Waterfront space is an important part of waterfront cities, and it carries the functions of ecological protection, tourism and urban landscape. As a city built on an island, Macao has abundant waterfront space. Howeve...Waterfront space is an important part of waterfront cities, and it carries the functions of ecological protection, tourism and urban landscape. As a city built on an island, Macao has abundant waterfront space. However, due to the geographical location, cultural and historical reasons, the waterfront space of Macao has a development gap in the use of urban waterfront space. The internal reasons for the differences in the waterfront space construction in which regions of the island are more perfect are the issues to be studied in this article. It is hoped that through the study of the current situation of Macao’s local waterfront space infrastructure construction, the main points that affect advanced cases will be sorted out. From the location, industry, and infrastructure, find out its enlightenment to other waterfront spaces in Macao that are relatively backward in construction.展开更多
Two-dimensional(2D)ferroelectrics with high Curie temperature(T_(c))exhibit stable ferroelectricity at the nanoscale and possess significant applications in the miniaturization of ferroelectric devices.However,control...Two-dimensional(2D)ferroelectrics with high Curie temperature(T_(c))exhibit stable ferroelectricity at the nanoscale and possess significant applications in the miniaturization of ferroelectric devices.However,controllable growth of wafer-scale 2D ferroelectric films with desired thickness is still rarely reported.In this study,we develop a two-step vapour deposition method to grow wafer-scale 2D CuCrS_(2)ferroelectric films with a uniform thickness from 2 to 10 nm.These films possess a non-centrosymmetric structure with a 3R stacking sequence,exhibit ferroelectric polarizations,and the Tc of CuCrS_(2)is higher than room temperature.The constructed electronic devices exhibit the characteristics of ferroelectric memristor,which opens up applications for ferroelectric functional devices.展开更多
In the present contribution,we demonstrate that the sluggish kinetics of oxygen evolution reaction(OER)over the bismuth sulfide(Bi_(2)S_(3))photoanode,which severely restricts its photoelectrochemical activity,is mark...In the present contribution,we demonstrate that the sluggish kinetics of oxygen evolution reaction(OER)over the bismuth sulfide(Bi_(2)S_(3))photoanode,which severely restricts its photoelectrochemical activity,is markedly accelerated by employing a sulfatecontaining electrolyte.First-principle calculation points to the spontaneous adsorption of sulfate(SO_(4)^(2−))on Bi_(2)S_(3)and its capacity of stabilizing the OER intermediates through hydrogen bonding,which is further reinforced by increasing the local density of states near the Fermi level of Bi_(2)S_(3).Meanwhile,the electron transfer is also promoted to synergistically render the ratedetermining step(from O*to OOH*)of OER over Bi_(2)S_(3)kinetically facile.Last but not least,benefitting from such enhanced OER activity and efficient charge separation resulted from depositing Bi_(2)S_(3)on the zinc oxide nanorods(ZnO NRs),forming a core–shell heterojunction,its photocurrent density achieves 8.61 mA·cm^(−2)at 1.23 VRHE,far surpassing those reported for additional Bi_(2)S_(3)-based and several state-of-the-art photoanodes in the literature and further exceeding their theoretical limit.The great promise of the Bi_(2)S_(3)/ZnO NRs is in view of such outperformance,the superior Faradaic yield of oxygen of more than~80%and the outstanding half-cell applied bias photon-to-current efficiency of~1%well corroborated.展开更多
Heavy metals(HMs)represent pervasive and highly toxic environmental pollutants,known for their long latency periods and high toxicity levels,which pose significant challenges for their removal and degradation.Therefor...Heavy metals(HMs)represent pervasive and highly toxic environmental pollutants,known for their long latency periods and high toxicity levels,which pose significant challenges for their removal and degradation.Therefore,the removal of heavy metals from the environment is crucial to ensure the water safety.Biochar materials,known for their intricate pore structures and abundant oxygen-containing functional groups,are frequently harnessed for their effectiveness in mitigating heavy metal contamination.However,conventional tests for optimizing biochar synthesis and assessing their heavy metal adsorption capabilities can be both costly and tedious.To address this challenge,this paper proposes a data-driven machine learning(ML)approach to identify the optimal biochar preparation and adsorption reaction conditions,with the ultimate goal of maximizing their adsorption capacity.By utilizing a data set comprising 476 instances of heavy metal absorption by biochar,seven classical integrated models and one stacking model were trained to rapidly predict the efficiency of heavy metal adsorption by biochar.These predictions were based on diverse physicochemical properties of biochar and the specific adsorption reaction conditions.The results demonstrate that the stacking model,which integrates multiple algorithms,allows for training with fewer samples to achieve higher prediction accuracy and improved generalization ability.展开更多
文摘Waterfront space is an important part of waterfront cities, and it carries the functions of ecological protection, tourism and urban landscape. As a city built on an island, Macao has abundant waterfront space. However, due to the geographical location, cultural and historical reasons, the waterfront space of Macao has a development gap in the use of urban waterfront space. The internal reasons for the differences in the waterfront space construction in which regions of the island are more perfect are the issues to be studied in this article. It is hoped that through the study of the current situation of Macao’s local waterfront space infrastructure construction, the main points that affect advanced cases will be sorted out. From the location, industry, and infrastructure, find out its enlightenment to other waterfront spaces in Macao that are relatively backward in construction.
基金the National Natural Science Foundation of China(52425203,52221001,62090035,12404216)the Natural Science Foundation of Jiangsu Province(BK20240008,BK20241252,BK20233001)+3 种基金the National Key R&D Program of China(2022YFA1204300)the Key Research and Development Plan of Hunan Province(2023GK2012)the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20231093)the Jiangsu Funding Program for Excellent Postdoctoral Talent(2023ZB553)。
文摘Two-dimensional(2D)ferroelectrics with high Curie temperature(T_(c))exhibit stable ferroelectricity at the nanoscale and possess significant applications in the miniaturization of ferroelectric devices.However,controllable growth of wafer-scale 2D ferroelectric films with desired thickness is still rarely reported.In this study,we develop a two-step vapour deposition method to grow wafer-scale 2D CuCrS_(2)ferroelectric films with a uniform thickness from 2 to 10 nm.These films possess a non-centrosymmetric structure with a 3R stacking sequence,exhibit ferroelectric polarizations,and the Tc of CuCrS_(2)is higher than room temperature.The constructed electronic devices exhibit the characteristics of ferroelectric memristor,which opens up applications for ferroelectric functional devices.
基金supported by the National Natural Science Foundation of China and Shanghai Jiao Tong University(Nos.22109096,WF220528005 and ZXDF280001/024).
文摘In the present contribution,we demonstrate that the sluggish kinetics of oxygen evolution reaction(OER)over the bismuth sulfide(Bi_(2)S_(3))photoanode,which severely restricts its photoelectrochemical activity,is markedly accelerated by employing a sulfatecontaining electrolyte.First-principle calculation points to the spontaneous adsorption of sulfate(SO_(4)^(2−))on Bi_(2)S_(3)and its capacity of stabilizing the OER intermediates through hydrogen bonding,which is further reinforced by increasing the local density of states near the Fermi level of Bi_(2)S_(3).Meanwhile,the electron transfer is also promoted to synergistically render the ratedetermining step(from O*to OOH*)of OER over Bi_(2)S_(3)kinetically facile.Last but not least,benefitting from such enhanced OER activity and efficient charge separation resulted from depositing Bi_(2)S_(3)on the zinc oxide nanorods(ZnO NRs),forming a core–shell heterojunction,its photocurrent density achieves 8.61 mA·cm^(−2)at 1.23 VRHE,far surpassing those reported for additional Bi_(2)S_(3)-based and several state-of-the-art photoanodes in the literature and further exceeding their theoretical limit.The great promise of the Bi_(2)S_(3)/ZnO NRs is in view of such outperformance,the superior Faradaic yield of oxygen of more than~80%and the outstanding half-cell applied bias photon-to-current efficiency of~1%well corroborated.
基金financially supported by the National Key Research and Development Program of China(No.2021YFC1808902)the National Natural Science Foundation of China(No.42307546)+1 种基金the Key Research and Development Program of Shaanxi Province(China)(Nos.2019NY200,2020ZDLNY06-06,and 2020ZDLNY07-10)the Agricultural Technology Innovation Driven Program of Shaanxi Province(China)(No.NYKJ-2022-XA-02).
文摘Heavy metals(HMs)represent pervasive and highly toxic environmental pollutants,known for their long latency periods and high toxicity levels,which pose significant challenges for their removal and degradation.Therefore,the removal of heavy metals from the environment is crucial to ensure the water safety.Biochar materials,known for their intricate pore structures and abundant oxygen-containing functional groups,are frequently harnessed for their effectiveness in mitigating heavy metal contamination.However,conventional tests for optimizing biochar synthesis and assessing their heavy metal adsorption capabilities can be both costly and tedious.To address this challenge,this paper proposes a data-driven machine learning(ML)approach to identify the optimal biochar preparation and adsorption reaction conditions,with the ultimate goal of maximizing their adsorption capacity.By utilizing a data set comprising 476 instances of heavy metal absorption by biochar,seven classical integrated models and one stacking model were trained to rapidly predict the efficiency of heavy metal adsorption by biochar.These predictions were based on diverse physicochemical properties of biochar and the specific adsorption reaction conditions.The results demonstrate that the stacking model,which integrates multiple algorithms,allows for training with fewer samples to achieve higher prediction accuracy and improved generalization ability.
