Research Progress----Shanghai Advanced Research Institute,Chinese Academy of Sciences

NOW OPEN: The expression plasmids for all 29 proteins encoded by the COVID-19 virus are available for request

Now, expression plasmids for all these 29 proteins are available to global scientists through a Protein Bank Program (PBP) launched by the National Facility for Protein Science in Shanghai (NFPS).

2020-06-22 more+

Efficient Indium Oxide Catalysts Designed for CO2 Hydrogenation to Methanol

Catalytic hydrogenation of carbon dioxide is a green and sustainable means of synthesizing commodity chemicals such as methanol.Recent studies revealed the potential for a family of metal oxides to catalyze this reaction. However, further optimizing their catalytic performance for industrial applications remained a great challenge.A team at the Shanghai Advanced Research Institute (SARI) of the Chinese Academy of Sciences reported a successful case of theory-guided rational design of indium oxide (In2O3) catalysts for CO2 hydrogenation to methanol with high activity and selectivity.

　　Catalytic hydrogenation of carbon dioxide (CO2) is a green and sustainable means of synthesizing commodity chemicals such as methanol. This conversion process is key to realizing the “methanol economy” or creating “liquid sunshine,” both aspects of the circular economy. Recent studies revealed the potential for a family of metal oxides to catalyze this reaction. However, further optimizing their catalytic performance for industrial applications remained a great challenge, mostly due to the difficulties related to the rational design and controlled synthesis of these catalysts.
　　Motivated by such a challenge, a team jointly led by Profs. SUN Yuhan, GAO Peng, and LI Shenggang at the Shanghai Advanced Research Institute (SARI) of the Chinese Academy of Sciences, reported a successful case of theory-guided rational design of indium oxide (In2O3) catalysts for CO2 hydrogenation to methanol with high activity and selectivity. The new findings were published in the latest issue of Science Advances on June 17.
　　To rationally design In2O3-based nanocatalysts with favorable methanol synthesis performance, researchers carried out extensive density functional theory (DFT) calculations to establish the catalytic mechanism of the In2O3 catalyst during CO2 hydrogenation to methanol and carbon dioxide by identifying preferred pathways. The computational modeling identified the rarely studied {104} facet of hexagonal In2O3 as the most favorable for methanol synthesis.
　　On the basis of this theoretical prediction, several experimental methods were then employed to synthesize In2O3 catalysts in different phases with distinct morphologies.
　　Interestingly, one of the four In2O3 catalysts synthesized in this way was confirmed to mainly expose the theoretically identified {104} facets. This catalyst also exhibited the best performance in terms of both activity and selectivity, confirming the DFT prediction. The methanol synthesis reaction catalyzed by this catalyst is favorable even at the very high temperature of 360 °C.
　　The space-time yield of methanol reached 10.9 mmol/g/hour at this temperature, which surpassed all previously known catalysts for this reaction, including previously reported In2O3-based catalysts and well-known Cu-based catalysts.
　　The In2O3 catalyst discovered in this research is promising as a way to directly convert CO2 into methanol for industrial applications. In addition, the discovery of this In2O3 catalyst will promote the further development of oxide/zeolite bifunctional catalysts for direct CO2 hydrogenation to various C2+ hydrocarbons (lower olefins, gasoline, aromatics and so on) via the methanol intermediate. Just as importantly, this discovery also highlights the pivotal role of computational science in helping to design industrially relevant catalysts.
　　 Schematic illustration of the most favorable CO2 hydrogenation pathways on different cubic (c–In2O3) and hexagonal indium oxide (c–In2O3) surfaces (Figures adapted from Science Advances)
　　
　　 Structural characterization and catalytic performance of various In2O3 catalyst materials for CO2 hydrogenation (Figures adapted from Science Advances)
　　

2020-06-18 more+

SSRF Helps on the COVID-19 Structure Determination to Understand the Infection Mechanism and Drugs R&D

To meet the urgent needs of determining the protein structure, Shanghai Synchrotron Radiation Facility (SSRF) has opened a green channel to fully support the research teams carrying out studies related to COVID-19. At the end of January, SSRF promptly rebooted the accelerator that was shut down for maintenance. Three protein crystallography beamlines reopened: BL17U1, BL18U1 and BL19U1, which also played a significant role in the studies of the previous epidemic like H1N1, H7N9, MERS, Zika, and Ebola.

　　Since the outbreak of novel coronavirus 2019 (COVID-19), the number of confirmed cases has reached 1,016,000 worldwide and the global death has exceeded 53,000. This highly infectious disease is caused by the virus SARS-CoV-2. COVID-19 poses a great threat to human activities and keeps the world in suspense. A comprehensive knowledge of this novel virus will help fight against COVID-19. Several important proteins play a crucial role in the process of the virus infection. Structural information of these proteins will be helpful for the understanding of the infectious mechanism and offer a basis for the drug development. Macromolecular X-Ray Crystallographys using synchrotron radiation facility is an efficient technique to determine the 3-D structures of protein.
　　
　　To meet the urgent needs of determining the protein structure, Shanghai Synchrotron Radiation Facility (SSRF) has opened a green channel to fully support the research teams carrying out studies related to COVID-19. At the end of January, SSRF promptly rebooted the accelerator that was shut down for maintenance. Three protein crystallography beamlines reopened: BL17U1, BL18U1 and BL19U1, which also played a significant role in the studies of the previous epidemic like H1N1, H7N9, MERS, Zika, and Ebola.
　　
　　Since January 2020, SSRF has assisted research teams by arranging enough beam shifts (Jan. 12, Feb. 2-3, Feb. 11, Feb. 17, and Feb. 23) to carry out their studies on protein structure related to COVID-19 and selection of candidate active substances, including Zihe Rao team for the viral main protease (Mpro or also 3CLpro), Jianxun Qi and Xinquan Wang teams for the spike protein, and other teams for the drug screening.
　　
　　1. On January 12, 2020, the research team led by Zihe Rao and Haitao Yang at Shanghai Tech University collected the diffraction data of COVID-19 coronavirus 3CL hydrolase (Mpro) and took the lead in determining its high-resolution crystal structure. Related link:
　　https://www.rcsb.org/news?year=2020&article=5e39e03fa5007a04a313edc3
　　The crystal structure of COVID-19 Main protease in complex with an inhibitor N3 (PDB entry 6LU7)
　　
　　2. On February 11, 2020, the research team led by Jianxun Qi at Institute of Microbiology, CAS, collected the diffraction data of COVID-19 RBD-ACE2 and shared its 2.5 ANG crystal structure to the whole community. An article titled with “structural and functional basis of SARS-CoV2 entry by using human ACE2” was published on Cell.
　　DOI: 10.1016/j.cell.2020.03.045
　　Structure of novel coronavirus spike receptor-binding domain complexed with its receptor ACE2 (PDB entry 6LZG)
　　
　　3. On February 17, 2020, the research team led by Xinquan Wang and Linqi Zhang at Tsinghua University collected the diffraction data of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor, then determined and shared its crystal structure. The article was published on Natural on March 30, 2020:
　　https://www.nature.com/articles/s41586-020-2180-5
　　Crystal structure of COVID-19 spike receptor-binding domain bound with ACE2
　　(PDB entry 6M0J))
　　
　　4. Moreover, beamtime was also allocated to the relevant drug screening. There are six research teams working on drug development at SSRF during this rapid access program simultaneously. Dozens of potential active substances are screened.
　　 SSRF will be available to all users very soon and also continue to give higher priority to drug development against COVID-19.

2020-04-07 more+

Researchers Reveal a Dynamic Mechanism for Ni–Au Bimetallic Nanoparticles during CO2 Hydrogenation

The high catalytic performance of core–shell nanoparticles (NP) is usually attributed to the syngergy of distinct geometric and electronic structures. Although the general assumption is that core–shell NPs maintain their configuration under working conditions, it remains unclear whether they maintain their structure throughout a reaction.Scientists recently reported a different working mechanism and demonstrated that the core–shell structure may not exist under a specific set of conditions, which overturns the conventional understanding.

　　The high catalytic performance of core–shell nanoparticles (NP) is usually attributed to the syngergy of distinct geometric and electronic structures. Although the general assumption is that core–shell NPs maintain their configuration under working conditions, it remains unclear whether they maintain their structure throughout a reaction.
　　Scientists recently reported a different working mechanism and demonstrated that the core–shell structure may not exist under a specific set of conditions, which overturns the conventional understanding.
　　
　　The results appear in a study conducted by a team from the Shanghai Advanced Research Institute (SARI) of the Chinese Academy of Sciences (CAS) along with other collaborators in the latest issue of Nature Catalysis entitled “Reversible loss of core–shell structure for Ni–Au bimetallic nanoparticles during CO2 hydrogenation.”
　　
　　The scientists use environmental transmission electron microscopy (ETEM) to directly visualize the dynamic process at atomic level, coupled with multiple state-of-the-art in situ techniques, including synchrotron X-ray absorption spectroscopy, infrared spectroscopy and theoretical simulations, to precisely analyze the imaging conditions of over 3,000 high-resolution transmission electron microscopy (TEM) images.
　　
　　By tracing the real-time changes of the surface atomic structure during the entire reaction process, the result exhibits a highly selective CO production in CO2 hydrogenation, features an intact ultrathin Au shell over the Ni core before and after the reaction. However, the catalytic performance could not be attributed to the Au shell surface, but rather to the formation of a transient reconstructed alloy surface, promoted by CO adsorption during the reaction.
　　
　　Density functional theory (DFT) calculations also confirmed that it is the kinetically alloyed surface, rather than the ultrathin Au shell surface, that is catalytically active during the highly selective reverse water gas shift reaction.
　　
　　The discovery of such a reversible transformation urges us to reconsider the reaction mechanism beyond the stationary model, and may have important implications not only for core–shell nanoparticles, but also for other well-defined nanocatalysts.
　　Dynamic Mechanism for Ni–Au Bimetallic Nanoparticles during CO2 Hydrogenation (Image by SARI)
　　In situ observation and theoretical interpretation of the structural transition of NiAu NPs during the reaction (Figures adapted from Nature Catalysis)
　　Contact: GAO Yi
　　Shanghai Advanced Research Institute, Chinese Academy of Sciences
　　Email: gaoyi@zjlab.org.cn
　　

2020-04-01 more+

Novel Approach to Pt Electroless Deposition for Highly Efficient Hydrogen Evolution

The small size and large specific surface area intrinsically associated with Pt atomic clusters pose challenges in the synthesis and stabilization of Pt-ACs without agglomeration. A research team reported a novel one-step carbon-defect-driven electroless deposition (ELD) method to produce ultrasmall but well-defined and stable Pt-ACs supported by defective graphene (Pt-AC/DG) structures.

　　Pt atomic clusters (Pt-ACs) display outstanding electrocatalytic performance because of their unique electronic structure with a large number of highly exposed surface atoms. However, the small size and large specific surface area intrinsically associated with ACs pose challenges in the synthesis and stabilization of Pt-ACs without agglomeration.
　　
　　Motivated by such a challenge, a research team led by Prof. YANG Hui at Shanghai Advanced Research Institute (SARI) of the Chinese Academy of Sciences collaborated with Prof. DAI Liming at Case Western Reserve University of the United States reported a novel one-step carbon-defect-driven electroless deposition (ELD) method to produce ultrasmall but well-defined and stable Pt-ACs supported by defective graphene (Pt-AC/DG) structures. The research results were published in the Journal of the American Chemical Society entitled " Carbon-Defect-Driven Electroless Deposition of Pt Atomic Clusters for Highly Efficient Hydrogen Evolution”.
　　
　　A theoretical simulation clearly revealed that the defective regions with a lower work function, and hence a higher reducing capacity, than that of normal hexagonal sites triggered the reduction of Pt ions preferentially at the defect sites.
　　
　　Moreover, the strong binding energy between Pt and carbon defects effectively restricted the migration of spontaneously reduced Pt atoms to immobilize/stabilize the resultant Pt-ACs.
　　
　　The prepared Pt-AC/DG catalysts exhibited superb electrocatalytic performance for the hydrogen evolution reaction (HER) with a greatly enhanced Pt utilization efficiency and stability with significantly reduced Pt usage compared with the use of commercial Pt/C catalysts.
　　
　　Water electrolysis based on renewable energy is the key of hydrogen production. However, large usage of precious metal catalysts is the primary reason of high costs in HER. The study provides an ideal strategy for the future development of cost effective Pt-based catalysts for the HER and many other reactions.
　　Electrocatalytic performance of the prepared Pt-AC/DG catalysts (Image by Prof. YANG’s group)
　　Contact: YANG Hui
　　Shanghai Advanced Research Institute, Chinese Academy of Sciences
　　Email: yangh@sari.ac.cn
　　

2020-03-30 more+

Researchers Develop an Intelligent Spectrum Sensing Technique for 5G communications

The ongoing 5G communication involves diversified scenarios with different characteristics and diverse requirements, which makes spectrum sensing methods difficult to serve various applications flexibly while maintaining satisfactory performance. Motivated by such a challenge,researchers provided a novel spectrum sensing technique, seeking a feasible way to combine the reinforcement learning concept with advanced spectrum sensing methods so as to optimize the performance of the cognitive radio network under multifarious scenarios in 5G communications.

　　Spectrum sensing plays an important role in future wireless communication systems as it helps to resolve the coexistence issue and optimize spectrum efficiency. However, the ongoing 5G communication involves diversified scenarios with different characteristics and diverse requirements, which makes spectrum sensing methods difficult to serve various applications flexibly while maintaining satisfactory performance. The scarcity of spectrum resource remains a critical challenge for 5G communications.
　　
　　Motivated by such a challenge, a research team led by Prof. HU Honglin and Prof. XU Tianheng at Shanghai Advanced Research Institute (SARI) of the Chinese Academy of Sciences provided a novel spectrum sensing technique, seeking a feasible way to combine the reinforcement learning concept with advanced spectrum sensing methods so as to optimize the performance of the cognitive radio network under multifarious scenarios in 5G communications. The research results were published in the latest issue of IEEE Wireless Communications entitled “Intelligent Spectrum Sensing: When Reinforcement Learning Meets Automatic Repeat Sensing in 5G Communications.”
　　
　　The research team analyzes different requirements of several typical 5G scenarios, and categorizes three dedicated models with respective optimization targets for spectrum sensing techniques. In order to be adaptive for various optimization targets, scientists have designed the architecture for the intelligent spectrum sensing technique, trying to take account of both instability and adaptability issues. Numerical results manifested that the proposed sensing technique has the capability of adapting to various scenarios with different optimization targets.
　　
　　The research results are promising for practical applications. They have been applied in the SEANET system developed by CAS and Alpha, a campus network constructed by CAS and ShanghaiTech University. The results also contribute to further deployment and promotion of 5G and next generation communication system in China.
　　
　　This research was supported in part by the National Natural Science Foundation of China, the Shanghai Rising-Star Program, the Shanghai Young Talent Sailing Program and the Program of Shanghai Academic Research Leader.
　　Three typical spectrum sensing involved scenarios in 5G communications: that is, throughput-oriented scenarios (a), energy saving-oriented scenarios (b), and sensing accuracy-oriented scenarios(c) (Image by SARI)
　　Reinforcement-learning-driven automatic repeat sensing mechanism (Image by SARI)
　　Performance comparison among three intelligent sensing strategies: a) Sensing accuracy performance; b) Throughput performance (Image by SARI)
　　Contact: HU Honglin
　　Shanghai Advanced Research Institute, Chinese Academy of Sciences
　　Email:huhl@sari.ac.cn

2020-03-25 more+