A safe, clean, and cost-effective H 2 production system is critically important for developing hydrogen energy. Sodium hypophosphite (NHP) represents a promising hydrogen carrier due to its high stability, low cost, and abundance. In the presence of appropriate catalysts, NHP can easily react with water under mild conditions to yield high-purity H 2 but without any gaseous by-products. In this work, we report an efficient room-temperature H 2 production system containing the supported CuPd/TiO 2 as a catalyst, and NHP and water as hydrogen carriers (hydrogen sources). The H 2 production rate is 13.53 mL·min − 1 (135.3 mL·min − 1 ·g − 1 ) and NHP reaches 100% conversion within 30 min. The CuPd/TiO 2 catalyst also exhibits excellent stability and recyclability toward H 2 production. Cu generates both geometric and electronic effects in CuPd/TiO 2 catalyst. Pd nanoparticles are more dispersive, and their sizes are smaller with the help of Cu. The electronic interaction between Cu and Pd leads to an increased d-band holes of Pd, which is beneficial for the adsorption of H 2 PO 2 − and reduce the activation energy of H 2 PO 2 − dehydrogenation. This work develops a new cost-economic and highly efficient catalytic H 2 production system, which is expected to contribute to development of hydrogen economy, especially hydrogen–oxygen fuel cell.

A safe, clean, and cost-effective H2 production system is critically important for developing hydrogen energy. Sodium hypophosphite (NHP) represents a promising hydrogen carrier due to its high stability, low cost, and abundance. NHP can hydrolyse under mild conditions to yield H2 without any gaseous by-products. In this work, we report clean and efficient H2 production at room temperature using CuPd/TiO2 catalytic NHP hydrolysis with the rate of 13.53 mL·min−1 (135.3 mL·min−1·g−1) and 100% NHP conversion within 30 min. The catalyst also exhibits excellent recyclability toward H2 production. The two metals in CuPd/TiO2 exhibit a synergistic effect, Cu can facilitate the activation and dissociation of water, whereas Pd sites accelerate the activation and dehydrogenation of H2PO2−. This work develops a new cost-economic and highly efficient catalytic H2 production system, which is expected to contribute to development of hydrogen economy. Sodium hypophosphite (NHP) represents a promising hydrogen carrier due to its high stability, low cost and abundance, however, its potential as a source for hydrogen production remains underexplored. Here, the authors report a room-temperature, additive-free, hydrogen production system based on NHP and water as carriers and CuPd/TiO2 as a catalyst, with NHP reaching 100% conversion within 30 min and a hydrogen production rate of 135.3 mL·min−1·g−1.

Catechol, a common aromatic diol pollutant, poses significant ecological risks due to its persistence and toxicity. However, precise monitoring is challenged by complex sample matrices when relying on a single analytical mode. To address this, a dual-mode sensing platform for catechol was developed using a spatially engineered indium (In) single-atom nanozyme. Highly dispersed In single atoms were anchored on a S,N-codoped porous carbon matrix (InSAs@S-NC) via a NaCl template-assisted ion-imprinting strategy, effectively preventing active site aggregation and enhancing catalytic performance. The InSAs@S-NC nanozyme exhibited outstanding oxidase-like activities, enabling the colorimetric detection of catechol through two distinct chromogenic pathways. When coupled with its inherent electrochemical activity, the nanozyme also facilitated highly sensitive electrochemical analysis for catechol. Consequently, the dual-mode sensing system based on InSAs@S-NC achieved wide linear ranges (colorimetric modes: 10-500 μM for reduction system and 5-200 μM for oxidation system, electrochemical mode: 2-443 μM) with low detection limits (0.11, 0.16, and 0.38 μM, respectively). Practical utility was demonstrated by analyzing catechol in environmental and beverage samples (water, sewage, and red wine), showing high recoveries (98.9-110.2%), good reproducibility, and consistent cross-verification between modes (deviation <5.6%). This study revealed that the spatial confinement of In atom sites promoted reactant affinity and electron transfer, underpinning enhanced multi-enzyme and electrocatalytic activities. This work highlighted spatial engineering as an effective strategy for designing robust multi-functional nanozymes and presented a reliable dual-mode sensing approach for environmental pollutant monitoring.

Abstract Prussian blue analogues (PBAs) are promising cathodes for sodium-ion batteries, yet intrinsic [Fe(CN)6] vacancies, interstitial water, and poor electronic conductivity compromise their rate capability and structural stability. Here, we develop a sequential dual-modification strategy that simultaneously suppresses lattice defects and constructs a three-dimensional (3D) conductive network. Sodium carboxymethyl cellulose (CMC) regulates crystallization to minimize [Fe(CN)6] vacancies and coordinated water, thereby stabilizing the open framework, while Ketjen black (KB) forms an interconnected conductive matrix that promotes charge-transfer kinetics through host–guest electronic hybridization. This multiscale regulation accelerates Na+ transport and reduces interfacial resistance, enabling the optimized PBA cathode to deliver 109.2 mAh g–1 at 5 A g–1 and retain 86.6% of its capacity after 10,000 cycles. This work establishes a generalizable strategy integrating defect suppression and electronic hybridization for designing durable, high-rate electrode materials for high-power energy storage.

Atomically dispersed Fe single-atom catalysts are engineered with S as a second-shell environmental modulator rather than a direct ligand. This configuration delivers superior ORR activity and excellent zinc-air battery performance, while resolving a long-standing controversy over the coordination role of S.

Rational design of high-performance, low-cost oxygen reduction reaction (ORR) catalysts is critical for advancing zinc-air batteries (ZABs). This study proposed a closed-loop paradigm integrating first-principles active site identification, precursor-ratio-controlled synthesis, and device validation to develop superior metal-free ORR electrocatalysts. Density functional theory (DFT) calculations identify pyridinic-N as the optimal doping configuration, exhibiting the lowest energy barrier (0.17 eV) for the rate-determining step (RDS, *O-2 -> *OOH). Further electronic structure analyses revealed that this enhancement originates from pyridinic-N-induced upward shifts in the p-band center of adjacent carbon atoms during the RDS, establishing this shift as a universal activity descriptor. Guided by these insights, aniline(A)/pyrrole(P) co-polymerization with precise monomer molar ratio control yielded a series of N-doped carbon materials (A(x)P(y)-NC). A(0.5)P(0.5)-NC achieved the highest pyridinic-N content (38.91%), demonstrating exceptional ORR activity that surpasses other A(x)P(y)-NC variants and the benchmark 20 wt.% Pt/C. The optimized catalyst enabled transformative ZAB performance in liquid and flexible configurations, achieving enhanced open-circuit voltage, superior power densities, high specific capacities, and prolonged durability compared to commercial 20 wt.% Pt/C. This work establishes a catalyst development paradigm bridging mechanistic understanding, controllable synthesis, and practical application for next-generation energy storage devices.

Sodium-ion batteries (SIBs) are promising for large-scale energy storage, with cathode materials being key to their electrochemical performance. Recently, Na3Fe2(PO4)P2O7 has drawn attention as a potential cathode material for SIBs due to its low cost and stable crystal structure. In this study, we prepared a porous Na3Fe2(PO4) P2O7 (NFPP) and introduced nano-BaTiO3 (BT) to create a composite cathode. The synthesized Na3Fe2(PO4) P2O7-3 %BaTiO3 (NFPP-3BT) delivered a reversible capacity of 62.7 mAh g- 1 at an ultra-high rate of 120C and exhibited a long cycle life of 2000 cycles at 10C with a capacity retention of 80.5 %. The high-rate performance is attributed to the synergic effect of the porous structure of NFPP and the polarization electric field from BT's ferroelectricity, enhancing the Na+ diffusion. Moreover, the strong adsorption energy for sodium salt anions on the BT surface accelerates the desolvation process and improves the stability of cathode electrolyte interphase (CEI), further improving the rate and cycling performance of NFPP. This work unveils a new strategy for achieving both high-rate capability and excellent cycle stability in SIBs through the synergistic effect of mixed polyanionic cathode materials and ferroelectric materials.

The development of oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER) electrocatalysts with low-cost, high activity and stability is critical to the advancement of novel clean and sustainable energy technologies. Non-precious metal catalysts offer promising alternatives to expensive platinum-based materials. Herein, we designed and synthesized two BODIPY-based supramolecular complexes, BODIPY-Mn-bipy-I and BODIPY-Mn-bipy, as bifunctional electrocatalysts for ORR and HER. The resultant BODIPY-Mn-bipy-I catalyst exhibited bifunctional catalytic performance for ORR and HER, in which the half-wave potential for ORR was 0.84 V and the over-potential for HER was 36 mV at 10 mA cm- 2. DFT calculations revealed that BODIPY-Mnbipy-I catalyst demonstrated better electrocatalytic activity compared to BODIPY-Mn-bipy catalyst. Furthermore, the zinc-air battery assembled with BODIPY-Mn-bipy-I catalyst exhibited a peak power density of 176 mW cm- 2 and a specific capacity of 815.2 mAh g- 1 at 5 mA cm- 2. This work provides a new way to explore the application of non-precious metal molecular catalysts in electrochemical energy storages and conversion systems.

A data-free predictive scientific AI model, termed Tensor-decomposition-based A Priori Surrogate (TAPS), is proposed for tackling ultra large-scale engineering simulations with significant speedup, memory savings, and storage gain. TAPS does not require any training data and can effectively obtain surrogate models for high-dimensional parametric problems with equivalently zetta-scale (1021) degrees of freedom (DoFs) using a single GPU. TAPS achieves this by directly obtaining reduced-order models through solving the weak form of the governing equations with multiple independent variables such as spatial coordinates, parameters, and time. The paper first introduces an AI-enhanced finite element-type interpolation function called convolution hierarchical deep-learning neural network (C-HiDeNN) with tensor decomposition (TD). Subsequently, the generalized space-parameter-time Galerkin weak form and the corresponding matrix form are derived. Through the choice of TAPS hyperparameters, different convergence rates can be achieved. To show the capabilities of this framework, TAPS is then used to simulate a large-scale additive manufacturing process and achieves around 1,370x speedup, 14.8x memory savings, and 955x storage gain compared to the finite difference method with 3.46 billion spatial DoFs. As a result, the TAPS framework opens a new avenue for many challenging ultra large-scale engineering problems, such as additive manufacturing and integrated circuit design, among others.

The oxygen reduction reaction (ORR) plays a vital role in many next-generation electrochemical energy conversion and storage devices, motivating the search for low-cost ORR electrocatalysts possessing high activity and excellent durability. In this work, we demonstrate that iron-cobalt phosphide (FeCoP) nanoparticles encapsulated in a N-doped carbon framework (FeCoP@NC) represent a very promising catalyst for the ORR in alkaline media. The core-shell structured FeCoP@NC catalyst offered outstanding ORR activity with a half-wave potential (E1/2) of 0.86 V vs reversible hydrogen electrode (RHE) and excellent stability in a 0.1 M KOH electrolyte, outperforming commercial Pt/C and many recently reported noble-metal-free ORR electrocatalysts. The superiority of FeCoP@NC as an ORR electrocatalyst relative to Pt/C was further verified in prototype zinc-air batteries (ZABs), with the aqueous and flexible ZABs prepared using FeCoP@NC offering excellent stability, impressive open circuit voltages (1.56 and 1.44 V, respectively), and high maximum power densities (183.5 and 69.7 mW cm-2, respectively). Density functional theory calculations revealed that encapsulating FeCoP nanoparticles in N-doped carbon shells resulted in favorable electron penetration effects, which synergistically regulated the adsorption/desorption of ORR intermediates for optimal ORR performance while also boosting the electronic conductivity. Our findings offer valuable new insights for rational design of transition metal phosphide-based catalysts for the ORR and other electrochemical applications.

The laser-assisted wire-directed energy deposition (DED) process has distinct advantages over the laser-assisted powder DED process. The material usage efficiency of wire-DED is predominantly higher than the powder-DED process. As versatile as the DED process can be, its multiphysics in situ integrated with the process parameters is key to achieving a qualitative layer deposition. This research demonstrates a computational fluid dynamics (CFD) modeling of the coaxial multiple laser-assisted single wire-DED process in conjunction with the already published experimental coaxial laser-assisted single wire-DED process. This wire-DED process involves four lasers coaxially aligned with its central axis for a single wire feed. The CFD model helps predict the wire melting, mass transfer, and melt pool dynamics that are otherwise difficult to understand using the experiments. The geometric dimensions of the simulated thin wall and the experimental thin wall match greatly throughout the length of the deposition. This experimental validation further allows one to study the effect of multiple laser incident angles on the single wire, wire-multiple laser interactions, and its cumulative impact on the deposition.

Phosphorization of molybdates has been shown to promote hydrogen evolution reaction (HER) activity but is usually detrimental to oxygen evolution reaction (OER) activity, frustrating efforts to create bifunctional HER/ OER electrocatalysts. Herein, we show that Fe2O3-modulated P-doped CoMoO4 on nickel foam (Fe-P-CMO) is an excellent bifunctional HER/OER electrocatalyst in alkaline media, with the adverse effect of phosphorization on the OER activity of CoMoO4 being countered via Fe2O3 introduction. An alkaline splitting electrolyser assembled directly using the self-supporting Fe-P-CMO electrode possessed outstanding long-term durability with ultralow cell voltages of 1.48 and 1.59 V required to achieve current densities of 10 and 100 mA cm-2, respectively. Detailed experimental investigations showed that during HER, P-doped CoMoO4 in Fe-P-CMO underwent surface reconstruction with the in-situ formation of Co(OH)2 on the P-CoMoO4 (Co(OH)2/P-CoMoO4). During OER, Pdoped CoMoO4 was deeply reconstructed to CoOOH with the complete dissolution of Mo, leading to the in-situ formation of Fe2O3/CoOOH heterojunctions.

The optimization of band structure, properties, and the extending of applications for metal–organic frameworks (MOFs) is highly desired by researchers. In order to explore the patterns of influence of the ligands to band structures, a series of MOFs using dicarboxylic acids: fumaric acid (Fumas), 2,5-thiophene dicarboxylic acid (TDC), terephthalic acid(H2BDC), and 2-amino terephthalic acid(H2ATA) as ligands, respectively, and zirconium as metal nodes were synthesized by hydrothermal method in this work. The results reveal that the density of electron cloud increases with the increase of number of ligand carbon–carbon double bonds, and the density of electron cloud has an obvious effect on the band structure of MOFs that the higher the density of the electron cloud of ligands, the higher the energy position of Highest Occupied Molecular Orbital (HOMO), the narrower the band gap, and the more positive the valence band of MOFs with the normal hydrogen electrode potential level (NHE.) as a reference. Regarding photocatalytic performance, H2BDC-Zr showed the highest degradation efficiency, degrading 91.09

Currently almost all the directed energy deposition (DED) processes are performed under ideal lab conditions with the room temperature close to 20 C. By contrast, the cold-temperature DED has potentially onsite use in cold environments, such as the winter in the Northern Hemisphere, where the ambient temperatures are often near or below freezing point temperature (0 C). However, there is a lack of study on the cold-temperature DED process due to its unique temperature conditions. To fill this gap, the authors employed both multi-physics modelling and experimental approaches to study the DED process at cold temperature (CT) -3 C-degrees, and compare to the room temperature (RT) 20(degrees) C DED process. Stainless Steel 316L (SS316L) was selected as powder material. The multiple physics in the DED process involving laser heat source, local melting, rapid cooling, solidification, phase change, evaporation, and fluid-gas interactions were modeled using the computational fluid dynamics (CFD) - volume of fluid (VOF) approach. To validate the model, the DED experiments were conducted using a cryogenic DED platform in which the DED process was chilled to customized low temperatures. This highfidelity model predicted accurate thermal results and deposit geometries for both the CT and RT DED cases. The results show that under sub-freezing conditions, the deposit size of the CT-DED is similar to 62.1 % bigger than the RTDED in the mean area throughout the length of the single-track thin wall. Furthermore, the CT-DED results show a steeper thermal gradient and at the same time a lower heat flux near the substrate. This high-fidelity modelling framework can be effectively expanded to study more cold-temperature additive manufacturing cases, like the Arctic exploration and in-Space manufacturing.

Na2Ti3O7-based anodes show great promise for Na+ storage in sodium-ion batteries (SIBs), though the effect of Na2Ti3O7 morphology on battery performance remains poorly understood. Herein, hydrothermal syntheses is used to prepare free-standing Na2Ti3O7 nanosheets or Na2Ti3O7 nanotubes on Ti foil substrates, with the structural and electrochemical properties of the resulting electrodes explored in detail. Results show that the Na2Ti3O7 nanosheet electrode (NTO NSs) delivered superior performance in terms of reversible capacity, rate capability, and especially long-term durability in SIBs compared to its nanotube counterpart (NTO NTs). Electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM) investigations, combined with density functional theory calculations, demonstrated that the flexible 2D Na2Ti3O7 nanosheets are mechanically more robust than the rigid Na2Ti3O7 nanotube arrays during prolonged battery cycling, explaining the superior durability of the NTO NSs electrode. This work prompts the use of anodes based on Na2Ti3O7 nanosheets in the future development of high-performance SIBs.

Developing visible-light response photocatalysts with high activity and adsorption alongside sustainability is vitally important to environmental restoration. Here, we fabricated a novel metal organic framework (MOF) with cost-effective double-ligands (fumaric acid and 2-aminoterephthalic acid as ligand precursors, denoted as MA-MOF) via a facile solvothermal method. Specifically, crystalline [Zr6O4(OH)4(fumarate)6] (MOF-801) can be only formed with monocarboxylic acids as modulators. Therefore, in the construction of crystalline double-ligand MA-MOF, the absence of monocarboxylic acid modulators successfully prevents the formation of crystalline MOF-801. Instead, the crystalline double-ligand MA-MOF is formed. Properties of MA-MOFs including the surface area, porosity, charge transfer resistance, and energy level position can be adjusted via altering the ratio of ligands. The optimal sample, MA-MOF2 (prepared with a molar ratio of fumaric acid and 2-aminoterephthalic acid being 2:1), shows a total 94.6% removal of tetracycline via adsorption and photodegradation, far exceeding the corresponding single-ligand counterparts. This work proposes an innovative inverted modulator strategy for constructing double-ligand MOFs.

Seawater electrolysis is a valuable and promising method for clean hydrogen generation. The corrosion induced from active anions in seawater and the competition between oxygen evolution reaction (OER) and chloride evolution reaction (CER) limit the overall efficiency of seawater electrolysis. Herein, shielding strategy was introduced with cinnamate anion (CNA) intercalated in NiFe LDHs (NiFe LDHCNAs) for efficient alkaline seawater oxidation. It displays an outstanding OER performance with 247 mV and 258 mV to achieve the current density of 50 mA/cm2 in 1 M KOH electrolyte and alkaline seawater (1 M KOH + real seawater), respectively. Meanwhile, CNA-NiFe LDH presents excellent durability (over 72 h at 100 mA/cm2) in 1 M KOH electrolyte and alkaline seawater. The enhanced catalytic performance and durability can ascribe to the enlarged interlayer spacing by CNA intercalation and shielding effect of CNA against chlorine corrosion. This research offers a novel approach to the design of efficient electrocatalysts for hydrogen production from seawater electrolysis.

The vacuum-assisted resin infusion mold (VARIM) process is widely used in wind blade manufacturing for its cost-effectiveness and reliability. However, the current method faces challenges such as long curing times and defects due to nonuniform heating across the blade structure. To address this, a multi-zone heated bed setup tailored to blade thickness has been considered. However, determining an optimal temperature for each zone poses a computational challenge, which can be tackled with a novel machine-learning approach. Using a digital twin based on a high-fidelity multiphysics solver, a time-distributed LSTM model was trained to understand complex resin curing dynamics. This eliminates the need for costly lab experiments, as the model learns heating patterns and curing behavior efficiently. Once trained, the ML model acts as a digital twin by predicting the degree of cure for a given temperature setpoint with 96.73% accuracy. This model, when used as a surrogate for a Nelder-mead optimization workflow, improves the curing time by roughly 12.5% and presents a more uniform curing rate throughout the part.

The current research aims to predict the residual stress accumulation and evolution in the powder bed fusion processed multi-layer thin wall structures through a conforming mesh modeling approach. It involves the discrete element method (DEM) interfaced with the volume of fluid (VOF) method using computational fluid dynamics (CFD) coupled with the finite element method (FEM). The conforming mesh approach developed in the research predicts multi-physics, its induced porosity, and the cumulative effect on the residual stress in the powder bed fusion processed Ti-6Al-4V thin wall structures. The results of the residual stress in the multi-layered component from this method were further quantitatively compared with the non-conforming finite element method. The results show the conforming mesh approach was not only effective in capturing the layer geometry, and defects induced during the printing, but also predicted the residual stress in the region of the defect more accurately than the non-conforming mesh methods.