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学者姓名：王大彪
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氨部分预分解是改善氨的燃烧性能的有效手段,但对于氨预分解条件的影响仍缺乏系统的研究.该文针对基于氨预分解策略的氨扩散燃烧装置开展数值模拟研究,以分析氨预分解比例、当量比和氨分解余热对燃烧及污染物排放特性的影响.结果表明,随着氨预分解比例提高,火焰温度提高,火焰高温区更靠近喷嘴,NOx排放量下降;NO排放在NOx中占主导,并随着当量比的提高先增大后减小;N2O排放主要发生在低氨预分解比例、低当量比条件下,在氨预分解比例达到50％后基本消失;利用氨分解余热预热燃料有助于稳定燃烧,并在氨预分解比例不超过30％时,明显减少氨泄漏而未增加NOx排放.研究表明,提高氨预分解比例和当量比能有效改善氨燃烧及污染物排放特性,而在小比例氨预分解条件下应充分利用氨分解的余热.
Keyword ：
NOx排放 NOx排放 当量比 当量比 数值模拟 数值模拟 氨分解 氨分解 氨氢燃烧 氨氢燃烧
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| GB/T 7714 | 黄文仕 , 王智雄 , 林立 et al. 基于氨预分解的氨扩散燃烧模拟研究 [J]. | 中国电机工程学报 , 2025 , 45 (2) : 479-488,中插7 . |
| MLA | 黄文仕 et al. "基于氨预分解的氨扩散燃烧模拟研究" . | 中国电机工程学报 45 . 2 (2025) : 479-488,中插7 . |
| APA | 黄文仕 , 王智雄 , 林立 , 伍泽赟 , 王大彪 , 罗宇 et al. 基于氨预分解的氨扩散燃烧模拟研究 . | 中国电机工程学报 , 2025 , 45 (2) , 479-488,中插7 . |
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Ammonia is a carbon-free energy carrier with 17.6 wt% hydrogen content. The design of an efficient and compact ammonia decomposition reactor based on low-temperature catalysts is the key to realizing industrial hydrogen production from ammonia. In this work, a multiscale model was developed by bridging the particle-scale characteristics of catalysts and reactor performances, to fully comprehend the ammonia decomposition process. The effects of catalyst porosity and pore diameters on the reactor size, precious metal loading, and the profile of temperature and heat flux were systematically evaluated. An improved reactor design was further proposed by applying the segmented reactor packed with two-stage egg-shell-type low-temperature catalysts, which decreased the precious metal usage by 61.6% and the temperature drop by 42.9 K. This segmentation strategy balanced the reaction rate and heat flux, indicating a significant potential in highly efficient, economical, and reliable hydrogen production from ammonia.
Keyword ：
ammonia decomposition ammonia decomposition catalyst micro-structure catalyst micro-structure hydrogen production hydrogen production multiscale model multiscale model precious metal reduction precious metal reduction
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| GB/T 7714 | Zhang, Lixuan , Wu, Yifan , Huang, Wenshi et al. Multiscale modeling of a low-temperature NH3 decomposition reactor for precious metal reduction and temperature control [J]. | AICHE JOURNAL , 2025 , 71 (6) . |
| MLA | Zhang, Lixuan et al. "Multiscale modeling of a low-temperature NH3 decomposition reactor for precious metal reduction and temperature control" . | AICHE JOURNAL 71 . 6 (2025) . |
| APA | Zhang, Lixuan , Wu, Yifan , Huang, Wenshi , Lin, Li , Wang, Luqiang , Wu, Zeyun et al. Multiscale modeling of a low-temperature NH3 decomposition reactor for precious metal reduction and temperature control . | AICHE JOURNAL , 2025 , 71 (6) . |
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As a carbon-free hydrogen (H2) carrier with the advantage of liquefaction storage and transportation, ammonia (NH3) is regarded as a competitive clean energy carrier for H2 production and power generation. This work designs a novel NH3-fueled hybrid power generation system, which combines ammonia decomposition reactor (ADR), proton exchange membrane fuel cell (PEMFC) and micro gas turbine (MGT) together with thermochemical recuperation for ADR. A system-level thermodynamic model has been developed to evaluate system performance with different optimization strategies. The model calculation reveals that the NH3 decomposition temperature drop from 500 degrees C to 350 degrees C can increase the energy efficiency from 33.5 % to 43.2 %, and two improved integration strategies have therefore been proposed. Mixing a part of NH3 with the exhaust gas from PEMFC anode to fuel MGT can reduce the NH3 decomposition demand and makes better use of waste heat from MGT. Integrating ADR with MGT combustor can lower the exhaust gas temperature and the efficiency loss when using high temperature NH3 decomposition catalyst. Both strategies can improve the system energy efficiency, to about 40% and 44% when NH3 decomposition temperature is 500 degrees C and 350 degrees C, respectively, and demonstrate better flexibility in adapting to changes in NH3 decomposition temperature.
Keyword ：
Ammonia decomposition Ammonia decomposition Ammonia energy Ammonia energy Power generation system Power generation system Proton exchange membrane fuel cell Proton exchange membrane fuel cell Thermochemical recuperation Thermochemical recuperation
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| GB/T 7714 | Lin, Li , Sun, Mingwei , Wu, Yifan et al. High-efficiency ammonia-fueled hybrid power generation system combining ammonia decomposition, proton exchange membrane fuel cell and micro gas turbine: A thermodynamic model and performance optimization [J]. | ENERGY CONVERSION AND MANAGEMENT , 2025 , 325 . |
| MLA | Lin, Li et al. "High-efficiency ammonia-fueled hybrid power generation system combining ammonia decomposition, proton exchange membrane fuel cell and micro gas turbine: A thermodynamic model and performance optimization" . | ENERGY CONVERSION AND MANAGEMENT 325 (2025) . |
| APA | Lin, Li , Sun, Mingwei , Wu, Yifan , Huang, Wenshi , Wu, Zeyun , Wang, Dabiao et al. High-efficiency ammonia-fueled hybrid power generation system combining ammonia decomposition, proton exchange membrane fuel cell and micro gas turbine: A thermodynamic model and performance optimization . | ENERGY CONVERSION AND MANAGEMENT , 2025 , 325 . |
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Accurate and fast histological diagnosis of cancers is crucial for successful treatment. The deep learning-based approaches have assisted pathologists in efficient cancer diagnosis. The remodeled microenvironment and field cancerization may enable the cancer-specific features in the image of non-cancer regions surrounding cancer, which may provide additional information not available in the cancer region to improve cancer diagnosis. Here, we proposed a deep learning framework with fine-tuning target proportion towards cancer surrounding tissues in histological images for gastric cancer diagnosis. Through employing six deep learning-based models targeting region-of-interest (ROI) with different proportions of no-cancer and cancer regions, we uncovered the diagnostic value of non-cancer ROI, and the model performance for cancer diagnosis depended on the proportion. Then, we constructed a model based on MobileNetV2 with the optimized weights targeting non-cancer and cancer ROI to diagnose gastric cancer (DeepNCCNet). In the external validation, the optimized DeepNCCNet demonstrated excellent generalization abilities with an accuracy of 93.96%. In conclusion, we discovered a non-cancer ROI weight-dependent model performance, indicating the diagnostic value of non-cancer regions with potential remodeled microenvironment and field cancerization, which provides a promising image resource for cancer diagnosis. The DeepNCCNet could be readily applied to clinical diagnosis for gastric cancer, which is useful for some clinical settings such as the absence or minimum amount of tumor tissues in the insufficient biopsy.
Keyword ：
Cancer-adjacent tissues Cancer-adjacent tissues Cancer diagnosis Cancer diagnosis Deep learning Deep learning Field cancerization Field cancerization Histological image Histological image
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| GB/T 7714 | Li, Lanlan , Geng, Yi , Chen, Tao et al. Deep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images [J]. | JOURNAL OF TRANSLATIONAL MEDICINE , 2025 , 23 (1) . |
| MLA | Li, Lanlan et al. "Deep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images" . | JOURNAL OF TRANSLATIONAL MEDICINE 23 . 1 (2025) . |
| APA | Li, Lanlan , Geng, Yi , Chen, Tao , Lin, Kaixin , Xie, Chengjie , Qi, Jing et al. Deep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images . | JOURNAL OF TRANSLATIONAL MEDICINE , 2025 , 23 (1) . |
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为解决深度学习分割算法在病灶的细节分割上存在漏判且模型参数量较大不利于实际应用的问题,提出一种基于改进的CG-Net的深度轻量化分割神经网络.在编码块加入改进高效金字塔拆分注意力模块和深度可分离卷积,以学习丰富多尺度全局特征;采用残差思想将注意力模块与编码块结合,提出高效金字塔语境引导模块,帮助网络学习全局和局部特征信息.在中山大学附属第六医院提供的腹部MRI图像数据库的结直肠肿瘤病灶分割实验中,验证了改进模型算法在分割精度和模型轻量化方面的有效性.
Keyword ：
医学图像分割 医学图像分割 注意力机制 注意力机制 深度可分离卷积 深度可分离卷积 深度学习 深度学习 结直肠癌 结直肠癌 编码解码网络 编码解码网络 轻量级 轻量级
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| GB/T 7714 | 李兰兰 , 胡益煌 , 王大彪 et al. CG-Net改进的结直肠癌病灶分割算法 [J]. | 计算机工程与设计 , 2024 , 45 (1) : 299-306 . |
| MLA | 李兰兰 et al. "CG-Net改进的结直肠癌病灶分割算法" . | 计算机工程与设计 45 . 1 (2024) : 299-306 . |
| APA | 李兰兰 , 胡益煌 , 王大彪 , 徐斌 , 李娟 . CG-Net改进的结直肠癌病灶分割算法 . | 计算机工程与设计 , 2024 , 45 (1) , 299-306 . |
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To meet the simultaneous needs of high temperature disinfection and freezing in the field of food processing, a new concept of combined heating and cooling transcritical CO2 system integrated with dedicated mechanical subcooling utilizing hydrocarbon mixture is proposed. The system performance in terms of thermodynamics, economy and environment is studied and compared with the baseline combined heating and cooling transcritical CO2 system and four traditional combined heating and cooling solutions, considering the influence of temperature glide and the heat transfer deterioration. The new proposed system is further optimized by using the machine learning method of artificial neural network and non-dominated sorting genetic algorithm. Multi-objective optimization is conducted considering the objective function of energy efficiency, initial capital cost and life cycle carbon emissions of the new system, to obtain the optimum components and concentration ratio of the hydrocarbon mixture. The results indicate the thermodynamic performance and environmental benefits of subcooling subsystem with hydrocarbon mixture are better than those of the pure system. In contrast to that using pure R290 and R601, the coefficient of performance is enhanced by 8.20 % and 8.13 % and the life cycle carbon emission is reduced by 8.54 % and 9.31 %, respectively, when R290/R601 (50/50) is used. However, the initial capital cost is 9.25 % and 10.23 % higher than that of pure R290 and R601, respectively. Finally, the hydrocarbon mixture corresponding to the optimal design point is R1270/R601a (53/47), the corresponding discharge pressure is 12.86 MPa, and the subcooling degree is 37.50 degrees C. This study can provide a theoretical reference for the application of CO2 refrigeration and heat pump technology.
Keyword ：
Combined heating and cooling Combined heating and cooling Dedicated mechanical subcooling Dedicated mechanical subcooling Hydrocarbon mixture Hydrocarbon mixture Machine learning Machine learning Multi-objective optimization Multi-objective optimization Transcritical CO2 Transcritical CO2
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| GB/T 7714 | Dai, Baomin , Wang, Qilong , Liu, Shengchun et al. Multi-objective optimization analysis of combined heating and cooling transcritical CO2 system integrated with mechanical subcooling utilizing hydrocarbon mixture based on machine learning [J]. | ENERGY CONVERSION AND MANAGEMENT , 2024 , 301 . |
| MLA | Dai, Baomin et al. "Multi-objective optimization analysis of combined heating and cooling transcritical CO2 system integrated with mechanical subcooling utilizing hydrocarbon mixture based on machine learning" . | ENERGY CONVERSION AND MANAGEMENT 301 (2024) . |
| APA | Dai, Baomin , Wang, Qilong , Liu, Shengchun , Zhang, Jianing , Wang, Yabo , Kong, Ziang et al. Multi-objective optimization analysis of combined heating and cooling transcritical CO2 system integrated with mechanical subcooling utilizing hydrocarbon mixture based on machine learning . | ENERGY CONVERSION AND MANAGEMENT , 2024 , 301 . |
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Ammonia decomposition for onsite hydrogen production has been regarded as an important reaction which links to efficient hydrogen storage, transport and utilization. However, it still remains challenging to develop efficient catalysts with robust stability for ammonia decomposition. Herein, an integrated strategy was employed to synthesize Ru/SiO2@N-CS via wrapping a thin layer of N-doped carbon onto the SiO2 sphere, following the anchor of Ru nanoparticles (NPs) onto the support. The obtained Ru/SiO2@N-CS (Ru loading: 1 wt%) shows a promising performance for ammonia decomposition, reaching 94.5 % at 550 degrees C with a gas hourly space velocity (GHSV) of 30 000 mL gcat-1 h- 1. The combination of the SiO2 as the core prevents the degradation of N-doped carbon layers and then enhance the durability of the catalysts, remaining stable after 50 h at evaluated temperatures. Adequate characterizations were used to illustrate the effect of microchemical environment on ammonia decomposition activity of Ru/SiO2@N-CS catalyst under different calcination atmosphere and the correlation between structure and performance.
Keyword ：
Ammonia decomposition Ammonia decomposition N-doped carbon N-doped carbon Ruthenium Ruthenium Stability Stability
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| GB/T 7714 | Huang, Yunyun , Ren, Hongju , Fang, Huihuang et al. Ru nanoparticles embedded in Ru/SiO2@N-CS for boosting hydrogen production via ammonia decomposition with robust lifespan [J]. | APPLIED SURFACE SCIENCE , 2024 , 669 . |
| MLA | Huang, Yunyun et al. "Ru nanoparticles embedded in Ru/SiO2@N-CS for boosting hydrogen production via ammonia decomposition with robust lifespan" . | APPLIED SURFACE SCIENCE 669 (2024) . |
| APA | Huang, Yunyun , Ren, Hongju , Fang, Huihuang , Ouyang, Dong , Chen, Chongqi , Luo, Yu et al. Ru nanoparticles embedded in Ru/SiO2@N-CS for boosting hydrogen production via ammonia decomposition with robust lifespan . | APPLIED SURFACE SCIENCE , 2024 , 669 . |
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结肠镜检查依赖于操作人员且漏检率较高,所以需要一种实时的息肉分割算法,来辅助医生的息肉检测工作.因此论文提出短期密集连接注意网络(Short-Term Dense Concatenate Attention Network,STDCANet).网络编码端的核心层是短期密集连接注意模块,此模块整合了传统卷积、STDC、残差思想和NAM的优势,以较小的计算复杂度保留了可伸缩的感受野和多尺度信息,在解码端引入了PD解码器,摈弃了部分底层特征用于模型的加速,聚合了高层特征实现了较好的分割结果.STDCANet在CVC-ClinicDB数据集上与经典的医学图像分割网络进行性能和模型复杂度的对比,在这两方面均优于对比网络,有临床实时分割的潜力.
Keyword ：
医学图像处理 医学图像处理 注意力机制 注意力机制 深度学习 深度学习 结肠镜图像 结肠镜图像
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| GB/T 7714 | 李兰兰 , 张孝辉 , 王大彪 . 基于短期密集连接注意网络的结肠息肉分割方法 [J]. | 计算机与数字工程 , 2024 , 52 (8) : 2469-2472,2497 . |
| MLA | 李兰兰 et al. "基于短期密集连接注意网络的结肠息肉分割方法" . | 计算机与数字工程 52 . 8 (2024) : 2469-2472,2497 . |
| APA | 李兰兰 , 张孝辉 , 王大彪 . 基于短期密集连接注意网络的结肠息肉分割方法 . | 计算机与数字工程 , 2024 , 52 (8) , 2469-2472,2497 . |
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Long-term energy storage and carbon capture technologies are pivotal in managing renewable energy surpluses and achieving carbon neutrality. This paper proposes a Carnot battery system integrating calcium-looping thermochemical energy storage with a coal-fired power plant. The system utilizes excess electricity from the grid for energy input, facilitating long-term energy storage, achieving carbon capture, and reducing coal consumption in the power plant. An optimization framework is developed, incorporating component thermodynamic models and optimization algorithms, to maximize the coal savings in plants and energy efficiencies of the Carnot battery system. During the energy release process, the carbonator partially replaces the reheat load of the boiler, necessitating retrofitting of the boiler's heating surface to ensure normal operation. The base system demonstrates a CO2 2 capture capacity of 3.23 MJ/kg and a reduction in coal consumption by 7.07 %. The roundtrip efficiency and comprehensive efficiency of the base system are 36.93 % and 37.91 %, respectively. The relatively low energy efficiency is primarily due to the deactivation of circulating adsorbents and the limited efficiency of the subcritical coal-fired power plant. By incorporating an additional recarbonation step to mitigate adsorbent deactivation, the system's comprehensive efficiency is improved to 42.20 %. Further improvements in system efficiency can be achieved by using modified adsorbents with high cycling stability instead of natural limestone and by coupling the system with more efficient ultra-supercritical units instead of the investigated subcritical units. This study offers valuable insights into the development of long-term energy storage solutions and multifunctional Carnot battery technology.
Keyword ：
Calcium looping Calcium looping Carbon capture Carbon capture Carnot battery Carnot battery Coal-fired power plant Coal-fired power plant Thermochemical energy storage Thermochemical energy storage
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| GB/T 7714 | Wang, Dabiao , Sun, Zihao , Xu, Qianghui et al. Thermodynamic modeling and analysis of a Carnot battery system integrating calcium looping thermochemical energy storage with coal-fired power plant [J]. | ENERGY CONVERSION AND MANAGEMENT , 2024 , 318 . |
| MLA | Wang, Dabiao et al. "Thermodynamic modeling and analysis of a Carnot battery system integrating calcium looping thermochemical energy storage with coal-fired power plant" . | ENERGY CONVERSION AND MANAGEMENT 318 (2024) . |
| APA | Wang, Dabiao , Sun, Zihao , Xu, Qianghui , Tian, Ran , Han, Wei , Shen, Jun . Thermodynamic modeling and analysis of a Carnot battery system integrating calcium looping thermochemical energy storage with coal-fired power plant . | ENERGY CONVERSION AND MANAGEMENT , 2024 , 318 . |
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For the scope of commercial supermarkets, the demand for energy efficiency improvement and environmentallyfriendly working fluid of the refrigeration system is necessary. In this study, supermarket booster refrigeration system by using eco-friendly working fluid CO 2 /halogenated alkene (HA) mixture is proposed, and the mixture used in systems with two evaporation temperatures and operating modes affected by ambient temperature are studied. The energy efficiency, economic performance and emission reduction potential of the whole life cycle are conducted to compare with the pure CO 2 booster refrigeration system. Furthermore, the influence of climate condition is discussed when used in 40 typical cities around the world. The results show the coefficient of performance (COP) of booster refrigeration system can be significantly improved by using CO 2 /HA mixtures. As the ambient temperature is 33 degrees C, the CO 2 /R1234yf (93/7) operates with the maximum COP of 1.367, which is 11.59 % higher than that of pure CO 2 . Using CO 2 /HA mixtures in the booster refrigeration system can significantly improve the exergy efficiency of system. Moreover, the system using CO 2 /HA mixtures has higher annual performance factor and lower life cycle cost (LCC) than pure CO 2 . LCC of the system using CO 2 /R1234yf (94/6) is the lowest, and the reduction rate is 3.06 - 5.59 %. Meanwhile, the life cycle carbon emissions of systems in different climatic regions using CO 2 /R1234yf can be reduced by 2.39 - 5.21 %. The booster refrigeration system adopting CO 2 /HA mixtures is a promising alternative solution for commercial supermarket refrigeration and energy -saving.
Keyword ：
CO2/Halogenated alkene mixture CO2/Halogenated alkene mixture Economic and environmental analysis Economic and environmental analysis Energy and exergy performance Energy and exergy performance Life cycle assessment Life cycle assessment Supermarket booster refrigeration system Supermarket booster refrigeration system
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| GB/T 7714 | Dai, Baomin , Wu, Tianhao , Liu, Shengchun et al. Assessment of booster refrigeration system with eco-friendly working fluid CO 2 /halogenated alkene (HA) mixture for supermarket application around the world: Energy conservation, cost saving, and emissions reduction potential [J]. | ENERGY , 2024 , 297 . |
| MLA | Dai, Baomin et al. "Assessment of booster refrigeration system with eco-friendly working fluid CO 2 /halogenated alkene (HA) mixture for supermarket application around the world: Energy conservation, cost saving, and emissions reduction potential" . | ENERGY 297 (2024) . |
| APA | Dai, Baomin , Wu, Tianhao , Liu, Shengchun , Zhang, Peng , Zhang, Jianing , Fu, Rao et al. Assessment of booster refrigeration system with eco-friendly working fluid CO 2 /halogenated alkene (HA) mixture for supermarket application around the world: Energy conservation, cost saving, and emissions reduction potential . | ENERGY , 2024 , 297 . |
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