3-dB couplers are key building blocks for on-chip optical switches,optical phased arrays,and photonic computing applications,for the ease of realizing balanced beam splitting and combining.Adiabatic3-dB couplers ensur...3-dB couplers are key building blocks for on-chip optical switches,optical phased arrays,and photonic computing applications,for the ease of realizing balanced beam splitting and combining.Adiabatic3-dB couplers ensure exclusive excitation and propagation of the fundamental eigenmode along the waveguide,characterized by low insertion loss,broad bandwidth,low power imbalance,and resilience to fabrication variations.However,conventional adiabatic designs need to extend the propagation length to achieve broadband performance.In this paper,we overcome such a length-bandwidth trade-off by employing fast quasi-adiabatic(FAQUAD)dynamics in the TFLN 3-dB couplers,thereby accelerating the mode evolution process.Theoretical analysis predicts that the proposed 2×2 FAQUAD 3-dB coupler exhibits an unprecedented operation bandwidth of 350 nm(1285 to 1635 nm)with a FAQUAD taper length of only 88.9μm.Experimental characterization of the fabricated device demonstrates broadband 3-dB power splitting over 165 nm(exceeding the range of the used tunable laser:1470 to 1635 nm),achieving the power imbalance of<0.5 dB and insertion loss of 0.14 dB.Those results establish the foundation for next-generation photonic integrated circuits featuring high efficiency,compact footprint,and ultra-wide bandwidth.展开更多
The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring suffi...The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring sufficient count accumulation for evaluation,thereby limiting response time.The sequential Bayesian approach,which utilizes prior information and considers both photon energies and interarrival times,can significantly enhance the performance of radionuclides identification.This study proposes a theoretical optimization method for the traditional sequential Bayesian approach.Each photon is processed sequentially,and the corresponding posterior probability is updated in real time using a noninformative prior from the Bayesian theory.By comparing the posterior probabilities of the background and radionuclides based on the energy variance and time interval,the type of γ-rays can be identified(background characteristic γ-rays,Compton plateaus γ-rays,or radionuclide-specific characteristic γ-rays).By integrating the information from these multiple characteristic γ-rays,the presence and type of radionuclides were determined based on the final decision function and a set threshold.Based on theoretical research,verification experiments were conducted using a LaBr_(3)(Ce)detector in both low-and natural background radiation environments with typical radionuclides(^(137)Cs,^(60)Co,and ^(133)Ba).The results show that this approach can identify ^(137)Cs in 7.9 s and 8.5 s(source dose rate contribution:approximately 6.5×10^(−3)μGy/h),^(60)Co in 8.1 s and 9.8 s(approximately 4.8×10^(−2)μGy/h),and ^(133)Ba in 4.05 s and 5.99 s(approximately 3.4×10^(−2)μGy/h)under low and natural background radiation,respectively,with a miss rate below 0.01%.This demonstrates the effectiveness of the proposed approach for fast radionuclides identification,even at low activity levels and highlights its potential for enhancing public safety in diverse radiation environments.展开更多
To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate elect...To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).展开更多
Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NM...Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NMR spectroscopy.This problem,to some extent,limits broader applications of NMR techniques.Various methods have been proposed to accelerate sampling,including non-uniform sampling(NUS),multi-FID acquisition(MFA),Hadamard encoding,Fourier encoding,spatial encoding Ultrafast 2D NMR(UF2DNMR),and so on.The review focuses on rapid sampling methods developed in contemporary China,introducing their fundamental principles and applications while discussing their respective advantages and disadvantages.展开更多
The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculati...The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.展开更多
Owing to a lack of gaugemeter and the variety of steel grades and standards in some plate mills, the longand short-term self-learning models of rolling force based on gauge soft-measuring with high precision were brou...Owing to a lack of gaugemeter and the variety of steel grades and standards in some plate mills, the longand short-term self-learning models of rolling force based on gauge soft-measuring with high precision were brought up. The soft-measuring method and target value locked method were used in these models to confirm the actual exit gauge of passes, and thick layer division and exponential smoothing method were used to dispose the deformation resistance parameter, which could be calculated from the actual data of the rolling process. The correlative mathematical methods can also be adapted to self-learning with gaugemeter. The models were applied to the process control system of AGC （automatic gauge control） reconstruction on 2800 mm finishing mill of Anyang steel and favorable effect was obtained.展开更多
On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enha...On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.展开更多
In machine learning,positive-unlabelled(PU)learning is a special case within semi-supervised learning.In positiveunlabelled learning,the training set contains some positive examples and a set of unlabelled examples fr...In machine learning,positive-unlabelled(PU)learning is a special case within semi-supervised learning.In positiveunlabelled learning,the training set contains some positive examples and a set of unlabelled examples from both the positive and negative classes.Positive-unlabelled learning has gained attention in many domains,especially in time-series data,in which the obtainment of labelled data is challenging.Examples which originate from the negative class are especially difficult to acquire.Self-learning is a semi-supervised method capable of PU learning in time-series data.In the self-learning approach,observations are individually added from the unlabelled data into the positive class until a stopping criterion is reached.The model is retrained after each addition with the existent labels.The main problem in self-learning is to know when to stop the learning.There are multiple,different stopping criteria in the literature,but they tend to be inaccurate or challenging to apply.This publication proposes a novel stopping criterion,which is called Peak evaluation using perceptually important points,to address this problem for time-series data.Peak evaluation using perceptually important points is exceptional,as it does not have tunable hyperparameters,which makes it easily applicable to an unsupervised setting.Simultaneously,it is flexible as it does not make any assumptions on the balance of the dataset between the positive and the negative class.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB2807903)the National Natural Science Foundation of China(Grant Nos.62025502 and 62475050)the Guangdong Introducing Innovative and Entrepreneurial Teams of“The Pearl River Talent Recruitment Program”(Grant No.2021ZT09X044)。
文摘3-dB couplers are key building blocks for on-chip optical switches,optical phased arrays,and photonic computing applications,for the ease of realizing balanced beam splitting and combining.Adiabatic3-dB couplers ensure exclusive excitation and propagation of the fundamental eigenmode along the waveguide,characterized by low insertion loss,broad bandwidth,low power imbalance,and resilience to fabrication variations.However,conventional adiabatic designs need to extend the propagation length to achieve broadband performance.In this paper,we overcome such a length-bandwidth trade-off by employing fast quasi-adiabatic(FAQUAD)dynamics in the TFLN 3-dB couplers,thereby accelerating the mode evolution process.Theoretical analysis predicts that the proposed 2×2 FAQUAD 3-dB coupler exhibits an unprecedented operation bandwidth of 350 nm(1285 to 1635 nm)with a FAQUAD taper length of only 88.9μm.Experimental characterization of the fabricated device demonstrates broadband 3-dB power splitting over 165 nm(exceeding the range of the used tunable laser:1470 to 1635 nm),achieving the power imbalance of<0.5 dB and insertion loss of 0.14 dB.Those results establish the foundation for next-generation photonic integrated circuits featuring high efficiency,compact footprint,and ultra-wide bandwidth.
基金supported by the Program for NIM-Basic Research Business Expenses Key Field Program,China(No.AKYCX2315).
文摘The rapid identification of γ-emitting radionuclides with low activity levels in public areas is crucial for nuclear safety.However,classical methods rely on full-energy peaks in the integral spectrum,requiring sufficient count accumulation for evaluation,thereby limiting response time.The sequential Bayesian approach,which utilizes prior information and considers both photon energies and interarrival times,can significantly enhance the performance of radionuclides identification.This study proposes a theoretical optimization method for the traditional sequential Bayesian approach.Each photon is processed sequentially,and the corresponding posterior probability is updated in real time using a noninformative prior from the Bayesian theory.By comparing the posterior probabilities of the background and radionuclides based on the energy variance and time interval,the type of γ-rays can be identified(background characteristic γ-rays,Compton plateaus γ-rays,or radionuclide-specific characteristic γ-rays).By integrating the information from these multiple characteristic γ-rays,the presence and type of radionuclides were determined based on the final decision function and a set threshold.Based on theoretical research,verification experiments were conducted using a LaBr_(3)(Ce)detector in both low-and natural background radiation environments with typical radionuclides(^(137)Cs,^(60)Co,and ^(133)Ba).The results show that this approach can identify ^(137)Cs in 7.9 s and 8.5 s(source dose rate contribution:approximately 6.5×10^(−3)μGy/h),^(60)Co in 8.1 s and 9.8 s(approximately 4.8×10^(−2)μGy/h),and ^(133)Ba in 4.05 s and 5.99 s(approximately 3.4×10^(−2)μGy/h)under low and natural background radiation,respectively,with a miss rate below 0.01%.This demonstrates the effectiveness of the proposed approach for fast radionuclides identification,even at low activity levels and highlights its potential for enhancing public safety in diverse radiation environments.
基金financially supported by the National Natural Science Foundation of China (Grant No. 52372191)the National Natural Science Foundation of China (Grant No. 22271106)+2 种基金the National Science Foundation of China (Grant Nos. 52073286 (C.-Z.L.), 22275185 (C.-Z.L.))the Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ115 (C.-Z.L.)the XMIREM Autonomously Deployment Project (2023GG01 (C.-Z.L.))
文摘To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).
基金financially supported by the National Natural Science Foundation of China(grant numbers 22174118,12411530077,and 22374124).
文摘Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NMR spectroscopy.This problem,to some extent,limits broader applications of NMR techniques.Various methods have been proposed to accelerate sampling,including non-uniform sampling(NUS),multi-FID acquisition(MFA),Hadamard encoding,Fourier encoding,spatial encoding Ultrafast 2D NMR(UF2DNMR),and so on.The review focuses on rapid sampling methods developed in contemporary China,introducing their fundamental principles and applications while discussing their respective advantages and disadvantages.
基金Item Sponsored by National Natural Science Foundation of China(50474016)
文摘The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.
基金Item Sponsored by National Natural Science Foundation of China (50604006)
文摘Owing to a lack of gaugemeter and the variety of steel grades and standards in some plate mills, the longand short-term self-learning models of rolling force based on gauge soft-measuring with high precision were brought up. The soft-measuring method and target value locked method were used in these models to confirm the actual exit gauge of passes, and thick layer division and exponential smoothing method were used to dispose the deformation resistance parameter, which could be calculated from the actual data of the rolling process. The correlative mathematical methods can also be adapted to self-learning with gaugemeter. The models were applied to the process control system of AGC （automatic gauge control） reconstruction on 2800 mm finishing mill of Anyang steel and favorable effect was obtained.
基金Item Sponsored by National Natural Science Foundation of China (50527402)
文摘On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.
文摘In machine learning,positive-unlabelled(PU)learning is a special case within semi-supervised learning.In positiveunlabelled learning,the training set contains some positive examples and a set of unlabelled examples from both the positive and negative classes.Positive-unlabelled learning has gained attention in many domains,especially in time-series data,in which the obtainment of labelled data is challenging.Examples which originate from the negative class are especially difficult to acquire.Self-learning is a semi-supervised method capable of PU learning in time-series data.In the self-learning approach,observations are individually added from the unlabelled data into the positive class until a stopping criterion is reached.The model is retrained after each addition with the existent labels.The main problem in self-learning is to know when to stop the learning.There are multiple,different stopping criteria in the literature,but they tend to be inaccurate or challenging to apply.This publication proposes a novel stopping criterion,which is called Peak evaluation using perceptually important points,to address this problem for time-series data.Peak evaluation using perceptually important points is exceptional,as it does not have tunable hyperparameters,which makes it easily applicable to an unsupervised setting.Simultaneously,it is flexible as it does not make any assumptions on the balance of the dataset between the positive and the negative class.
基金the National Natural Science Foundation of China(No.61375086)the Key Project of Science and Technique Plan of Beijing Municipal Commission of Education(No.KZ201210005001)+1 种基金the National Basic Research Program(973)of China(No.2012CB720000)the China Scholarship Council Program(No.201406540017)
