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| 1 | An all-round AI-Chemist with a scientific mind显示文摘The realization of automated chemical experiments by robots unveiled the prelude to an artificial intelligence(AI)laboratory.Several AI-based systems or robots with specific chemical skills have been demonstrated,but conducting all-round scientific research remains challenging.Here,we present an all-round AI-Chemist equipped with scientific data intelligence that is capable of performing basic tasks generally required in chemical research.Based on a service platform,the AI-Chemist is able to automatically read the literatures from a cloud database and propose experimental plans accordingly.It can control a mobile robot in-house or online to automatically execute the complete experimental process on 14 workstations,including synthesis,characterization and performance tests.The experimental data can be simultaneously analysed by the computational brain of the AI-Chemist through machine learning and Bayesian optimization,allowing a new hypothesis for the next iteration to be proposed.The competence of the AI-Chemist has been scrutinized by three different chemical tasks.In the future,the more advanced all-round AI-Chemists equipped with scientific data intelligence may cause changes to the landscape of the chemical laboratory. | Qing Zhu Fei Zhang Yan Huang Hengyu Xiao LuYuan Zhao XuChun Zhang Tao Song XinSheng Tang Xiang Li Guo He BaoChen Chong JunYi Zhou YiHan Zhang Baicheng Zhang JiaQi Cao Man Luo Song Wang GuiLin Ye WanJun Zhang Xin Chen Shuang Cong Donglai Zhou Huirong Li Jialei Li Gang Zou WeiWei Shang Jun Jiang Yi Luo | 2022 | National Science Review2022，9，10： | 5 |
| 2 | Formation and growth mechanisms of ultrafine particles in sludge-incineration flue gas显示文摘Atmospheric particulate matter with diameter<2.5μm now makes up much of the air pollution in China,but it is the ultrafine particles(UFPs)with diameter<90 nm that are of particular interest.This is because UFPs are strongly linked with human health for two reasons:they contain a variety of hazardous substances and they can deeply penetrate human respiratory systems.Therefore,scanning electron microscopy combined with X-ray dispersive energy spectrometry was used to characterize the morphology and surface texture,as well as the elemental composition of 60 UFPs.The UFPs was generated in a sewage sludge-incineration power plant in Zhejiang Province.This was done to determine the microstructure of the ultrafine particles and to follow the evolution of particle surface elemental composition with increasing particle size.Then,a comparison of the characteristic time for nucleation,condensation and coagulation was done to estimate the dominant mechanism.The results show that the UFPs have generally irregular shapes(cotton-like,irregular balls,sheets,etc.)and that they usually aggregate to form a mass.With increase in the size of a UFP,the mass fraction of the elements presents clearly changed:Na,K and Fe gradually decreased;while Ca,Si and Al,as well as the heavy metals Cu,Zn and Ni increased.Characteristic time estimation is a convenient and effective tool for identifying the predominant mechanisms during combustion.In this study,calculations of characteristic time were used to reveal a mechanism of vaporization,nucleation,condensation and coagulation,which drives the formation and growth of ultrafine particles. | Yanlong Li Jiaqi Man Zhengquan Fang Yunbin Zhao Feng Wang Rundong Li | 2019 | Waste Disposal and Sustainable Energy2019，1，2： | 1 |
| 3 | The Systemic Immune Inflammatory Index Predicts No-Reflow Phenomenon after Primary Percutaneous Coronary Intervention in Older Patients with STEMI显示文摘Purpose:Coronary no-reflow phenomenon(NRP),a common adverse complication in patients with ST-segment eleva-tion myocardial infarction(STEMI)treated by percutaneous coronary intervention(PCI),is associated with poor patient prognosis.In this study,the correlation between the systemic immune-inflammation index(SII)and NRP in older patients with STEMI was studied,to provide a basis for early identification of high-risk patients and improve their prognosis.Materials and methods:Between January 2017 and June 2020,578 older patients with acute STEMI admitted to the Department of Cardiology of Hebei General Hospital for direct PCI treatment were selected for this retrospective study.Patients were divided into an NRP group and normal-flow group according to whether NRP occurred during the operation.Clinical data and the examination indexes of the two groups were collected.Logistic regression was used to analyze the independent predictors of NRP,and the receiver operating characteristic curve was used to further analyze the ability of SII to predict NRP in older patients with STEMI.Results:Multivariate logistic analysis indicated that hypertension(OR=2.048,95%CI:1.252–3.352,P=0.004),lymphocyte count(OR=0.571,95%CI:0.368–0.885,P=0.012),platelet count(OR=1.009,95%CI:1.005–1.013,P<0.001),hemoglobin(OR=1.015,95%CI:1.003–1.028,P=0.018),multivessel disease(OR=2.237,95%CI:1.407–3.558,P=0.001),and SII≥1814(OR=3.799,95%CI:2.190–6.593,P<0.001)were independent predictors of NRP after primary PCI in older patients with STEMI.Receiver operating characteristic curve analysis demonstrated that SII had a high predictive value for NRP(AUC=0.738;95%CI:0.686–0.790),with the best cut-off value of 1814,a sensitivity of 52.85%and a specificity of 85.71%.Conclusion:For older patients with STEMI undergoing primary PCI,SII is a valid predictor of NRP. | Jiaqi Wang Feifei Zhang Man Gao Yudan Wang Xuelian Song Yingxiao Li Yi Dang Xiaoyong Qi | 2023 | Cardiovascular Innovations and Applications2023，7，1： | 0 |
| 4 | A fully self-powered, natural-light-enabled fiber-optic vibration sensing solution显示文摘Fiber-optic sensors have been developed to monitor the structural vibration with advantages of high sensitivity,immunity to electromagnetic interference(EMI),flexibility,and capability to achieve multiplexed or distributed sensing.However,the current fiber-optic sensors require precisely polarized coherent lasers as the lighting sources,which are expensive in cost and suffer from the power supply issues while operating at outdoor environments.This work aims at solving these issues,through developing a fully self-powered,natural-light-enabled approach.To achieve that,a spring oscillator-based triboelectric nanogenerator(TENG),a polymer network liquid crystal(PNLC),and an optical fiber were integrated.The external vibration drove the PNLC to switch its transparency,allowing the varia-tion of the incident natural light in the optical fiber.Compared with the majority of conventional TENG-based active vibration sensors,the developed paradigm does not suffer from the EMI,without requirements of the signal preamplifica-tion which consumes additional energy.The vibration displacement monitoring was performed to validate the sensing effectiveness of the developed paradigm. | Jiaqi Wang Ho-Yin Man Cuiling Meng Pengcheng Liu Shaoxin Li Hoi-Sing Kwok Yunlong Zi | 2021 | SusMat2021，1，4： | 0 |
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