International Journal of Hydrogen Energy最新文献

Development and optimization of a novel multi-generation energy system powered by woody biomass: A multi-objective approach using NSGA-II 以木质生物质为动力的新型多代能源系统的开发与优化：基于NSGA-II的多目标方法

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.ijhydene.2026.153821

Songcen Wang , Jingshuai Pang , Hongyin Chen , Xinhe Zhang , Jianfeng Li , Fengkai Gao

In this work, a biomass-based multigeneration energy system that simultaneously generates electricity, cooling, and hydrogen is developed and optimized. The suggested setup combines a proton exchange membrane for electrolysis, thermoelectric generators, an externally fired gas turbine, and a downdraft gasifier. Both experimental and published data are used to validate a steady-state model, and thorough parametric, sensitivity, and multi-objective optimization analyses are carried out. The air-side compression ratio and gas turbine inlet temperature have the largest effects on system behavior, according to the one- and two-variable studies. The net power output increases by 62% and the energy efficiency increases from 23.26% to 33.94% when the gas turbine's inlet temperature is raised from 1100 K to 1450 K. By achieving a balanced design, the NSGA-II and TOPSIS optimization framework reduces the levelized cost to 0.0973 $/kWh, shortens the payback period to 4.788 years, and increases energy efficiency to 37.04%. Additionally, the optimized configuration increases total profit to 95.16 M$ and reduces carbon emissions by 11.5%. According to exergy analysis, the primary sources of irreversibility are the combustion chamber and gasifier.

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引用次数: 0

Simulation of the refuelling process for an LH2-Powered commercial Aircraft: Part 2 - Refuelling time of the Airbus ZEROe turboprop concept lh2动力商用飞机加油过程的模拟：第2部分-空中客车ZEROe涡桨概念机的加油时间

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.ijhydene.2026.153582

L. ten Damme , M. van Put , A. Gangoli Rao

Liquid hydrogen (LH₂) is gaining momentum as a sustainable aviation fuel, but its cryogenic nature poses significant challenges for ground operations, particularly aircraft refuelling. This process is increasingly recognised as a potential bottleneck for operational efficiency, as it can significantly extend turnaround times. Although some recent studies have proposed assumptions about LH₂ refuelling rates, their conclusions vary widely, and detailed modelling efforts remain limited.

This paper presents the second part of a two-part study that aims to improve understanding of the LH₂ refuelling by delivering a validated numerical modelling framework and practical insights to support the design of future LH₂-powered aircraft and their airport refuelling operations. Part 1 focused on developing and validating a thermodynamic model that captures key physical phenomena such as heat transfer and droplet dynamics. The model was validated against experimental data from the LH₂ no-vent filling tests to demonstrate its accuracy in predicting relevant physical processes.

In Part 2, the validated model is applied to a representative case study based on the Airbus ZEROe Turboprop concept. The objective is to quantify the refuelling time and hydrogen venting under realistic conditions. The simulation results indicate a refuelling time of approximately 19, min and ventilation losses of 36.7, kg, corresponding to approximately 2. 2 % of the total transferred LH₂ mass.

Although the duration of refuelling exceeds that of current kerosene-powered aircraft such as the Bombardier Q400, the overall turnaround time remains feasible if the LH₂ refuelling process is carried out in parallel with other ground operations, subject to safety protocols. These findings challenge simplified assumptions in the previous literature and provide physics-based insight to support the design of safe and efficient LH₂ fuelling procedures and infrastructure for future zero-emission aviation.

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引用次数: 0

Photoreforming with Cu/TiO2 and Ni/TiO2 photocatalysts: production of hydrogen and revalorization of biomass substrates Cu/TiO2和Ni/TiO2光催化剂的光重整：氢的产生和生物质底物的再增值

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.ijhydene.2026.153568

Meryem Bouchabou, Stephanie Araceli Brocani-Pasino, Sergio Belda-Marco, M. Carmen Román-Martínez, M. Angeles Lillo-Rodenas

To produce hydrogen and revalorize lignocellulosic residues, Cu/TiO₂ and Ni/TiO₂ photocatalysts (metal loading 1 or 5 wt%), as-prepared and after thermal reduction treatment, were tested for the photoreforming of cellulose and almond shell derived-substrates. Net photoreforming contributions were quantified by subtracting the individual contributions of photodegradation and photocatalyzed water splitting. Only milled cellulose (MC) and the liquid from the hydrothermal carbonization of milled almond shell (HMAS-L2) substrates proved effective for photoreforming, yielding significantly higher hydrogen productions than those obtained from substrates photodegradation and water splitting. As-prepared Cu/TiO₂ showed efficient photocatalytic activity due to the facile in-situ reduction of Cu species. Conversely, Ni/TiO₂ photocatalysts became active only after the reduction treatment, when partial formation of Ni⁰ species enhanced charge separation. The presence of reduced metals significantly improved photoactivity by decreasing charge recombination. The highest hydrogen productions reached were 2320 μmol·g_cat⁻¹· h⁻¹ and 2440 μmol·g_cat⁻¹·h⁻¹ with MC_5Ni-P25-r and HMAS-L2_5Cu/P25-r, respectively, surpassing previously reported literature values. The H₂/CO₂ molar ratios, with values close to the theoretical stoichiometric ratio (≈2), confirmed the predominant photoreforming pathway, while deviations indicated concurrent photodegradation and/or photoinduced water splitting. Tests with scavengers confirmed the effective photoreforming with MC and HMAS-L2 substrates, in contrast to milled almond shell and its derived solids.

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引用次数: 0

Potential and trade-offs of native versus sludge-derived microbiota in dark fermentation of agro-industrial effluents 农业工业废水暗发酵中原生微生物群与污泥衍生微生物群的潜力和权衡

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-05 DOI: 10.1016/j.ijhydene.2026.153820

José de Jesús Montoya-Rosales , Ana Chango-Cañola , Paola Janet Delgado-Espitia , Elías Razo-Flores , Julián Carrillo-Reyes

Dark fermentation offers a scalable route to low-carbon hydrogen, yet performance depends on inoculum origin and feedstock. This study contrasts native microbiota with pretreated granular sludge for hydrogen and metabolite production from agro-industrial residues, agave bagasse enzymatic hydrolysates (EH1, EH2), cheese whey (CW), and winery wastewater (WW). Sludge inoculum consistently enhanced H₂, reaching 842 mL H₂/L in EH1. Native microbiota, while producing lower H₂ (e.g., 536 mL H₂/L in EH1), showed metabolic flexibility: rapid carbohydrate/lactate use, activation of formate hydrogenase, and frequent electron diversion to propionate/lactate. Community profiling showed sludge-derived consortia converged to specialized structures, whereas native microbiota remained substrate-specific and diverse. Despite taxonomic divergence, functional predictions indicated redundant core hydrogenogenic pathways and complementary strengths: sludge maximized H₂ efficiency, while native microbiota minimized inputs by avoiding inoculum supply/pretreatment. These trade-offs support selective pretreatment, co-inoculation, or target microbial management to optimize dark fermentation in integrated biorefineries.

暗发酵提供了一条可扩展的低碳氢路线，但性能取决于接种源和原料。本研究对比了原生微生物群与预处理颗粒污泥中的氢和农业工业残留物的代谢物生产，龙舌兰甘蔗渣酶解物（EH1, EH2），奶酪乳清（CW）和酿酒厂废水（WW）。污泥接种持续增强H2，在EH1达到842 mL H2/L。原生微生物群虽然产生较低的H2（例如，在EH1中产生536 mL H2/L），但却表现出代谢灵活性：快速使用碳水化合物/乳酸，激活甲酸氢化酶，并频繁地将电子转移到丙酸/乳酸。群落分析显示，污泥衍生的菌群趋同为专门的结构，而原生微生物群仍然具有底物特异性和多样性。尽管分类上存在差异，但功能预测表明了冗余的核心产氢途径和互补优势：污泥最大化H2效率，而原生微生物群通过避免接种供应/预处理来最小化投入。这些权衡支持选择性预处理、共接种或目标微生物管理，以优化综合生物精炼厂的暗发酵。

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引用次数: 0

Physics-guided transfer learning for robust biomass gasification modeling under data scarcity 数据稀缺下稳健生物质气化建模的物理引导迁移学习

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-05 DOI: 10.1016/j.ijhydene.2026.153826

Shaojun Ren, Yijia Zhang, Qihang Weng, Shiliang Wu, Cong Fu, Qingding Zhu, Baoyu Zhu, Fengqi Si

Accurate prediction of product distributions from biomass gasification is crucial for effective regulation of biomass gasifiers. Machine learning methods offer high fitting accuracy and fast response speed, but often struggle with low interpretability and poor generalization when sample sizes are limited. Therefore, this paper proposes a physics-informed composite artificial neural network (PI-CANN) approach for robust biomass gasification modeling under data scarcity. First, a thermodynamic equilibrium model for biomass gasification is developed to generate simulation data using the Monte Carlo method. An artificial neural network (ANN) is then trained on sufficient low-fidelity simulation data, serving as the pre-trained model for PI-CANN. This PI-CANN framework connects the pre-trained ANN with both linear and nonlinear calibration networks. Throughout the PI-CANN training process, the pretrained ANN remains fixed, and calibration networks are trained using limited experimental data under the guidance of boundary conditions and physically monotonic relationships. As a result, the PI-CANN model achieves high-fidelity alignment with experimental data while adhering to fundamental physical principles. Furthermore, the PI-CANN method was used to develop a predictive model for pine sawdust biomass. The results demonstrated that this model can accurately predict five test samples using only four training samples, achieving an R² of 0.98 and a root mean square error of 0.38%. This proposed method demonstrates better generalization and interpretability than state-of-the-art techniques.

准确预测生物质气化产物分布对有效调节生物质气化炉至关重要。机器学习方法具有较高的拟合精度和快速的响应速度，但在样本量有限的情况下，往往存在可解释性低和泛化能力差的问题。因此，本文提出了一种基于物理信息的复合人工神经网络（PI-CANN）方法，用于数据稀缺条件下的鲁棒生物质气化建模。首先，建立了生物质气化热力学平衡模型，利用蒙特卡罗方法生成模拟数据。然后在足够的低保真仿真数据上训练人工神经网络（ANN），作为PI-CANN的预训练模型。该PI-CANN框架将预训练的人工神经网络与线性和非线性校准网络连接起来。在整个PI-CANN训练过程中，预训练的ANN保持固定，在边界条件和物理单调关系的指导下，使用有限的实验数据训练校准网络。因此，PI-CANN模型在坚持基本物理原理的同时，实现了与实验数据的高保真对齐。在此基础上，利用PI-CANN方法建立了松木木屑生物量预测模型。结果表明，该模型仅使用4个训练样本即可准确预测5个测试样本，R2为0.98，均方根误差为0.38%。该方法比先进的技术具有更好的通用性和可解释性。

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引用次数: 0

Integration of PRO/II simulation and XGBoost machine learning for predicting and optimizing hydrogen-rich syngas from air-blown biomass–plastic co-gasification PRO/II模拟和XGBoost机器学习的集成，用于预测和优化空气吹生物质-塑料共气化富氢合成气

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-05 DOI: 10.1016/j.ijhydene.2026.153747

Victor Hugo Xavier Bernardes , Rubens Gedraite , Nicolas Spogis , Sarah Arvelos Altino

Co-gasification of biomass and plastic waste enables low-carbon syngas and hydrogen generation, yet its optimization remains limited by the nonlinear interplay among temperature, equivalence ratio, and feed composition. This study integrates a physico-chemical process simulation framework—implemented in AVEVA PRO/II with sequential modules for drying, pyrolysis, gasification, and restricted chemical equilibrium—with a gradient-boosted machine-learning model (XGBoost) to predict syngas composition and performance indicators directly from operating conditions. Validation against independent experiments confirmed that the PRO/II framework reproduces the correct order of magnitude for H₂, CO, CO₂, and CH₄ yields, supporting the generation of 3000 Latin-Hypercube simulations for model training. The regressors achieved out-of-sample R² > 0.98 for all targets.

SHAP analysis revealed that temperature and oxygen-to-fuel ratio govern hydrogen formation, whereas carbon and fixed-carbon contents control CO generation. Differential-evolution optimization identified plastic-rich blends of polypropylene with lignocellulosic residues as optimal for hydrogen-rich syngas (H₂ = 28%, H₂/CO ~ 1.1, LHV≈6.5MJ/Nm³. This modular simulation–learning–optimization architecture bridges mechanistic process modelling and data-driven prediction, offering a reproducible pathway to accelerate the design of hydrogen-oriented co-gasification systems.

生物质和塑料废弃物共气化可以实现低碳合成气和制氢，但其优化仍然受到温度、等效比和饲料成分非线性相互作用的限制。该研究将物理化学过程模拟框架（在AVEVA PRO/II中实现，具有干燥、热解、气化和受限化学平衡的顺序模块）与梯度增强机器学习模型（XGBoost）集成在一起，直接从操作条件预测合成气成分和性能指标。对独立实验的验证证实，PRO/II框架再现了H2、CO、CO2和CH4产率的正确数量级，支持生成3000个Latin-Hypercube模拟用于模型训练。所有目标的回归量均达到样本外R2 >； 0.98。SHAP分析表明，温度和氧燃料比控制氢的形成，而碳和固定碳含量控制CO的产生。差异演化优化结果表明，聚丙烯与木质纤维素残基的富塑共混物（H2 = 28%, H2/CO ~ 1.1, LHV≈6.5MJ/Nm3）是制备富氢合成气的最佳原料。这种模块化的模拟-学习-优化架构连接了机械过程建模和数据驱动预测，为加速氢导向共气化系统的设计提供了可重复的途径。

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引用次数: 0

Dual-active CuCo2S4@Ni(OH)2 heterojunctions for sustainable hydrogen production via alkaline and seawater electrolysis 双活性CuCo2S4@Ni(OH)2异质结通过碱性和海水电解可持续制氢

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-05 DOI: 10.1016/j.ijhydene.2026.153861

T.R. Naveen Kumar , P. Nitesh , C. Sengottaiyan , Daniel Arulraj Abraham , Arun Thirumurugan , Manikandan Kandasamy , T. Kavinkumar

The development of cost-effective, durable bifunctional catalysts is pivotal for scalable green hydrogen production. Herein, a CuCo₂S₄@Ni(OH)₂ heterostructure was fabricated via a hydrothermal method, delivering remarkable catalytic activity towards hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in both alkaline and seawater media. The strong electronic coupling at the CuCo₂S₄@Ni(OH)₂ interface enhances charge transfer and optimizes intermediate adsorption, enabling efficient water splitting. Benefiting from these features, the CuCo₂S₄@Ni(OH)₂ achieves overpotentials of 134.3 mV and 187.6 mV at 10 mA cm⁻² for HER and OER, respectively. A CuCo₂S₄@Ni(OH)₂ electrolyzer delivers a cell voltage of 1.52 V at 10 mA cm⁻² in KOH and excellent seawater activity with low overpotentials (124.1 mV for HER, 186.4 mV for OER) and minimal degradation. Density functional theory analysis reveals that charge migration from Ni(OH)₂ to CuCo₂S₄ enhances catalyst's conductivity. This study demonstrates sulfide-hydroxide heterostructures as efficient, stable catalysts for large-scale hydrogen generation.

开发具有成本效益、耐用的双功能催化剂对于规模化的绿色制氢至关重要。本文通过水热法制备了CuCo2S4@Ni(OH)2异质结构，该异质结构在碱性和海水介质中对析氢反应（HER）和析氧反应（OER）都具有显著的催化活性。CuCo2S4@Ni(OH)2界面的强电子耦合增强了电荷转移，优化了中间吸附，实现了高效的水分解。得益于这些特性，CuCo2S4@Ni(OH)2在10 mA cm−2下，HER和OER的过电位分别为134.3 mV和187.6 mV。CuCo2S4@Ni(OH)2电解槽在KOH中电压为1.52 V，电压为10 mA cm - 2，过电位低（HER为124.1 mV， OER为186.4 mV），降解最小，具有优异的海水活性。密度泛函理论分析表明，Ni(OH)2向CuCo2S4的电荷迁移增强了催化剂的导电性。本研究证明了氢氧化硫异质结构是一种高效、稳定的大规模制氢催化剂。

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引用次数: 0

From waste-to-energy to waste-to-hydrogen units: A new role of waste combustion plants 从废物发电到废物制氢：废物燃烧厂的新角色

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-04 DOI: 10.1016/j.ijhydene.2026.153807

Filomena Ardolino , Francesco Parrillo , Simone Malvezzi , Lorenzo Privitera , Beatrice Papa , Umberto Arena

The study focused on a new Waste-to-Hydrogen (WtH2) strategy, where a waste combustion plant (WCP), originally designed and operated as a Waste-to-Energy unit, provides “renewable” electricity to an electrolyser, to obtain “green hydrogen” utilised in a regional railway line. The investigation included three systems using alternative WCPs, differing for size, energy efficiency and input waste composition. A Life Cycle Assessment, with a “separate share” approach and “product&tranportation” perspective, compares trains powered by WtH2 systems, diesel or hydrogen from steam reforming, respectively. The WtH2 systems show savings ranging from 39 to 57 t_CO2,eq per tonne of produced H₂, and are in compliance with the EU decarbonisation targets. The WtH2 system including the co-generative large-scale plant has the best performance when all categories are evaluated as a single score (with improvements up to 180%). The main relevant contributions to the results come from the thermal energy recovery and biogenic waste avoided management.

这项研究的重点是一项新的废物制氢（WtH2）战略，其中一个废物燃烧厂（WCP）最初是作为废物制氢单元设计和运行的，为电解槽提供“可再生”电力，以获得区域铁路线使用的“绿色氢”。调查包括三个使用替代性wcp的系统，其大小、能源效率和投入废物组成不同。生命周期评估采用“单独分享”的方法和“产品运输”的观点，分别比较了由WtH2系统驱动的列车、柴油驱动的列车和由蒸汽重整产生的氢气驱动的列车。WtH2系统显示，每生产一吨H2可节省39至57吨二氧化碳当量，符合欧盟的脱碳目标。当所有类别以单一分数评估时，包括共产大型电厂在内的WtH2系统表现最佳（改进幅度高达180%）。结果的主要相关贡献来自热能回收和避免生物废物的管理。

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引用次数: 0

Synthesis of a new polystyrene-based anion exchange membrane for alkaline electrolyzer 碱性电解槽用新型聚苯乙烯基阴离子交换膜的合成

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-04 DOI: 10.1016/j.ijhydene.2026.153703

Leyla Basat , Murat Farsak , Gülfeza Kardaş

In this study, a PMMA-b-PS anion-exchange membrane with high thermal and chemical stability is obtained by mixing polymethyl methacrylate (PMMA) and polystyrene (PS) using the film-casting method. PS is synthesized by radical polymerization and subsequently chloromethylated. Chloromethylated polystyrene is quaternized by adding trimethylamine (TMA) to the PS ring. The structure of the synthesized polystyrene was characterized by FTIR and ¹H NMR spectroscopy. Thermal analysis of the polymers was carried out by TGA and DSC analysis, according to which the first thermal decomposition started at approximately 200 °C and the backbone dissociated at 450 °C indicating that the membranes maintained their thermal stability at high temperatures. The solution resistance, conductivity, and stability of the PMMA-b-PS membrane were measured by EIS in 1 M KOH, and a hydrogen volume of 30.8 mL was obtained after repeated electrolyzer measurements for an hour.

本研究以聚甲基丙烯酸甲酯（PMMA）和聚苯乙烯（PS）为原料，采用膜铸法制备了热稳定性和化学稳定性高的PMMA-b-PS阴离子交换膜。PS是通过自由基聚合合成的，随后进行氯甲基化。氯甲基化聚苯乙烯通过在PS环上加入三甲胺（TMA）进行季铵化。用FTIR和1H NMR对合成的聚苯乙烯进行了结构表征。通过热重分析和差热分析对聚合物进行了热分析，根据热分析，聚合物的第一次热分解开始于约200°C，主链在450°C时解离，表明膜在高温下保持热稳定性。在1 M KOH条件下，用EIS法测定PMMA-b-PS膜的耐溶液性、电导率和稳定性，经1小时的反复电解槽测得氢气体积为30.8 mL。

引用次数: 0

Efficient UV–vis light induced water splitting and CO2 photoreduction over CdS-decorated MgO nanofibers 高效紫外-可见光诱导的水分解和CO2光还原在cds修饰的MgO纳米纤维

IF 8.3 2区工程技术 Q1 CHEMISTRY, PHYSICAL

International Journal of Hydrogen Energy

Pub Date : 2026-02-04 DOI: 10.1016/j.ijhydene.2026.153829

Ming Huang, Li Xing, Xiaogang Zheng

Heterojunction fabrication is a promising route to enhance the separation and migration of e⁻/h⁺ pairs and to restrain the carrier recombination. To achieve the spatial separation of redox sites and the directional migration of interfacial charges, CdS-decorated MgO (CdS/MgO) nanofibers were prepared via the electrospinning and hydrothermal approaches. The orientated MgO nanofibers favored the fast transfer and migration of photo-induced charge carriers. In addition, the hydration effect of MgO is likely to form the abundant –OH groups on the surface of MgO, providing the sufficient Lewis-base sites for CO₂ conversion and H₂ evolution and a unique alkaline microenvironment for suppressing Cd²⁺ leaching. In contrast with pristine CdS and MgO nanofibers alone for ultraviolet–visible (UV–vis) light driven water splitting and CO₂ methanation, CdS/MgO exhibited the better photocatalytic activity. The optimal 4-CdS/MgO with a nominal CdS content of 8 wt% exhibited a H₂ evolution rate of 951.79 μmol g⁻¹ h⁻¹, CH₄ yield rate of 67.35 μmol g⁻¹ h⁻¹, and CO yield rate of 120.62 μmol g⁻¹ h⁻¹.

异质结的制备是增强e−/h+对的分离和迁移以及抑制载流子复合的一种很有前途的途径。为了实现氧化还原位点的空间分离和界面电荷的定向迁移，采用静电纺丝和水热法制备了CdS修饰的MgO纳米纤维。取向MgO纳米纤维有利于光诱导载流子的快速转移和迁移。此外，MgO的水化作用可能在MgO表面形成丰富的-OH基团，为CO2转化和H2演化提供了充足的lewis碱基位点，并为抑制Cd2+浸出提供了独特的碱性微环境。在紫外光-可见（UV-vis）光驱动下，CdS/MgO纳米纤维在水裂解和CO2甲烷化反应中表现出更好的光催化活性。当标称cd含量为8 wt%时，4-CdS/MgO的H2析出率为951.79 μmol g−1 h−1，CH4产率为67.35 μmol g−1 h−1，CO产率为120.62 μmol g−1 h−1。

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引用次数: 0