Zheng-Hong Huang

Predicting the ammonium nitrogen (NH4+-N) adsorption capacity of biochar is challenged by coupled, nonlinear interactions among operational variables, pyrolysis synthesis parameters, and intrinsic material properties. A unified data set comprising 425 literature-reported adsorption records from 18 studies was compiled, and preprocessing (KNN imputation and Z-score standardization) was fitted exclusively on the training subset to prevent data leakage. Among seven machine learning algorithms benchmarked with Bayesian optimization and 5-fold cross-validation, XGBoost achieved the highest test-set coefficient of determination (R2) of 0.901 and root-mean-square error of 0.555 mg g–1. TreeSHAP analysis quantitatively decoupled three driver groups, adsorption operational parameters (53.3%), biochar physicochemical properties (38.2%), and pyrolysis synthesis parameters (8.5%), and identified initial concentration, biochar oxygen content, and adsorbent dosage as the dominant variables, with oxygen content exhibiting a unimodal relationship with adsorption capacity. Partial dependence plots were further utilized to reveal nonlinear response behaviors and determine data-coverage-validated optimal operation and design windows for key variables. A graphical user interface was developed to estimate equilibrium adsorption capacity, reducing reliance on extensive laboratory trials.

Recognizing the gap between traditional verification-oriented undergraduate chemistry experiments and real-world nanomaterial research practice, we designed a comprehensive laboratory experiment integrating nanomaterial synthesis, characterization, and electrochemical sensing for third-year and senior undergraduate students majoring in analytical chemistry, environmental engineering, or materials science. This experiment focuses on addressing the limitations of enzyme-based glucose sensors (e.g., strict environmental dependence, poor stability) by constructing an enzyme-free glucose sensor using copper oxide/porous nitrogen-doped graphene (CuO/PNrGO) nanocomposites. Students sequentially synthesize porous nitrogen-doped graphene (PNrGO) via calcination, prepare CuO/PNrGO through a hydrothermal method, and fabricate the enzyme-free sensor. They characterize the nanomaterials using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and N2 adsorption–desorption while evaluating the performance of the sensor via cyclic voltammetry (CV) and amperometric i–t curves. The optimized CuO/PNrGO sensor exhibits a high sensitivity of 2020.54 μA·mM–1·cm–2, a low detection limit of 0.13 μM, excellent anti-interference ability, and long-term stability. This experiment bridges foundational chemistry principles (electrochemistry and materials science) with interdisciplinary research, enhancing students’ experimental skills, data analysis capabilities, and scientific literacy.

The porous structure and surface chemistry of graphene aerogels (GAs), critical to their energy storage performance in aqueous supercapacitors, can be effectively modulated by postoxidation washing treatments. In this study, three graphene aerogel samples, namely water-washed graphene aerogel (GA-W), acid–water cowashed graphene aerogel (GA-A/W), and acid-washed graphene aerogel (GA-A), were prepared through hydrothermal assembly of graphene oxide with different washing protocols. Experimental characterizations and density functional theory calculations confirm that residual protons trigger the transformation of carbonyl groups to hydroxyl moieties, accompanied by lattice distortion and pore collapse. Electrochemical measurements show that GA-W with a microporous structure and intact sp2 network achieves a specific capacitance of 319 F g–1 at 1 A g–1 in 6 M KOH electrolyte via dominant electric double-layer capacitance. Benefiting from high mesopore fraction (86.7%) and moderate carbonyl retention, GA-A/W delivers a capacitance of 248 F g–1 at 1 A g–1 in 0.5 M (NH4)2SO4 electrolyte, owing to matched ion transport channels and enhanced proton-coupled electron transfer (PCET) pseudocapacitance. This work elucidates the proton-induced structural degradation mechanism of GAs and proves that washing engineering is a facile and scalable approach to develop electrolyte-adaptive carbon electrodes for aqueous supercapacitors.

Sodium-ion batteries are attractive for large-scale energy storage, but the limited capacity of hard-carbon anodes constrains practical energy density. Increasing porosity can boost capacity, but typically enlarges the electrolyte-accessible surface, lowers the initial Coulombic efficiency (ICE) and the low-voltage plateau capacity, especially in low-cost, coal-derived carbons that require aggressive activation. Here, we develop a selective pore-mouth sealing strategy that exploits the strong affinity between oxygen-rich edge sites at pore mouths and a polyacrylonitrile (PAN) precursor to build a high density of closed pores while preserving the internal pore network. PAN preferentially accumulates at pore entrances and undergoes in situ cyclization–carbonization during heat treatment, enabling directional pore-mouth contraction and sealing (pore mouth < 0.35 nm). By tuning the PAN content, the volume and fraction of closed pores are precisely controlled, limiting electrolyte penetration and substantially enhancing low-voltage plateau Na storage. The optimized electrode delivers 338.4 mAh g–1 at 0.05 A g–1 with a plateau capacity of 233 mAh g–1 and an ICE increased by ∼42% compared with activated coal-based hard carbon, outperforming most reported coal-derived hard carbons. Even at 5 A g–1, it retains 102.4 mAh g–1. This pore-mouth engineering offers a practical route to coal-derived hard-carbon anodes with controlled closed-porosity for sodium-ion batteries.

As one of the important candidate systems in the “post-lithium-ion batteries” era, lithium-sulfur (Li-S) batteries have developed rapidly in recent decades. However, the practical energy density achievable for Li-S batteries still has a certain gap to meet the demands of practical applications, which is mainly attributed to excessive electrolyte usage. In this paper, this key issue has been effectively alleviated through a two-pronged approach that combines electrocatalysis and electrode structure design. On the one hand, VC0.75 was in situ grown on the surface of graphene (VC0.75/G), forming a heterostructure catalyst between the two. This catalyst can strongly anchor the dissolved long-chain Li2Sn molecules and catalyze the rate-limiting step of the sulfur redox reaction, namely the deposition/decomposition of Li2S. On the other hand, the microlattice electrode fabricated via 3D printing features a dual-scale pore structure, consisting of through-hole channels perpendicular to the electrode plane and abundant micro-nano pores inside the printed filaments. This well-designed architecture significantly facilitates electrolyte infiltration and mass transport within the thick electrode. Consequently, this VC0.75/G microlattice cell can achieve discharge capacities of 882.8 mAh g–1 at 0.05 C and 1206.4 mAh g–1 at 0.02 C under the conditions of an ultra-high sulfur areal loading of ∼31 mg cm–2 and a lean electrolyte of 5 μL mg−1, corresponding to remarkable areal capacities of 27.8 and 37.4 mAh cm–2. This integrated approach highlights the synergistic role of architectural engineering and catalytic activation in addressing the key challenges of sluggish reaction kinetics and low sulfur utilization rate for high sulfur loading and lean electrolyte Li-S batteries.

Physical adsorption is a green separation technology with industrial potential. Precise control of the pore structure of adsorbent is key to achieving highly selective separation of target molecules of similar size. In this study, a combined molecular simulation and experimental approach was employed to investigate the influence of pore size on the adsorption behavior of benzene, toluene and o-xylene over silica-based adsorbents. The simulation results show that methyl groups enhance the interfacial interactions between adsorbate molecules and pore walls, whereas steric hindrance limits the packing efficiency of the adsorbates within the pores. Consequently, adsorption selectivity is governed by the balance between confinement-enhanced adsorbate–adsorbent interactions and steric accessibility, with a pore size of approximately 0.7 nm providing the most favorable adsorption environment for toluene. The experimental results are consistent with the simulation results. When benzene and toluene are co-adsorbed, the NaY adsorbent with an average pore size of 0.7 nm exhibits the highest adsorption capacity and selectivity for toluene.

The development of non-enzymatic glucose sensors for beverage analysis remains challenging due to insufficient active sites, poor conductivity, and limited stability in complex matrices. A nickel-carbon nanotube composite (Ni/CNT−600) was synthesized via in situ solvothermal deposition followed by pyrolysis at 600 °C under an inert atmosphere. The optimized Ni/CNT−600 featured uniform anchoring of Ni nanoparticles on CNTs through strong Ni–C and Ni–O–C interfacial bonds, validated by various characteristic techniques. The Ni/CNT−600 sensor exhibited exceptional sensitivity (538.48 μA mM⁻¹ cm⁻²) and an ultralow detection limit (0.003 μM) in 0.1 M NaOH at +0.65 V, surpassing many reported metal-based and enzymatic sensors. It demonstrated remarkable selectivity against key interferents (e.g., ascorbic acid, uric acid). In real beverage samples (orange juice, grape juice, cola, green tea, milk), recovery rates ranged from 95.6% to 112.8%. This work demonstrates a well-defined Ni-CNT synergistic interface that contributes to enhanced non-enzymatic glucose sensing performance, effectively addressing matrix complexity in beverages.

Natural flake graphite is widely used as anode material of commercial lithium‐ion batteries. In contrast, natural microcrystalline graphite (MG) has not been in practical application. This work systematically investigates the structure‐property relationship between the intrinsic structure of MG and its electrochemical performance. The results indicate that that both morphology and particle size significantly affect its electrochemical performance. The small‐particle‐sized and spheroidized MG can provide abundant pathways for the rapid transport of Li ⁺ , contributing to a higher rate capability because MG with a short‐range ordered and long‐range disordered structure is more conducive to the rapid migration of Li ⁺ .

The development of smart coatings with active protection is a promising approach to prolonging the service life in extreme environments. Herein, the corrosion inhibitors 2-mercaptobenzimidazole (MBI) and CeO₂ were in situ loaded onto the surface of graphene oxide (GO) by dopamine (DA) polymerization, and we ultimately obtained the multifunctional composite MBI@CeO₂@PDA@GO (MCPG). The electrochemical impedance spectroscopy (EIS) results revealed that after 30 days of immersion in the corrosive media, the |Z|_0.01 Hz value of MCPG/WEP coating remained at 3.7 × 10⁹ Ω/cm², which displayed four orders of magnitude higher than that of pure WEP coating (1.4 × 10⁵ Ω/cm²). In a 200 h salt spray test, the MCPG/WEP coating also demonstrated minimal corrosion products and bubbles, affirming the exceptional corrosion-inhibiting effect and excellent self-healing performance. Consequently, the synergistic combination of pH-sensitive properties and outstanding barrier effect imparted dual active/passive anti-corrosion capabilities to the coating, resulting in long-lasting metal protection.