Meng An

Hygroscopic materials that capture water vapor across a wide humidity range are important for emerging applications including atmospheric water harvesting, moisture control, and thermal management. Hydrogel sorbents are attractive because they can store large amounts of water while remaining solid-like, yet common hydrophilic gels sorb little vapor at low relative humidity (RH) unless hygroscopicity is introduced by deliquescent salts. Here, we report intrinsically hygroscopic hydrogels (IHHs) assembled from inosine and Zn²⁺ through pH-controlled supramolecular coordination. The IHHs show a moisture-sorption onset near zero RH, reaching 0.17 g g^-1 at 30% RH while retaining swelling-amplified uptake at high RH (1.9 g g^-1 at 95% RH) and reversible cycling. Varying gelation pH reprograms the coordination microenvironment and network structure, reshaping early-stage sorption and shifting uptake onset. Experiments and simulations indicate that hydration-accessible Zn-centered motifs serve as important early hydration loci, while pH-dependent network structure further modulates hydration growth. These results provide a coordination-chemistry route to hygroscopic hydrogels without salt deliquescence.

Aligned vertical mass transfer channels have been constructed in a 2D monolayered Fe–N–C carbon honeycomb, significantly enhancing the accessibility of Fe–N ₄ active sites and overall mass transfer efficiency for ORR.

Two-dimensional (2D) β-bismuthene has emerged as a promising thermoelectric material owing to its distinctive electronic and thermal properties. Engineering phonon transport through structural parameters such as layer numbers and twist angle provide a powerful strategy for tailoring the thermal behavior of 2D layered materials. In this work, we systematically investigate its thermal transport behavior using molecular dynamics simulations, focusing on the effects of layer number and twist angle. The lattice thermal conductivity increases with layer number from monolayer to five layers but gradually saturates, exhibiting an anomalous layer-dependent trend. In twisted bilayer β-bismuthene, a pronounced 79.2% reduction in in-plane thermal conductivity is observed at a twist angle of θ = 30° compared to θ = 0°, accompanied by a 62.4% decrease in interfacial thermal conductance. Detailed analyses of phonon transmission, density of states, participation ratio, and interfacial potential energy reveal that these reductions arise from suppressed low-frequency phonon transport and weakened interlayer coupling. This work demonstrates that twist angle engineering provides an effective strategy for tuning both in-plane and interfacial thermal transport, offering valuable guidance for designing 2D materials with tailored thermoelectric performance.

Erratum: Data-Driven Prediction of Thermal Conductivity from Short MD Trajectories: A GCN-LSTM Approach [Chin. Phys. Lett. 43 020801 (2026)], Feng, Shihao, Chen, Haifeng, Zhang, Jian, An, Meng, Zhang, Gang Erratum: Data-Driven Prediction of Thermal Conductivity from Short MD Trajectories: A GCN-LSTM Approach [Chin. Phys. Lett. 43 020801 (2026)], Feng, Shihao, Chen, Haifeng, Zhang, Jian, An, Meng, Zhang, Gang

Solar‐driven adsorption–desorption‐based atmospheric water harvesting (AD‐AWH) presents a promising strategy for sustainable freshwater production. However, conventional hygroscopic materials typically feature disordered internal architectures, severely hindering vapor diffusion and heat transfer. These structural limitations constrain adsorption kinetics and elevate the energy demand for desorption. Here, we report a biomass‐based hygroscopic aerogel (BHA) with vertically aligned microfluidic channels, fabricated via directional freeze‐drying. This anisotropic architecture enables directed vertical moisture transport combined with radial diffusion into secondary pores, effectively reducing vapor transport tortuosity while simultaneously increasing water‐binding capacity. As a result, the BHA achieves a high‐water uptake of 3.18 g g ⁻¹ at 80% RH and a rapid adsorption rate of 0.25 g g ⁻¹ within 6 h at 30% RH. Upon surface modification with a photothermal ink, the evaporation rate increases to 2.89 kg m ⁻² h ⁻¹ , and the desorption ratio reaches 76.63% under one sun irradiation. Outdoor field tests confirm a high daily water yield of 1.51 L m ⁻² day ⁻¹ . Furthermore, the incorporation of montmorillonite significantly reinforces the mechanical robustness of the aerogel. This work presents a structurally engineered strategy for optimizing internal fluidic and thermal dynamics in hygroscopic materials, offering a scalable and energy‐efficient pathway for AD‐AWH in water‐stressed regions.

Sorption‐based Atmospheric Water Harvesting (AWH) is an innovative approach to mitigate global freshwater scarcity. However, there is a trade‐off between rapid kinetics and ultrahigh water uptake, which is a formidable challenge in designing sorbent materials. Herein, 4D printed dual‐functional hydrogel is constructed through the collaborative design of molecular‐scale dynamic response network and macro‐scale structure. The 4D dual‐functional hydrogel integrates thermoresponsive (PNIPAM) and zwitterionic (PDMPAS) to form dynamic response networks, and is loaded with polypyrrole (PPY) and lithium chloride (4D TZG‐PPY‐LiCl). Simultaneously, 4D TZG‐PPY‐LiCl utilizes an abundant air‐sorbent interface to accelerate moisture absorption kinetics, exhibiting a large swelling ratio under humidity stimulation to capture more water. The moisture absorption rate and water uptake of 4D TZG‐PPY‐LiCl are double those of bulk TZG‐PPY‐LiCl between 30% and 90% RH, exhibiting an ultrahigh water uptake of 1.62–6.85 g g ⁻¹ , which is superior to that of the state‐of‐the‐art sorbents. In addition, the excellent photothermal conversion of 4D TZG‐PPY‐LiCl induces a hydrophilic to hydrophobic transition and structural shrinkage under one‐sun illumination, facilitating rapid water release. Furthermore, 4D TZG‐PPY‐LiCl AWH device has been further constructed, enabling continuous freshwater production. This breakthrough provides a new idea for the development of sorbent materials.

We propose a data-driven framework for rapid prediction of thermal conductivity in solids based on short-time molecular dynamics (MD) simulations. By converting atomic configurations into graph representations, a graph convolutional networks (GCNs) is used to extract spatial features, which are then processed by a long short-term memory (LSTM) network to capture the temporal evolution of physical properties. The framework is validated using equilibrium MD simulations of germanium at 1000 K across various system sizes. With size-specific normalization and optimized hyperparameters, the model accurately predicts the converged thermal conductivity, achieving results consistent with experimental data. Notably, the proposed method significantly reduces computational time by up to 800-fold at large system sizes, which demonstrates its potential to accelerate thermal transport simulations in solid-state systems.