This work reports the use of defect engineering and carbon supporting to achieve metal-doped phosphides with high activities and stabilities for the hydrogen evolution reaction(HER)and the oxygen evolution reaction(OE...This work reports the use of defect engineering and carbon supporting to achieve metal-doped phosphides with high activities and stabilities for the hydrogen evolution reaction(HER)and the oxygen evolution reaction(OER)in alkaline media.Specifically,the nitrogen-doped carbon nanofiber-supported Ni-doped CoP_(3) with rich P defects(Pv·)on the carbon cloth(p-NiCoP/NCFs@CC)is synthesized through a plasma-assisted phosphorization method.The p-NiCoP/NCFs@CC is an efficient and stable catalyst for the HER and the OER.It only needs overpotentials of 107 and 306 mV to drive 100 mA cm^(-2) for the HER and the OER,respectively.Its catalytic activities are higher than those of other catalysts reported recently.The high activities of the p-NiCoP/NCFs@CC mainly arise from its peculiar structural features.The density functional theory calculation indicates that the Pv·richness,the Ni doping,and the carbon supporting can optimize the adsorption of the H atoms at the catalyst surface and promote the strong electronic couplings between the carbon nanofiber-supported p-NiCoP with the surface oxide layer formed during the OER process.This gives the p-NiCoP/NCFs@CC with the high activities for the HER and the OER.When used in alkaline water electrolyzers,the p-NiCoP/NCFs@CC shows the superior activity and excellent stability for overall water splitting.展开更多
Rule-based portfolio construction strategies are rising as investmentdemand grows, and smart beta strategies are becoming a trend amonginstitutional investors. Smart beta strategies have high transparency, lowmanageme...Rule-based portfolio construction strategies are rising as investmentdemand grows, and smart beta strategies are becoming a trend amonginstitutional investors. Smart beta strategies have high transparency, lowmanagement costs, and better long-term performance, but are at the risk ofsevere short-term declines due to a lack of Risk Control tools. Although thereare some methods to use historical volatility for Risk Control, it is still difficultto adapt to the rapid switch of market styles. How to strengthen the RiskControl management of the portfolio while maintaining the original advantagesof smart beta has become a new issue of concern in the industry. Thispaper demonstrates the scientific validity of using a probability prediction forposition optimization through an optimization theory and proposes a novelnatural gradient boosting (NGBoost)-based portfolio optimization method,which predicts stock prices and their probability distributions based on non-Bayesian methods and maximizes the Sharpe ratio expectation of positionoptimization. This paper validates the effectiveness and practicality of themodel by using the Chinese stock market, and the experimental results showthat the proposed method in this paper can reduce the volatility by 0.08 andincrease the expected portfolio cumulative return (reaching a maximum of67.1%) compared with the mainstream methods in the industry.展开更多
基金supports from the Zhejiang Provincial Natural Science Foundation(No.LR22E070001)the National Natural Science Foundation of China(Nos.12275239 and 11975205)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2020B1515120048)the Fundamental Research Funds of Zhejiang Sci-Tech University(No.23062096-Y).
文摘This work reports the use of defect engineering and carbon supporting to achieve metal-doped phosphides with high activities and stabilities for the hydrogen evolution reaction(HER)and the oxygen evolution reaction(OER)in alkaline media.Specifically,the nitrogen-doped carbon nanofiber-supported Ni-doped CoP_(3) with rich P defects(Pv·)on the carbon cloth(p-NiCoP/NCFs@CC)is synthesized through a plasma-assisted phosphorization method.The p-NiCoP/NCFs@CC is an efficient and stable catalyst for the HER and the OER.It only needs overpotentials of 107 and 306 mV to drive 100 mA cm^(-2) for the HER and the OER,respectively.Its catalytic activities are higher than those of other catalysts reported recently.The high activities of the p-NiCoP/NCFs@CC mainly arise from its peculiar structural features.The density functional theory calculation indicates that the Pv·richness,the Ni doping,and the carbon supporting can optimize the adsorption of the H atoms at the catalyst surface and promote the strong electronic couplings between the carbon nanofiber-supported p-NiCoP with the surface oxide layer formed during the OER process.This gives the p-NiCoP/NCFs@CC with the high activities for the HER and the OER.When used in alkaline water electrolyzers,the p-NiCoP/NCFs@CC shows the superior activity and excellent stability for overall water splitting.
基金supported by the National Natural Science Foundation of China[Grant Number 61902349].
文摘Rule-based portfolio construction strategies are rising as investmentdemand grows, and smart beta strategies are becoming a trend amonginstitutional investors. Smart beta strategies have high transparency, lowmanagement costs, and better long-term performance, but are at the risk ofsevere short-term declines due to a lack of Risk Control tools. Although thereare some methods to use historical volatility for Risk Control, it is still difficultto adapt to the rapid switch of market styles. How to strengthen the RiskControl management of the portfolio while maintaining the original advantagesof smart beta has become a new issue of concern in the industry. Thispaper demonstrates the scientific validity of using a probability prediction forposition optimization through an optimization theory and proposes a novelnatural gradient boosting (NGBoost)-based portfolio optimization method,which predicts stock prices and their probability distributions based on non-Bayesian methods and maximizes the Sharpe ratio expectation of positionoptimization. This paper validates the effectiveness and practicality of themodel by using the Chinese stock market, and the experimental results showthat the proposed method in this paper can reduce the volatility by 0.08 andincrease the expected portfolio cumulative return (reaching a maximum of67.1%) compared with the mainstream methods in the industry.
