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| 1 | Using Artificial Neural Networks for Energy Regulation Based Variable-speed Electrohydraulic Drive显示文摘In the energy regulation based varibable-speed electrohydraulic drive system, the supply energy and the demanded energy, which will affect the control performance greatly, are crucial. However, they are hard to be obtained via conventional methods for some reasons. This paper tries to a new route: the definitive numerical values of the supply energy and the demanded energy are not required, except for their relationship which is called energy state. A three-layer back propagation(BP) neural network was built up to act as an energy analysis unit to deduce the energy state. The neural network has three inputs: the reference displacement, the actual displacement of cylinder rod and the system flowrate supply. The output of the neural network is energy state. A Chebyshev type II filter was designed to calculate the cylinder speed for the estimation of system flowrate supply. The training and testing samples of neural network were collected by the system accurate simulation model. After off-line training, the neural network was tested by the testing data. And the testing result demonstrates that the designed neural network was successful. Then, the neural network acts as the energy analysis unit in real-time experiments of cylinder position control, where it works efficiently under square-wave and sine-wave reference displacement. The experimental results validate its feasibility and adaptability. Only a position sensor and some pressure sensors, which are cheap and have quick dynamic response, are necessary for the system control. And the neural network plays the role of identifying the energy state. | XU Ming JIN Bo YU Yaxin SHEN Haikuo LI Wei | 2010 | Chinese Journal of Mechanical Engineering2010，23，3： | 3 |
| 2 | Nano-polycrystalline diamond formation under ultra-high pressure显示文摘 | Chao Xu Duanwei He Haikuo Wang Junwei Guan Chunmei Liu Fang Peng Wendan Wang Zili Kou Kai He Xiaozhi Yan Yan Bi Lei Liu Fengjiao Li Bo Hui | 2013 | International Journal of Refractory Metals and Hard Materials2013，，： | 2 |
| 3 | In sight of K-deficient layered K_(x)MnO_(2) cathode for potassium-ions batteries显示文摘Potassium-ions batteries(PIBs)are attracting increasing attention as up-and-coming youngster in largescale grid-level energy storage benefiting from its low-cost and high energy density.Nevertheless,enough researches regarding indispensable cathode materials for PIBs are badly absent.Herein,we synthesize K-deficient layered manganese-based oxides(P2-K_(0.21)MnO_(2) and P3-K_(0.23)MnO_(2))and investigate them as cathode of PIBs for the first time.As the newcomer of potassium-containing layered manganese-based oxides(K_(x)MnO_(2))group,P2-K_(0.21)MnO_(2) delivers high discharge capacity of 99.3 mAh g^(-1) and P3-K_(0.23)MnO_(2) exhibits remarkable capacity retention rate of 75.5%.Besides,in-situ XRD and ex-situ XRD measurements reveal the reversible phase transition of P2-K_(0.21)MnO_(2) and P3-K_(0.23)MnO_(2) with the potassium-ions extraction and reinsertion,respectively.This work contributes to a better understanding for the potassium storage in K-deficient layered K_(x)MnO_(2)(x≤0.23),possessing an important basic scientific significance for the exploitation and application of layered K_(x)MnO_(2) in PIBs. | Tiezhong Liu Shuang Hou Youpeng Li Shoufeng Xue Junhua Hu Haikuo Fu Chenghao Yang Lingzhi Zhao | 2022 | Journal of Energy Chemistry2022，31，1： | 2 |
| 4 | Deep Learning Accelerates the Discovery of Two- Dimensional Catalysts for Hydrogen Evolution Reaction显示文摘Two-dimensional materials with active sites are expected to replace platinum as large-scale hydrogen production catalysts.However,the rapid discovery of excellent two-dimensional hydrogen evolution reaction catalysts is seriously hindered due to the long experiment cycle and the huge cost of high-throughput calculations of adsorption energies.Considering that the traditional regression models cannot consider all the potential sites on the surface of catalysts,we use a deep learning method with crystal graph convolutional neural networks to accelerate the discovery of high-performance two-dimensional hydrogen evolution reaction catalysts from two-dimensional materials database,with the prediction accuracy as high as 95.2%.The proposed method considers all active sites,screens out 38 high performance catalysts from 6,531 two-dimensional materials,predicts their adsorption energies at different active sites,and determines the potential strongest adsorption sites.The prediction accuracy of the two-dimensional hydrogen evolution reaction catalysts screening strategy proposed in this work is at the density-functional-theory level,but the prediction speed is 10.19 years ahead of the high-throughput screening,demonstrating the capability of crystal graph convolutional neural networks-deep learning method for efficiently discovering high-performance new structures over a wide catalytic materials space. | Sicheng Wu Zhilong Wang Haikuo Zhang Junfei Cai Jinjin Li | 2023 | Energy & Environmental Materials2023，6，1： | 1 |
| 5 | Modeling of wave propagation in plate structures using three-dimensional spectral element method for damage detection 显示文摘 | Peng Haikuo Meng Guang Li Fucai | 2009 | Journal of Sound and Vibration2009，320，： | 1 |
| 6 | Nanoparticle PCR:Nanogold-assisted PCR with enhanced specificity显示文摘 | Haikuo Li Huang J H Lu J H | 2005 | Angew Chem Int Ed2005，44，32： | 1 |
| 7 | Nanoparticle PCR: Nanogold-assisted PCR with enhanced specificity 显示文摘 | Haikuo Li Huang J H Lu J H | 2005 | Angew Chem Int Ed2005，44，32： | 1 |
| 8 | Diluent decomposition-assisted formation of Li F-rich solid-electrolyte interfaces enables high-energy Li-metal batteries显示文摘Passivation by the inorganic-rich solid electrolyte interphase(SEI),especially the LiF-rich SEI,is highly desirable to guarantee the durable lifespan of Li metal batteries(LMBs).Here,we report a diluent with the capability to facilitate the formation of LiF-rich SEI while avoiding the excess consumption of Li salts.Dissimilar to most of reported inert diluents,heptafluoro-l-methoxypropane(HM) is firstly demonstrated to cooperate with the decomposition of anions to generate LiF-rich SEI via releasing Fcontaining species near Li surface.The designed electrolyte consisting of 1.8 M LiFSI in the mixture of1,2-dimethoxyethane(DME)/HM(2:1 by vol.) achieves excellent compatibility with both Li metal anodes(Coulombic efficiency~99.8%) and high-voltage cathodes(4.4 V LiNi_(0.8)Mn_(0.1)Co_(0.1)O_(2)(NMC811) and 4.5 V LiCoO_(2)(LCO) vs Li^(+)/Li).The 4.4 V Li(20μm)‖NMC811(2.5 mA h cm^(-2)) and 4.5 V Li(20μm)‖LCO(2.5 mA h cm^(-2)) cells achieve capacity retentions of 80% over 560 cycles and 80% over 505 cycles,respectively.Meanwhile,the anode-free pouch cell delivers an energy density of~293 W h kg^(-1)initially and retains 70% of capacity after 100 deep cycles.This work highlights the critical impact of diluent on the SEI formation,and opens up a new direction for designing desirable interfacial chemistries to enable high-performance LMBs. | Junbo Zhang Haikuo Zhang Ruhong Li Ling Lv Di Lu Shuoqing Zhang Xuezhang Xiao Shujiang Geng Fuhui Wang Tao Deng Lixin Chen Xiulin Fan | 2023 | Journal of Energy Chemistry2023，，3： | 0 |
| 9 | Electrolyte and interphase engineering through solvation structure regulation for stable lithium metal batteries显示文摘Lithium metal batteries(LMBs)are considered to be one of the most promising high-energy-density battery systems.However,their practical application in carbonate electrolytes is hampered by lithium dendrite growth,resulting in short cycle life.Herein,an electrolyte regulation strategy is developed to improve the cyclability of LMBs in carbonate electrolytes by introducing LiNO3 using trimethyl phosphate with a slightly higher donor number compared to NO_(3)^(-)as a solubilizer.This not only allows the formaion of Li^(+)-coordinated NO3 but also achieves the regulation of electrolyte solvation structures,leading to the formation of robust and ion-conductive solid-electrolyte interphase films with inorganic-rich inner and organic-rich outer layers on the Li metal anodes.As a result,high Coulombic efficiency of 99.1%and stable plating/stripping cycling of Li metal anode in LilCu cells were realized.Furthermore,excellent performance was also demonstrated in Li||LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM83)full cells and Cul/NCM83 anodefree cells using high mass-loading cathodes.This work provides a simple interphase engineering strategy through regulating the electrolyte solvation structures for high-energy-density LMBs. | Hai Su Haikuo Zhang Zifeng Chen Mengjie Li Jiwei Zhao Haiyan Xun Jie Sun Yunhua Xu | 2023 | Chinese Chemical Letters2023，34，12： | 0 |
| 10 | Incorporating multifunctional LiAlSiO_(4) into polyethylene oxide for high-performance solid-state lithium batteries显示文摘High ionic conductivity,good electrochemical stability,and satisfactory mechanical property are the crucial factors for polymer solid state electrolytes.Herein,fast ion conductor LiAlSiO_4(LASO) is incorporated into polyethylene oxide(PEO)-based solid-state electrolytes(SSEs).The SSEs containing LASO exhibit enhanced mechanical properties performance compared to pristine PEO-LiTFSI electrolyte.A reduced melting transition temperature of 40.57℃ is enabled by introducing LASO in to PEO-based SSE,which is beneficial to the motion of PEO chain and makes it possible for working at a moderate environment.Coupling with the enhanced motion of PEO,dissociation of the lithium salt,and conducting channel of LASO,the optimized composite polymer SSE exhibits a high ionic conductivity of 4.68×10^(-4),3.16×10^(-4) and 1.62×10^(-4) S cm^(-1) at 60,50 and 40℃,respectively.The corresponding LiFePO_4//Li solid-state battery exhibits high specific capacities of 166,160 and 139 mAh g^(-1) at 0.2 C under 60,40 and 25℃.In addition,it remains 130 mAh g^(-1) at 4.0 C,and maintains 91.74% after 500 cycles at 1.0 C under 60℃.This study provides a simple approach for developing ionic conductor-filled polymer electrolytes in solid-state lithium battery application. | Yuqi Wu Xinhai Li Guochun Yan Zhixing Wang Huajun Guo Yong Ke Lijue Wu Haikuo Fu Jiexi Wang | 2021 | Journal of Energy Chemistry2021，30，2： | 0 |
| 11 | Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression显示文摘An altered proteome in lymph nodes often suggests abnormal signaling pathways that may be associated with diverse lymphatic disorders.Current clinical biomarkers for histological classification of lymphomas have encountered many discrepancies,particularly for borderline cases.Therefore,we launched a comprehensive proteomic study aimed to establish a proteomic landscape of patients with various lymphatic disorders and identify proteomic variations associated with different disease subgroups.In this study,109 fresh-frozen lymph node tissues from patients with various lymphatic disorders(with a focus on Non-Hodgkin’s Lymphoma)were analyzed by data-independent acquisition mass spectrometry.A quantitative proteomic landscape was comprehensively characterized,leading to the identification of featured protein profiles for each subgroup.Potential correlations between clinical outcomes and expression profiles of signature proteins were also probed.Two representative signature proteins,phospholipid-binding proteins Annexin A6(ANXA6)and Phospholipase C Gamma 2(PLCG2),were successfully validated via immunohistochemistry.We also evaluated the capability of acquired proteomic signatures to segregate multiple lymphatic abnormalities and identified several core signature proteins,such as Sialic Acid Binding Ig Like Lectin 1(SIGLEC1)and GTPase of immunity-associated protein 5(GIMAP5).In summary,the established lympho-specific data resource provides a comprehensive map of protein expression in lymph nodes during multiple disease states,thus extending the existing human tissue proteome atlas.Our findings will be of great value in exploring protein expression and regulation underlying lymphatic malignancies,while also providing novel protein candidates to classify various lymphomas for more precise medical practice. | Xin Ku Jinghan Wang Haikuo Li Chen Meng Fang Yu Wenjuan Yu Zhongqi Li Ziqi Zhou Can Zhang Ying Hua Wei Yan Jie Jin | 2023 | Phenomics2023，3，2： | 0 |
| 12 | Predicting adsorption ability of adsorbents at arbitrary sites for pollutants using deep transfer learning显示文摘Accurately evaluating the adsorption ability of adsorbents for heavy metal ions(HMIs)and organic pollutants in water is critical for the design and preparation of emerging highly efficient adsorbents.However,predicting adsorption capabilities of adsorbents at arbitrary sites is challenging,with currently unavailable measuring technology for active sites and the corresponding activities.Here,we present an efficient artificial intelligence(AI)approach to predict the adsorption ability of adsorbents at arbitrary sites,as a case study of three HMIs(Pb(Ⅱ),Hg(Ⅱ),and Cd(Ⅱ))adsorbed on the surface of a representative two-dimensional graphitic-C_(3)N_(4).We apply the deep neural network and transfer learning to predict the adsorption capabilities of three HMIs at arbitrary sites,with the predicted results of Cd(Ⅱ)>Hg(Ⅱ)>Pb(Ⅱ)and the root-mean-squared errors less than 0.1 eV.The proposed AI method has the same prediction accuracy as the ab initio DFT calculation,but is millions of times faster than the DFT to predict adsorption abilities at arbitrary sites and only requires one-tenth of datasets compared to training from scratch.We further verify the adsorption capacity of g-C_(3)N_(4) towards HMIs experimentally and obtain results consistent with the AI prediction.It indicates that the presented approach is capable of evaluating the adsorption ability of adsorbents efficiently,and can be further extended to other interdisciplines and industries for the adsorption of harmful elements in aqueous solution. | Zhilong Wang Haikuo Zhang Jiahao Ren Xirong Lin Tianli Han Jinyun Liu Jinjin Li | 2021 | npj Computational Materials2021，，1： | 0 |
| 13 | High performance wide bandgap perovskite solar cell with low V_(OC)deficit less than 0.4 V显示文摘Wide bandgap perovskite solar cells(PSCs)have attracted significant attention because they can be applied to the top cells of tandem solar cells.However,high open-circuit voltage(V_(OC))deficit(>0.4 V)result from poor crystallization and high non-radiative recombination losses become a serious limitation in the pursuit of high performance.Here,the relevance between different Pbl_(2)proportions and performance parameters are revealed through analysis of surface morphology,residual stress,and photostability.The increase of Pbl_(2)proportion promotes crystal growth and reduces the work function of the perovskite film surface and promotes the energy level alignment with the carrier transport layer,which decreased the V_(OC)deficit.However,residual PbI_(2)exacerbated the stress level of perovskite film,and the resulting lattice disorder deteriorated the photostability of the device.Ultimately,after the synergistic passivation of residual PbI_(2)and PEAI,the V_(OC)achieves 1.266 V and V_(OC)deficit is less than 0.4 V,the record value in wide bandgap PSCs. | Haikuo Guo Fuhua Hou Xuli Ning Xiaoqi Ren Haoran Yang Rui Liu Tiantian Li Chengjun Zhu Ying Zhao Wei Li Xiaodan Zhang | 2024 | Journal of Energy Chemistry2024，91，4： | 0 |
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