynomial Chaos Expansion enable full-cycle prediction of crack healing with high reliability , while machine learning models achieve R² values of 0.9918 for autogenous healing forecasting . This review concludes that integrated molecular design, controlled release mechanisms, and predictive modeling frameworks offer transformative potential for extending concrete service life by factors of 10 or more.

Abstract During the heating stage, the entire assembly placed in a furnace and its temperature increased from room temperature to below the eutectic temperature. When the assembly is heated, some solid-state penetration occurs between the interface layer and the base metal. The amount of penetration depends on several factors, including the surface roughness and cleanliness of the surface and the pressure exerted on the surface. In most cases, it expected that the amount of particle penetration of this stage is low. However, the amount of mass transferred in this step depends on the eutectic temperature, heating rate and diffusion coefficient. The longer the heating stage, the more penetration of elements that reduce the melting point in the base metal. If the heating rate is too low and the heating step is too long, the maximum concentration of the soluble element in the interlayer may be lower than its required value for melting, and therefore, by increasing the heating step too much, there may be no Do not form a liquid. After the dissolution and expansion phase, the melting point lowering elements permeate across the solid/melt interface in the base metal during an isothermal holding period. This infiltration process is similar to multiphase infiltration coupling. To maintain thermodynamic equilibrium, the melt composition at the solid/melt interface remains constant at CLα. Therefore, the composition of the melt assumed uniform throughout the width of the liquid. Since diffusion is faster in the melt than in the solid, the thickness of the melt is too thin for this assumption to consider accurate. The direction and rate of movement of the solid/melt interface should create a mass balance in the solid/melt interface, so that the direction of movement of the two solid/melt interfaces is towards the center of the connection.

Abstract Microbiologically influenced corrosion (MIC) represents one of the most complex and destructive forms of material degradation, accounting for approximately 20% of global corrosion-related economic losses . This comprehensive review systematically examines the multifaceted nature of MIC, from fundamental mechanistic understanding to advanced detection methodologies and sustainable control strategies. The electrochemical framework governing MIC involves distinct mechanisms including extracellular electron transfer (EET-MIC), metabolite-mediated corrosion (M-MIC), and biofilm-driven microenvironmental alterations . Sulfate-reducing bacteria (SRB) emerge as primary culprits, responsible for approximately 75% of production well corrosion issues and 50% of pipeline system failures in the oil and gas sector . Recent advances in molecular biology, including multi-omics approaches (genomics, transcriptomics, proteomics) and gene editing technologies, have provided unprecedented insights into corrosion-related genes, proteins, and metabolic pathways . Detection methodologies have evolved from traditional culture-based techniques to sophisticated biosensors, electrochemical monitoring, and AI-driven predictive frameworks achieving >98% detection accuracy . Mitigation strategies encompass biocides, nanomaterials, coatings, quorum sensing inhibition, and emerging enzymatic remediation approaches . The review concludes that effective MIC management requires integrated, interdisciplinary approaches combining mechanistic understanding, advanced monitoring, and sustainable control technologies.

Abstract High-temperature oxidation and corrosion represent critical degradation mechanisms that severely impair the service life of metallic components across aerospace, power generation, and energy sectors, with turbine inlet temperatures in modern engines now routinely exceeding 1500 °C . This comprehensive review systematically examines the fundamental principles governing high-temperature oxidation, from thermodynamic foundations and diffusion-controlled kinetics to the protective characteristics of oxide scales. The parabolic rate law, derived from Wagner's theory of diffusion-controlled growth, provides the framework for predicting oxidation kinetics, with rate constants increasing exponentially with temperature as demonstrated by activation energies ranging from 171 kJ/mol for Ti-based refractory alloys to higher values for alumina-forming systems . The formation of protective oxide scales—primarily α-Al₂O₃ and Cr₂O₃—depends critically on alloy composition, with critical concentrations of Al (>5 wt.%) and Cr (>20 wt.%) required for continuous scale formation . Non-protective oxides with Pilling-Bedworth ratios substantially deviating from unity lead to rapid, often catastrophic, degradation through linear kinetics . Surface coating technologies, including thermal spray processes (HVOF, plasma spraying), diffusion coatings, and emerging high-entropy alloy coatings, have emerged as the primary engineering solution, with MCrAlY coatings forming stable α-Al₂O₃ scales and high-entropy alloy coatings demonstrating exceptional thermal stability and oxidation resistance through their unique core effects . The review concludes that effective high-temperature corrosion management requires integrated approaches combining mechanistic understanding, advanced coating technologies, and real-time monitoring.

Abstract The design of corrosion-resistant alloys for demanding applications requires predictive tools that can link molecular-scale phenomena to component-level performance across vastly different length and time scales . This comprehensive review systematically examines the multiscale computational framework for corrosion-resistant alloy design, integrating density functional theory (DFT), ReaxFF molecular dynamics (MD), and phase-field modeling. DFT provides quantum-level insights into surface/adsorbate interactions, crystal structure information including lattice distortion and density of states, and formation energies essential for understanding corrosion initiation . ReaxFF MD enables dynamic simulation of chemical reactions, oxide growth, and dissolution kinetics at extended time scales, with recent studies on Ni-Cr alloys identifying three distinct voltage-dependent kinetic regimes governed by competing oxide growth, dissolution, and reprecipitation . Machine-learned interatomic potentials trained on DFT data have emerged as a bridge between quantum accuracy and atomistic-scale simulation, enabling molecular dynamics simulations of complex oxide microstructures . Phase-field modeling has matured as a powerful mesoscale technique for simulating autonomous evolution of corrosion pits and localized corrosion morphologies, with grand-potential formulations enabling efficient simulation in multiphase alloys . The integration of these approaches with thermodynamic databases (CALPHAD) and finite element methods enables prediction of microstructural evolution, stress corrosion cracking, and component lifetime . This review concludes that next-generation alloy design requires seamless coupling of quantum, atomistic, mesoscale, and continuum methods, supported by machine learning and experimental validation.