Materials-based hydrogen storage is recognized for its high volumetric density, inherent safety, and seamless system integration, offering a practical route toward large-scale hydrogen deployment and deep decarbonization. Low-dimensional materials emerge as especially promising owing to their extensive surface area, tailorable chemistry, and short diffusion distances, which collectively enable high-capacity, reversible, and fast hydrogen storage. While extensive research has been devoted to specific materials, a cohesive understanding that interconnects findings across various material systems and yields transferable design principles remains lacking. This review develops an integrated mechanistic perspective spanning graphene derivatives, CN/BN/BCN frameworks, MXenes, transition-metal dichalcogenides, elemental monolayers, and emerging 2D architectures. The analysis covers polarization-enhanced physisorption, Kubas coordination, catalytic spillover, moderate chemisorption, and interlayer confinement, clarifying how structural motifs and chemical terminations govern adsorption energetics and reversibility. The most promising low-dimensional sorbents combine firmly anchored electropositive sites on graphene and nitrogen-rich frameworks, programmable terminations and galleries in MXenes that operate between physisorption and weak chemisorption, and composite architectures that enhance heat management and packing density. We further identify a shared near-ambient operating window and a set of device-aware metrics (working capacity, kinetics, cycling stability, and volumetric efficiency) as practical benchmarks to guide future synthesis, simulation, and prototype development.

The reversible hydrogen storage performance of two-dimensional TPDH-graphene monolayer decorated with alkali metal Na atoms (Na@C12) was investigated using first-principles calculations. The most stable Na decoration site was firstly identified, with a binding energy of −1.59 eV/atom. A 2 × 1 × 1 C12 monolayer supercell was then constructed fully decorated with four Na atoms at the stable sites. The Na@C12 monolayer demonstrated reasonable thermal stability and enhanced electronic properties. It can reversibly adsorb 16 H2 molecules, achieving a high hydrogen storage capacity of 8.48 wt%. The average adsorption energy ranged from −0.157 to −0.191 eV/H2, corresponding to desorption temperatures of 200–244 K. Furthermore, mechanistic analysis, including partial density of states, charge density difference, and reduced density gradient, revealed that hydrogen adsorption is primarily driven by a combination of orbital interactions, electrostatic forces, and van der Waals interactions. These results indicate that the Na@C12 monolayer is a highly promising material for efficient and reversible hydrogen storage, with strong potential for practical implementation. Additionally, this study broadens the application prospects of 2D C12 materials and offers valuable theoretical guidance for developing next-generation hydrogen storage systems.

Grain boundaries (GBs) are usually in a metastable state and contain various types of ledges in polycrystalline materials. The presence of these structural features may lead to heterogeneous solute segregation at nearly flat GBs in Al alloys and affect the mechanical properties of materials. In this study, the effects of GB structural features on solute segregation and dislocation nucleation are investigated by hybrid Monte Carlo and molecular dynamics simulations. The results demonstrate that local GB structural transitions and GB ledges result in the heterogeneous segregation of solutes Cu and Mg. The solute density at the GB is determined by the average segregation energy in different regions. Local structural transitions and ledges at GBs intensify strain localization, and result in a lower nucleation stress for dislocations compared to the ground-state GBs. A low concentration of the solute Cu tends to promote dislocation nucleation when it segregates at ground-state GBs, but inhibits it in other types of GBs. Conversely, the segregation of solute Mg promotes dislocation nucleation at all GBs. This difference is attributed to the effect of solute segregation on GB disorder. Increased GB disorder generates a stress gradient that provides an additional driving force for the atomic shuffling and free volume migration required for dislocation nucleation. Therefore, a negative correlation has been identified between GB disorder and dislocation nucleation stress.

This study employs molecular dynamics simulations to investigate hydrogen diffusion and deformation mechanisms in FeCrNi-based austenitic stainless steels, with a focus on the effects of alloying composition, temperature, and hydrogen concentration. Arrhenius analysis reveals that Cr increases, while Ni decreases, the activation energy for hydrogen migration. Alloys with low Cr and Ni contents (6 wt.%) promote FCC→BCC→HCP martensitic transformations, accompanied by stress drops, whereas high Cr or Ni levels (24 wt.%) suppress these transformations and favour dislocation plasticity dominated by cross-slip. High hydrogen concentrations reduce stacking-fault energy, activating dense Shockley partial dislocations in agreement with hydrogen-enhanced localised plasticity. Elevated temperatures and high hydrogen concentrations synergistically promote dislocation-mediated plasticity and facilitate vacancy formation, which can cluster into hydrogen-vacancy complexes and proto-nanovoids, accelerating material failure. These findings advance our understanding of the coupled effects of composition, hydrogen, and temperature on degradation in austenitic stainless steels and provide guidance for tailoring Cr/Ni ratios, controlling hydrogen content, and optimising service temperatures in the design of hydrogen-related structural alloys.

Grain boundary (GB) segregation plays a critical role in determining the structural stability and mechanical properties of nanocrystalline aluminum alloys. In this study, first-principles calculations combined with interpretable machine learning were carried out to investigate the segregation behavior of solute elements and their effect on GB strength. A dataset containing five GBs and 52 solute elements was constructed for the prediction of GB strength, incorporating descriptors related to GB structure, solute-matrix interaction, and the intrinsic solute properties. Machine learning with leave-one-GB-out validation achieves robust strengthening/weakening classification and quantitative regression using a low-cost feature group dominated by tabulated solute properties.

Physisorption is an attractive approach among the emerging approaches for storing hydrogen. Improving hydrogen storage in physisorption-based materials by incorporating alkali metals is considered a highly efficient strategy. This research explores the hydrogen storage potential of B12N12 monolayer modified with four lithium (Li) atoms, using first-principles calculations. Li decoration transfers a portion of its electrons to the B12N12 surface, thereby generating additional active sites favorable for hydrogen adsorption. A comprehensive investigation of the 4Li@B12N12 system showed a shift in electronic behavior from semiconducting to metallic, driven by electron transfer from the Li adatoms. Molecular dynamics results verified that Li atoms remained anchored at their optimal adsorption positions, preserving the structural stability of the host material. One 4Li@B12N12 substrate is capable of accommodating up to 13H2 molecules, achieving a remarkable storage capacity of 8.05 wt %, which surpasses the DOE benchmark of 5.5 wt%. The calculated adsorption energy of 4Li@B12N12+H2 fall within the ranges of-0.26 to-0.67 eV/H2. These results reveal that hydrogen adsorption on 4Li@B12N12 occurs efficiently, driven by a synergistic effect of weak orbital interactions and electrostatic attractions between the 4Li@B12N12 surface and H2 molecules. Furthermore, the desorption temperature decreases from 767.38 K to 332.53 K as the number of adsorbed H2 molecules increases up to 13, demonstrating reversible adsorption-desorption behavior within a practical temperature range. These findings provide valuable theoretical guidance for the development of efficient and reversible hydrogen storage systems, with promising implications for clean energy technologies and sustainable transportation.

Ti-based high-entropy alloys (HEAs), (Ti42.5Zr42.5Nb10Ta5)100-xMox (x = 0, 5), were developed and evaluated for tribocorrosion, mechanical, and corrosion performance under simulated physiological conditions (PBS and SBF at 37 degrees C). Both alloys exhibit a single-phase BCC solid-solution structure, and the addition of 5 at% Mo increases the yield strength from 703 +/- 14.5 MPa to 925 +/- 6.4 MPa while maintaining high ductility. Both alloys show excellent corrosion resistance, which is attributed to the formation of multi-component passive films composed of TiO2, ZrO2, Nb2O5/ NbO2, and Ta2O5; Mo addition introduces MoO2 into the passive film, modifying its electrochemical behavior and repassivation capability. Despite slightly higher friction coefficients, the HEAs exhibit significantly lower wear rates than TC4 alloy in both PBS and SBF. Material degradation is governed by a strong tribocorrosion synergy involving wear-induced depassivation and corrosion-assisted material removal. Mo alloying suppresses subsurface cracking and reduces material loss by enhancing mechanical strength and repassivation efficiency. Overall, the superior tribocorrosion performance of TiZrNbTaMo HEAs arises from the coupled effects of microstructural strengthening and passive film stability, highlighting their potential for wear-sensitive biomedical implant applications.

This study presents a data-driven surrogate strategy for efficient residual stress prediction in the cold-spray additive manufacturing. A comprehensive dataset was generated from thermomechanical finite element simulations, with residual stress values extracted as targets. Using key process parameters—nozzle travel speed, heat flux, and substrate thickness—several algorithms, including Random Forest, Extra Trees, and XGBoost, were evaluated. The Extra Trees model achieved the best performance, with the highest coefficient of determination (R²) and the lowest MAE, MAPE, and RMSE. Model interpretability was examined via SHapley Additive exPlanations (SHAP), indicating that element position played a leading role. The surrogate model was further validated by predicting residual stress distributions in components with increased deposition layers. Overall, the framework provides a fast and reliable alternative to computationally intensive simulations, enabling real-time process optimization and design exploration in cold-spray additive manufacturing.

High-temperature ammonia decomposition reactors expose structural alloys to reactive nitrogen species that can induce severe nitridation corrosion, yet the temperature- and position-dependent mechanisms governing this degradation within reactors remain poorly understood. In this study, the corrosion behaviour of 310S stainless steel in NH3 environments was systematically investigated at 400-700 degrees C using controlled corrosion experiments combined with SEM, EDS, XRD, and TEM analyses. A pronounced non-monotonic temperature dependence of corrosion was observed, with the maximum corrosion rate at 500 degrees C, characterised by thick nitrided layers, extensive delamination, and intergranular cracking. Corrosion severity also shows clear spatial dependence, with upper-layer specimens experiencing stronger degradation due to higher local NH3 activity. Phase analysis reveals a transition from CrN-dominated corrosion at 400 degrees C to CrN-Fe4N dual phases at 500 degrees C, while Fe4N disappears above 600 degrees C due to thermal instability. The severe corrosion at 500 degrees C is attributed to the combined effects of rapid nitrogen diffusion and Fe4N formation, which promote stress accumulation and crack propagation. These findings provide mechanistic insights into ammonia-induced corrosion and offer guidance for material selection and reactor operation in ammonia-based hydrogen systems.

Ammonia (NH3) is a promising hydrogen carrier, yet the corrosion mechanisms of pipeline steels in impuritycontaminated NH3 environments remain unclear. This study elucidates the effects of chloride ions (Cl- ) and dissolved oxygen (O2) on the corrosion behaviour of X80 pipeline steel in aqueous NH3. Electrochemical measurements, potentiodynamic polarisation, and surface characterisation reveal a mechanistic transition from Cl- dominated localised pitting to NH3-driven mild corrosion as NH3 concentration increases. Cl-exacerbates passive film breakdown and pitting, whereas NH3 suppresses Cl-aggressiveness via metal cation complexation. O2 contributes to partial passivation by facilitating the formation of Fe(OH)3 and Fe2O3, although the resulting films are discontinuous and microcracked. A mechanistic framework is proposed, highlighting the competitive and sequential interplay among NH3, Cl-, and O2, which provides guidance for corrosion control in NH3 storage and transport pipelines.

The widespread presence of antibiotic residues, such as tetracycline (TC), in natural water bodies poses a threat to ecosystems and human health. Developing photocatalysts capable of efficient and rapid separation of photogenerated charge carriers under ambient conditions with visible light irradiation offers an eco-friendly solution for mineralizing persistent organic pollutants. In this study, we designed and synthesized a novel pine cone-like SnO2/Bi2O2CO3 (SBC) Z-scheme heterojunction photocatalyst via a solvothermal method to enhance the degradation efficiency of TC in water. Comprehensive characterization via X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) confirmed successful heterojunction formation and revealed unique interfacial electronic properties. Photocatalytic experiments demonstrated that the SBC heterojunction significantly outperformed the individual components in degrading TC, achieving a TC removal efficiency of 81% after 70 min. This enhancement is attributed to the efficient separation and transfer of photogenerated charge carriers facilitated by the Z-scheme heterojunction structure.

Deposition efficiency (DE) in cold spray additive manufacturing (CSAM) is a key indicator for evaluating process efficiency. Here we develop a reduced-order model to predict DE of metals during CSAM by simultaneously calculating the critical velocity and impact velocity using the gas temperature, gas pressure, and particle size as inputs. The impact velocity must exceed the critical velocity to achieve particle adhesion. Since both the critical and impact velocities vary with particle size, DE can be derived from the intersection of these curves. An equation for calculating critical velocity is proposed based on the hydrodynamic spall mechanism with the support of experimental data. The impact velocity is determined using a parametric expression that accounts for the bow shock effect. The model is first calibrated for aluminum to create process design maps. Ten validation experiments are then conducted using two different cold spray systems. The experimental DE values show close agreement with the predicted results. The model can be used to rapidly identify optimal process parameters for achieving high DE of metals, contributing to improved process efficiency and product quality during CSAM.

Cold spraying (CS) of composite coatings produced from mixed metal powders can exhibit enhanced functional properties over coatings made from pure metals. However, controlling the deposition efficiency and the resulting microstructure during CS is challenging due to interactions between different materials. In this study, we developed a modelling framework to predict the deposition efficiency (DE) of mixed metal powders and the resultant coating composition. This is achieved by predicting the critical and impact velocities as a function of particle size, which allows determination of the DEs of both matched (A/A or B/B) and mismatched (A/B or B/A) particle/substrate combinations. These DEs are then used to determine the overall DE of the composite coating and its composition by using a layer-wise deposition model. The modelling framework is validated by performing several CS experiments using Cu and Al particles together with SEM image analyses of the coating microstructures. We find that in-flight interaction of particles of different masses has a significant effect on the impact velocity and hence DE of composite coatings. By effectively predicting DE and coating composition, the proposed model serves as a valuable tool for optimizing cold spray parameters, reducing trial-and-error costs and time, and accelerating the development of novel composite coatings with enhanced properties.

The g-C2O monolayer, notable for its electron-rich oxygen atoms and pronounced van der Waals (vdW) forces, presents itself as a viable candidate for hydrogen storage. Through first-principles based calculations, we explore a novel composite, Li@g-C2O, tailored for physical hydrogen adsorption. Lithium (Li) atoms are stably anchored onto the g-C2O surface with a binding energy of-1.747 eV, ensuring thermal stability at 300 K. The system can accommodate up to eight H2 molecules per unit cell, resulting in a total hydrogen storage capacity that exceeds the DOE target (2025). The desorption process occurs within a temperature range of 253 K-384 K, corresponding to average adsorption energy ranging from-0.152 eV/H2 to-0.101 eV/H2, highlighting its favorable kinetic properties for hydrogen release. The hydrogen adsorption mechanism leverages both vdW interactions and electrostatic effects, with the oxygen atoms acting as active sites. These results offer critical theoretical insights into designing high-performance hydrogen storage materials for energy applications, including sustainable transportation.

Fascinating physical phenomena often occur near the phase transition points in materials. This study provides a comprehensive investigation into the structural and magnetic properties of a Gd-Al alloy using both experimental and theoretical methods. The results indicate that the Gd-Al alloy exhibits a distinct antiferromagnetic phase transition under a low magnetic field. Theoretical calculations show a non-collinear alignment of magnetic moments on a crystal plane parallel to (001). A non-hysteretic metamagnetic transition, which suggests a magnetoelastic transition with discontinuous volume changes, is observed when the external magnetic field increases. The alloy demonstrates a significant magnetic entropy change of 16.5 J kg-1 K-1 at a field variation of 7 T. Additionally, it displays a giant magnetoresistance effect at low temperatures under the same field conditions. Electronic structure calculations reveal a high density of states (DOS) value near the Fermi level, mainly due to the Gd 5d electrons. The hybridization of Gd 5d and Al 2p orbitals, along with the observed 5d-4f hybridization near the EF, plays a crucial role in the electronic structure. This systematic analysis highlights the importance of an elevated DOS at the Fermi level in enabling the metamagnetic transition, which promotes the application of the Gd-Al alloy in energy-related fields.

While the single-particle impact model is widely used in studying the high-velocity impact behavior of particles, its scope is limited to the interaction between an individual particle and the substrate. In this work, a multi-particle molecular dynamics model was established to investigate the impact behavior of Cu nanoparticles and the surface quality of coatings. It was found that with the increase in particles' impact velocity from 100 m/s to 1500 m/s, three distinct coating structures can be identified: adhesion between nanoparticles, co-deformation, and liquefaction. Due to the anisotropy of plastic deformation, coatings formed by particles with the initial orientation [110] displayed the roughest surface, while those aligned with [111] and [001] exhibited smoother surfaces. Additionally, as nanoscale particles possess limited kinetic energy, it is difficult to create a large crater on the surface of the substrate. Therefore, it was necessary to elevate the temperature to soften the substrate, which can increase the crater depth and improve bonding quality. A successful approach to enhancing the bonding strength and surface quality of coatings involves simultaneous optimization of impact velocity, crystallographic orientation of particles, and substrate temperature.

The classic Hall-Petch model effectively captures the relationship between strength and layer thickness for thicknesses above 100 nm, while the constrained layer slip (CLS) model provides a better prediction for thicknesses below 100 nm. Nonetheless, the precision of the current CLS model is insufficient, especially for structures with FCC/HCP interfaces, which limits the development of lightweight composites such as Al/Mg. To address this gap, this study uses molecular dynamics (MD) simulations to explore the CLS mechanism under compression in Al/Mg composites. We propose a novel dual-mode CLS model aimed at enhancing the accuracy of stress predictions across a wide range of layer thicknesses and various slip angles. Our findings indicate that with decreasing layer thickness and the loss of lattice structure, the FCC/HCP interface becomes unstable and exhibits reduced strength when the layer thickness falls below 26.7 nm. Moreover, as the slip angle rises from 0 degrees to 75 degrees, the improved interface compatibility aids in the initiation of basal slip in the Mg layer. This triggers a migration of dislocations from the Al side to the Mg side, thereby altering the dominant CLS mechanism. This work is expected to accelerate the development of Al/Mg composites and other similar FCC/HCP composite systems.