The phase transformation behavior and strengthening mechanisms of a newly developed 2000 MPa grade Mn-Cr hot-stamped steel were systematically investigated. The critical cooling rate required for complete martensitic transformation is merely 0.3 °C/s. Furthermore, in-situ observations reveal that, upon heating, austenite nucleation occurs preferentially at ferrite/pearlite grain boundaries. Upon cooling, martensitic transformation proceeds via a three-stage burst sequence: instantaneous nucleation at austenite grain boundaries, rapid growth along the boundaries, and a sluggish final transformation, which leaves a small fraction of retained austenite. Additionally, annealing at 730 °C for 6 h yields a ferrite and grain boundary martensite structure, effectively suppressing the yield plateau and conferring excellent, uniform plastic deformation capability. Following oil quenching, the experimental steel develops a fully martensitic microstructure, exhibiting a yield strength of 1450 ± 30 MPa, an ultimate tensile strength of 2066 ± 25 MPa, and a total elongation of 7.9 ± 0.5%. Notably, dislocation strengthening is the dominant contributor, accounting for 68% of the total yield strength.
The incomplete combustion of hydrocarbon fuels produces carbonaceous particulate matter, i.e., soot. Although soot is a known atmospheric pollutant, it also serves a valuable precursor, which could be synthetic raw materials of carbon nanomaterials such as carbon dots (CDs). Carbon dots typically have sizes below 10 nm. They consist of a quasi-spherical carbon core composed of graphene-like fragments and a functionalized surface. This unique structure provides CDs with tunable chemical, optical, and electronic properties. Moreover, CDs generally exhibit low toxicity, distinctive fluorescence, high water solubility, thermal stability, chemical inertness, and ease of functionalization. This review summarizes flame-based methods for preparing CDs, including routes that use soot as a starting material. It also discusses strategies for tuning the properties of CDs and outlines their separation and purification techniques. The main findings are as follows: soot and CDs share a common structural origin; the flame method offers a green and efficient synthetic route; multi-parameter regulation enables targeted performance optimization; separation and purification are critical for enhancing the applicability of CDs; and the fluorescence mechanism of CDs, while complex, is controllable. This work aims to identify efficient and low pollution synthesis pathways, thereby significantly enhancing the environmentally friendly nature of CDs from a synthesis perspective.
Leakage during the solid-liquid phase transition remains a major obstacle for the practical application of phase change materials (PCMs) in thermal management. In the present study, we report a green, leakage-proof composite phase change material derived entirely from biomass, specifically utilizing the biodegradable corn stalk pith (CP) as the supporting matrix. Unlike the existing method of reducing CP into particles, this study retains the natural cylindrical shape of CP as supporting framework. Meanwhile the degradable eutectic mixture of Lauric acid (LA) and Myristic acid (MA) were introduced as phase change material. CP in the form of cylindrical segment was treated with hot water, NaOH, and delignification treatment to improve filling rate. Though Fourier transform infrared spectroscopy indicates that the combination of LA-MA with CP is a physical interaction, the intact natural foam morphology of CP segment effectively prevented the melted LA-MA from leaking. Among them, the delignified CP (CP-DL) presented the highest pore volume (49.37 mL/g) and absorption mass ratio (90.66%), which are far superior to those of CP particles. The result composite phase change material melts at an appropriate phase transition temperature of 32.76°C for comfortable living conditions and exhibits a high latent heat of 141.3 J g−1. It exhibits good thermal stability at working temperatures even after 100 thermal cycles. As an environmentally friendly natural material, the composite phase change material based on CP cylinder shows its great potential applications in thermal management area.
Hydrogen storage remains a major barrier to the large-scale deployment of hydrogen energy. High-entropy alloys (HEAs) offer broad compositional flexibility for tuning phase constitution and hydrogen sorption behavior. Among them, dual-phase HEAs combining a body-centered cubic (BCC) major phase with a secondary Laves phase have attracted increasing attention. The BCC phase provides high hydrogen capacity, whereas the Laves phase improves activation, hydrogen transport, and cycling stability. This review examines how the two phases and their interphase boundaries act together across the successive stages of hydrogen storage. It then surveys compositional design methods spanning empirical criteria, CALPHAD, first-principles calculations, and machine learning, together with preparation and processing strategies for regulating the dual-phase microstructure. Reported performance is analyzed within individual composition series, covering capacity, activation, kinetics, dehydrogenation, and cycling stability. Key challenges are also discussed, including incomplete near-ambient dehydrogenation, the capacity-durability trade-off, limited predictive capability for dual-phase systems, and the engineering gaps in cost, scalable production, impurity tolerance, and heat management. Finally, future directions toward phase-resolved characterization, architecture-level design, and application-oriented evaluation are outlined.
Surface cooling devices are widely utilized to lower circulating drilling fluid temperature, whereas they are generally constrained by inadequate cooling capacity and poor heat transfer efficiency. Enhancing the thermal conductivity of drilling fluids is an effective approach to mitigate these limitations. In this work, boron nitride nanosheets (BNNS) were exfoliated via wet grinding coupled with high-pressure homogenization, adopted as high thermal-conductivity fillers for water-based drilling fluids (WBDFs). Experimental results reveal that BNNS can prominently elevate the thermal conductivity of aqueous solutions and WBDFs. At the optimal dosage of 1.5 wt%, the thermal conductivity of modified WBDFs reaches 0.878 W/(m·K) with a 21.4% enhancement, and remains 0.827 W/(m·K) after 16 h thermal aging at 200 °C. BNNS also ameliorates WBDFs rheological and filtration performances and inhibits high-temperature deterioration of viscosity and fluid loss. Mechanism analysis demonstrates that the improved thermal performance stems from the inherent high thermal conductivity of BNNS, constructed thermally conductive networks and reduced interfacial thermal resistance. Numerical simulations confirm that high-thermal-conductivity drilling fluids can significantly strengthen surface cooling performance, yielding a 36.9% increase in annular fluid temperature reduction. This study provides a feasible scheme for developing high-thermal-conductivity WBDFs and offers support for practical surface cooling system optimization.
This work establishes a yield strength model with respect to the precipitation driving force of heat-treatable aluminum (Al) alloys based on thermo-kinetic synergy. In combination with the classical nucleation/growth theory and the Kinetic Monte Carlo simulations, the structural features of short-range order (SRO) for atomic arrangement in solute clusters and the precipitation strengthening effects of 6xxx Al alloys are analyzed in terms of their influential factors. It turns out that increasing the alloy's Mg/Si ratio can enhance the precipitation driving force for solute clusters during natural aging, which favors the formation of the Mg-rich (Mg/Si ratio >1.5) clusters that contribute to the cluster strengthening effects. Increasing the aging temperature can promote the SRO features of atomic arrangement in solute clusters and accelerate their transition to the β″ phase. The dislocations introduced by an appropriate pre-strain treatment before isothermal aging can provide the pipe diffusion pathways for solute atoms, which increases the precipitation driving force for solute clusters, thus improving their strengthening effects. But an excessive pre-strain can decrease the solute concentration in α-Al matrix and decrease the precipitation driving force for solute clusters, thus weakening the cluster strengthening contribution. Our investigation provides an innovative insight into understanding the structural features of SRO solute clusters and the precipitation strengthening effects of 6xxx Al alloys, thus benefit to the development of advanced high-strength Al alloys.
One major challenge in applying a combined DFT–machine learning framework to high-strength, high-conductivity copper alloys is that conventional ground-state DFT alone does not straightforwardly provide conductivity data suitable for ML training. Recent advances in first-principles transport methods, including Boltzmann-transport, Kubo-Greenwood, and CPA-based approaches, however, show promise in overcoming this limitation for alloy systems. This paper systematically reviews the core strengthening mechanisms and representative microstructures of high-strength, high-conductivity copper alloys for applications such as aerospace power systems, electronic packaging, and high-end electrical connectors (e.g., graphene/copper composites, fiber-reinforced systems, coherent interfaces, and heterointerfaces). It further examines the application of DFT in alloy design—including thermodynamic stability assessment, electronic-structure analysis, and mechanical property prediction—and spotlights emerging trends in its integration with machine learning.
Heavy metal contamination severely threatens ecological systems and human well-being. Developing cost-efficient coal gangue-based geopolymers (CGGs) for heavy metal (HM) solidification/stabilization remains a critical challenge. Herein, machine learning (ML) and density functional theory (DFT) were integrated to probe key factors governing HM remediation by CGGs. A suite of analyses were performed. The random forest (RF) model exhibited superior predictive performance for HM solidification efficiency versus other ML models, with high accuracy and generalization capability. SHAP and PDP analyses identified pivotal factors (S/L, post-curing time, Na/Al ratio). DFT calculations verified that Ca vacancies enhance the adsorption stability of Pb, Cu and Cr. These superiorities stem from the synergy of ML-guided optimization and DFT-elucidated mechanisms, enabling precise regulation of material properties. This study provides a novel hybrid strategy for high-performance HM adsorbents, with great potential for engineering applications.
Edge computing and in-memory computing architectures demand non-volatile memory devices that simultaneously possess high-speed operation to match processor units, high thermal stability to accommodate complex ambient temperatures, and sufficient cycling endurance to support frequent weight updates. Sb2Te3, as a phase change material with nanosecond level operation speed, offers significant speed advantages over conventional Ge2Sb2Te5. However, its poor thermal stability with crystallization occurring at room temperature severely limits practical applications. To address this bottleneck, the Re-Sb2Te3 compound prepared in this paper significantly increased the crystallization temperature (277°C) and the ten-year data retention temperature (190.5°C). The Re0.188Sb2Te3 device exhibits reversible switching with a minimum pulse width of 6 ns. Stable endurance up to 105 cycles was further achieved under optimized programming conditions of 0.7 V/200 ns for SET and 2.2 V/100 ns for RESET. Furthermore, combined experimental and first principles calculations reveal the microscopic mechanism by which rhenium doping regulates crystallization kinetics and enhances thermal stability. This work effectively provides new insights for exploring phase change memory materials that combine high operation speed with high thermal stability, demonstrating application potential in edge computing and in-memory computing.
Aiming at the mechanistic disputes over the coexistence of positive and negative effects of natural aging in 6xxx series aluminum alloys for automotive structural components, as well as the technical bottleneck that alleviating negative aging effects cannot be well balanced with maintaining high strength, this study proposes a novel technical route combining solute content ratio design with precise natural aging regulation. By constructing optimal natural aging clusters, 6xxx series aluminum alloys for automotive structural parts with superior mechanical properties and excellent resistance to negative aging effects are ultimately fabricated. This study systematically reveals the intrinsic influence laws of solute atom proportioning and natural aging processes on the nucleation, growth and compositional evolution of atomic clusters in alloys. Combined with multi-scale characterization techniques, the atomic-scale compositional characteristics of clusters are accurately analyzed, and the triggering conditions and kinetic mechanisms of cluster type transformation are clarified. The structural inheritance mechanism for the transformation from clusters to GP zones and β'' phases as well as the critical conditions for the reversal of precipitation sequences are defined, which ultimately uncovers the essence of the bimodal natural aging behavior of 6xxx series aluminum alloys. The research findings provide a theoretical basis for the precise microstructure regulation of high-performance lightweight aluminum alloys and solid technical support for their industrial application, facilitating the coordinated improvement of lightweight design and safety performance in automobiles.
Superior mechanical performance can be achieved through the rational combination of soft and stiff materials in multilayered, hybrid, or heterogeneous architectures. However, the mechanical response of such composite structures is fundamentally constrained by the intrinsic properties of the individual soft and stiff constituents. In this study, stiff polyamide 12 (PA 12) and soft thermoplastic polyurethane (TPU) fabricated by selective laser sintering (SLS) were selected as representative materials, and their printability, tensile behavior, flexural performance, and structural adaptability in triply periodic minimal surface (TPMS) lattices were systematically investigated. The results show that the surface roughness of SLS-fabricated TPU is approximately twice that of PA 12, mainly owing to the irregular and angular morphology of TPU powders compared with the smooth and spherical PA 12 powders. Based on the average values across the X, Y, and Z printing directions, the Young's modulus, tensile strength, yield strength, flexural modulus, and flexural strength of SLS-fabricated PA 12 are approximately 18, 6.5, 4, 26, and 15 times those of TPU, respectively, whereas TPU exhibits an elongation at break approximately four times that of PA 12. By combining the present results with literature data, distinct material-dependent tensile relationships are identified. The tensile strength of PA 12 shows a positive correlation with Young's modulus, whereas that of TPU is more closely associated with elongation at break than with Young's modulus. Representative TPMS lattice architectures, including Gyroid, Primitive, and Diamond structures, were successfully fabricated from both PA 12 and TPU, confirming the capability of SLS to produce geometrically complex polymer lattices. Literature-assisted analysis further indicates that the specific energy absorption (SEA) of TPMS lattices generally increases with matrix strength. Linear fitting of SEA against relative density suggests that stronger matrix materials exhibit larger fitting slopes, indicating a higher sensitivity of SEA to relative density. However, this increased sensitivity also amplifies the influence of manufacturing-related variations, leading to larger SEA scatter, as reflected by lower R2 (coefficient of determination) values and higher RMSE (root mean square error) values. Our work provides a useful reference for the composite design of soft–stiff material systems.
Accurate impurity diffusivities are essential for quantitative understanding of diffusion-controlled processes in Ni-based alloys, yet reliable evaluation from interdiffusion composition profiles remains challenging due to fitting errors and the lack of quantitative uncertainty assessment. In this work, a rigorous uncertainty-quantification framework is developed for impurity diffusivities evaluated using the Hall method by systematically identifying error sources and their propagation. By integrating the Hall method, a distribution-function library, and the proposed uncertainty framework, a robust evaluation procedure is established and validated through 450 benchmark tests covering different diffusivity–composition relations and noise levels. The method is further applied to 9152 experimental data points from 124 diffusion couples to determine impurity diffusivities with quantified uncertainties for 21 alloying elements in pure Ni. Based on the assessed results, Arrhenius parameters for impurity diffusion of 17 elements are re-evaluated using weighted regression considering uncertainty. The correlation between activation energy and pre-exponential factor is analyzed to obtain empirical relationships, enabling prediction of impurity diffusivities for elements with limited or unavailable experimental data. This work provides a general framework for extracting impurity diffusivities with quantified uncertainties and establishes a consistent dataset and predictive capability for impurity diffusion in pure Ni.
Silicon monoxide (SiOx, 0 < x < 2) is a promising next-generation anode for lithium-ion batteries owing to its high theoretical capacity and the in situ formation of buffering Li2O and lithium silicate matrices that mitigate volume expansion. However, conventional high-temperature carbonization promotes excessive disproportionation of SiOx into electrochemically active Si and inert SiO2, which simultaneously coarsens nano-Si grains and consumes the active phase, leading to capacity loss and structural deterioration. Here, a confined-disproportionation strategy combining short-duration low-temperature carbonization (600 °C, 5 min) with subsequent high-energy ball milling is reported. The brief thermal step rapidly carbonizes the pitch coating while preserving an amorphous SiOx framework, and the milling step disperses the SiO@C particles into a graphite scaffold and triggers a localized, in situ disproportionation that introduces a controlled fraction of crystalline Si. The resulting SiO@C–graphite composite delivers a reversible capacity of 573 mAh g−1 after 500 cycles at 0.5C and 494 mAh g−1 at 1 C (capacity retentions of 95.5% and 94.8%, respectively) at 25 °C, and retains 748 and 786 mAh g−1 after 150 cycles at 45 and 60 °C. In situ XRD and quantitative kinetic analysis reveal that lithium storage proceeds through a reversible amorphous evolution of SiOx coupled with staged graphite intercalation, with surface-controlled pseudocapacitance contributing up to ∼90% of the capacity at 1.0 mV s−1. This work demonstrates that decoupling thermal carbonization from disproportionation through a thermal–mechanical sequential design provides a generalizable route to balance amorphous robustness and crystalline activity in SiOx-based anodes.
Contrary to the commonly anticipated metallization or structural complexity under compression, heavy alkali metal sulfides (K, Rb, and Cs) are found to undergo unexpected decomposition at high pressure. The structural and electronic characteristics of MexSy (Me = Li–Cs) are explored across a wide pressure range through a combination of first-principles calculations and CALYPSO-based structure searches. A variety of previously unidentified stable compounds with unconventional stoichiometries are predicted. Our results indicate that, under sufficient compression, heavy alkali metal sulfides tend to break down into their elemental constituents rather than forming more complex compounds. Compression leads to substantial broadening and activation of metal d states, thereby increasing their contribution below the Fermi level. This promotes electron back-transfer from S 3p states to metal d states, thereby weakening the ionic interaction. At the same time, the population of antibonding states destabilizes S–S linkages within the sulfides, making their covalent bonding less favorable compared to that in elemental sulfur. In contrast, elemental sulfur adopts energetically more stable, highly coordinated covalent networks under compression. The observed decomposition can thus be understood as a consequence of pressure-driven orbital reorganization together with the intrinsic stability of dense sulfur networks. These findings may significantly influence the understanding of sulfur chemistry in the deep interiors of giant planets.
Magnesium-doped ZnO (ZMO) ferroelectric capacitors were successfully fabricated via atomic layer deposition (ALD). The crystallinity of ZMO improved with increased annealing temperature and time, reaching optimal ferroelectric properties after annealing at 600 °C for 30 min. Films deposited on Pt substrates exhibited superior crystallization and density compared to those on TiN. Ferroelectric tests showed that Pt/ZMO/Pt capacitors achieved a remanent polarization (2Pr) of 1.9 μC/cm2 and a coercive field (Ec) of 1.2 MV/cm. Additionally, piezoelectric force microscopy (PFM) measurements confirmed 180° domain switching in the annealed ZMO films, further validating their ferroelectric behavior.
