Magnesium alloys,known for their lightweight advantages,are increasingly in demand across a range of applications,from aerospace to the automotive industry.With rising requirements for strength and corrosion resistanc...Magnesium alloys,known for their lightweight advantages,are increasingly in demand across a range of applications,from aerospace to the automotive industry.With rising requirements for strength and corrosion resistance,the development of new magnesium alloy systems has become critical.Phase diagrams play a crucial role in guiding the magnesium alloy design by providing key insights into phase stability,composition,and temperature ranges,enabling the optimization of alloy properties and processing conditions.However,accessing and interpreting phase diagram data with thermodynamic calculation software can be complex and time-consuming,often requiring intricate calculations and iterative refinement based on thermodynamic models.To address this challenge,we introduce PDGPT,a ChatGPT-based large language model designed to streamline the acquisition of magnesium alloys Phase Diagram information with high efficiency and accuracy.Enhanced by promptengineering,supervised fine-tuning and retrieval-augmented generation,PDGPT leverages the predictive and reasoning capabilities of large language models along with computational phase diagram data.By combining large language models with traditional phase diagram research tools,PDGPT not only improves the accessibility of critical phase diagram information but also sets the stage for future advancements in applying large language models to materials science.展开更多
Chip-based optical microresonators with ultra-high Q-factors are becoming increasingly important to a variety of applications. However, the losses of on-chip microresonators with the highest Q-factor reported in the p...Chip-based optical microresonators with ultra-high Q-factors are becoming increasingly important to a variety of applications. However, the losses of on-chip microresonators with the highest Q-factor reported in the past are still far from their material absorption limits. Here, we demonstrate an on-chip silica microresonator that has approached the absorption limit of the state-of-the-art material on chip, realizing, to our knowledge, record intrinsic Q-factors exceeding 3 billion at both 1560 nm and 1064 nm. This fact is corroborated by photo-thermal spectroscopy measurements. Especially, compared with the standard optical fibers, its corresponding optical losses are only 38.4 times and 7.7 times higher at the wavelengths of 1560 nm and 1064 nm, respectively.To exhibit the performance of such fabricated microresonator, we achieve a record-low optical parametric oscillation threshold(31.9 μW) for millimeter-sized microresonators and generate a single-soliton microcomb with a record-low pump power of 220.2 μW for all soliton microcombs realized thus far.展开更多
Cities are complex systems that develop under complicated interactions among their human and environmental components.Urbanization generates substantial outcomes and opportunities while raising challenges including co...Cities are complex systems that develop under complicated interactions among their human and environmental components.Urbanization generates substantial outcomes and opportunities while raising challenges including congestion,air pollution,inequality,etc.,calling for efficient and reasonable solutions to sustainable developments.Fortunately,booming technologies generate large-scale data of complex cities,providing a chance to propose data-driven solutions for sustainable urban developments.This paper provides a comprehensive overview of data-driven urban sustainability practice.In this review article,we conceptualize MetaCity,a general framework for optimizing resource usage and allocation problems in complex cities with data-driven approaches.Under this framework,we decompose specific urban sustainable goals,e.g.,efficiency and resilience,review practical urban problems under these goals,and explore the probability of using data-driven technologies as potential solutions to the challenge of complexity.On the basis of extensive urban data,we integrate urban problem discovery,operation of urban systems simulation,and complex decision-making problem solving into an entire cohesive framework to achieve sustainable development goals by optimizing resource allocation problems in complex cities.展开更多
基金the financial support provided by the National Natural Science Foundation of China(Grant Nos.52425101,52401216,52471012)Hongbin Zhang acknowledges also the funding by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)-Project-ID 405553726-TRR 270.
文摘Magnesium alloys,known for their lightweight advantages,are increasingly in demand across a range of applications,from aerospace to the automotive industry.With rising requirements for strength and corrosion resistance,the development of new magnesium alloy systems has become critical.Phase diagrams play a crucial role in guiding the magnesium alloy design by providing key insights into phase stability,composition,and temperature ranges,enabling the optimization of alloy properties and processing conditions.However,accessing and interpreting phase diagram data with thermodynamic calculation software can be complex and time-consuming,often requiring intricate calculations and iterative refinement based on thermodynamic models.To address this challenge,we introduce PDGPT,a ChatGPT-based large language model designed to streamline the acquisition of magnesium alloys Phase Diagram information with high efficiency and accuracy.Enhanced by promptengineering,supervised fine-tuning and retrieval-augmented generation,PDGPT leverages the predictive and reasoning capabilities of large language models along with computational phase diagram data.By combining large language models with traditional phase diagram research tools,PDGPT not only improves the accessibility of critical phase diagram information but also sets the stage for future advancements in applying large language models to materials science.
基金National Key Research and Development Program of China (2023YFB3906401, 2021YFA1400803)National Natural Science Foundation of China (12341403,12293054, 92463304, 12341402)+2 种基金Fundamental Research Funds for the Central Universities (021314380260)Zhangjiang LaboratoryNatural Science Foundation of Jiangsu Province (BK20221440)。
文摘Chip-based optical microresonators with ultra-high Q-factors are becoming increasingly important to a variety of applications. However, the losses of on-chip microresonators with the highest Q-factor reported in the past are still far from their material absorption limits. Here, we demonstrate an on-chip silica microresonator that has approached the absorption limit of the state-of-the-art material on chip, realizing, to our knowledge, record intrinsic Q-factors exceeding 3 billion at both 1560 nm and 1064 nm. This fact is corroborated by photo-thermal spectroscopy measurements. Especially, compared with the standard optical fibers, its corresponding optical losses are only 38.4 times and 7.7 times higher at the wavelengths of 1560 nm and 1064 nm, respectively.To exhibit the performance of such fabricated microresonator, we achieve a record-low optical parametric oscillation threshold(31.9 μW) for millimeter-sized microresonators and generate a single-soliton microcomb with a record-low pump power of 220.2 μW for all soliton microcombs realized thus far.
基金supported by National Natural Science Foundation of China(U23B2030,62302261)the National Key Research and Development Program of China(23IAA02114).
文摘Cities are complex systems that develop under complicated interactions among their human and environmental components.Urbanization generates substantial outcomes and opportunities while raising challenges including congestion,air pollution,inequality,etc.,calling for efficient and reasonable solutions to sustainable developments.Fortunately,booming technologies generate large-scale data of complex cities,providing a chance to propose data-driven solutions for sustainable urban developments.This paper provides a comprehensive overview of data-driven urban sustainability practice.In this review article,we conceptualize MetaCity,a general framework for optimizing resource usage and allocation problems in complex cities with data-driven approaches.Under this framework,we decompose specific urban sustainable goals,e.g.,efficiency and resilience,review practical urban problems under these goals,and explore the probability of using data-driven technologies as potential solutions to the challenge of complexity.On the basis of extensive urban data,we integrate urban problem discovery,operation of urban systems simulation,and complex decision-making problem solving into an entire cohesive framework to achieve sustainable development goals by optimizing resource allocation problems in complex cities.
