We report on a novel and convenient method of measuring secondary electron spectra for insulators in a secondary electron yield measurement system with a planar grid analyzer configuration and a metal mesh probe. In t...We report on a novel and convenient method of measuring secondary electron spectra for insulators in a secondary electron yield measurement system with a planar grid analyzer configuration and a metal mesh probe. In this measurement, the planar grid is negatively biased to force some emitted secondary electrons to return to the sample surface and to neutralize charges accumulated on the sample during the previous beam irradiation. The surface potential of the sample is then measured by use of a metal mesh probe. The grid bias for neutralization corresponding to the zero surface potential is determined based on the linear relationship between the surface potential and the grid bias. Once the surface potential equals zero, the secondary electron spectra of polymethyl methacrylate（PMMA） are studied experimentally by measuring the -curve and then fitting it to Everhart＇s formula. The measurement results show that the peak energy and the full width at half maximum of the spectra are 4.26 eV and 14.06 eV, respectively.展开更多
Low-density non-local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics.Understanding the X-ray spectrum and the atomic kinetics of such plasmas...Low-density non-local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics.Understanding the X-ray spectrum and the atomic kinetics of such plasmas is therefore of great importance.However,the creation of uniform-density nonequilibrium plasmas in intense radiation fields in the laboratory and the measurement of their spectra with high resolution are challenging tasks.Here,we present a new method to produce such a uniform aluminum plasma and explore photon-induced kinetics and relevant atomic physics by measuring its spectrum.It is observed that in the presence of an external radiation field,the satellites q,r and a-d of the He-resonance line are greatly enhanced compared with the satellites j,k,l.Analysis of atomic kinetics reveals that this effect of intense radiation is due to competition between the photoexcitation and autoionization processes.With this effect taken into account,simulated spectra are able to reproduce the measured spectra quite well.展开更多
Accurate monitoring of atmospheric carbon dioxide(CO_(2))is crucial for understanding the global carbon cycle and informing climate policy.Satellite-based remote sensing provides a promising means to obtain global mea...Accurate monitoring of atmospheric carbon dioxide(CO_(2))is crucial for understanding the global carbon cycle and informing climate policy.Satellite-based remote sensing provides a promising means to obtain global measurements of the column-averaged CO_(2) dry air mole fraction(XCO_(2)).However,traditional retrieval algorithms are computationally intensive due to their reliance on iterative radiative transfer simulations.In this study,we introduce the Spectrum Transformer(SpT),a novel neural network model that employs a Transformer-based architecture to enable fast and accurate XCO_(2) retrievals directly from satellite-measured spectra.Unlike previous machine learning approaches,the SpT model effectively handles data drift caused by increasing atmospheric CO_(2) levels without requiring synthetic future data or additional assumptions.Trained exclusively on historical OCO-2 spectra and retrievals from 2017 to 2019,the SpT model demonstrates unbiased generalization to data from 2020 to 2022,achieving high accuracy(root mean square error[RMSE]∼1.5 parts per million[ppm])in“future”retrievals.Through periodic fine-tuning with minimal new data(<10%of all available data),the model maintains even higher accuracy(RMSE∼1.2 ppm),demonstrating its applicability for ongoing missions up to the most recent measurements(2024 April 1).The SpT model reduces computational time from minutes to milliseconds per retrieval,offering an important advancement over traditional methods.Validation against TCCON ground-based measurements confirms the model’s ability to capture seasonal and regional variations in XCO_(2),highlighting its potential for real-time global CO_(2) monitoring.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos U1537210 and 11375139the National Key Laboratory of Space Microwave Technology China under Grant No 9140C530101130C53013
文摘We report on a novel and convenient method of measuring secondary electron spectra for insulators in a secondary electron yield measurement system with a planar grid analyzer configuration and a metal mesh probe. In this measurement, the planar grid is negatively biased to force some emitted secondary electrons to return to the sample surface and to neutralize charges accumulated on the sample during the previous beam irradiation. The surface potential of the sample is then measured by use of a metal mesh probe. The grid bias for neutralization corresponding to the zero surface potential is determined based on the linear relationship between the surface potential and the grid bias. Once the surface potential equals zero, the secondary electron spectra of polymethyl methacrylate（PMMA） are studied experimentally by measuring the -curve and then fitting it to Everhart＇s formula. The measurement results show that the peak energy and the full width at half maximum of the spectra are 4.26 eV and 14.06 eV, respectively.
基金supported by Science Challenge Project Nos.TZ2025013,TZ2018005,and TZ2018001the National Nature Science Foundation(NSFC)of China under Grant Nos.12335015,12375238,and 12374261National Safety Academic Fund(NSAF)Grant No.U2430206.
文摘Low-density non-local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics.Understanding the X-ray spectrum and the atomic kinetics of such plasmas is therefore of great importance.However,the creation of uniform-density nonequilibrium plasmas in intense radiation fields in the laboratory and the measurement of their spectra with high resolution are challenging tasks.Here,we present a new method to produce such a uniform aluminum plasma and explore photon-induced kinetics and relevant atomic physics by measuring its spectrum.It is observed that in the presence of an external radiation field,the satellites q,r and a-d of the He-resonance line are greatly enhanced compared with the satellites j,k,l.Analysis of atomic kinetics reveals that this effect of intense radiation is due to competition between the photoexcitation and autoionization processes.With this effect taken into account,simulated spectra are able to reproduce the measured spectra quite well.
基金supported by the National Natural Science Foundation of China(grants nos.52276077 and 52120105009).
文摘Accurate monitoring of atmospheric carbon dioxide(CO_(2))is crucial for understanding the global carbon cycle and informing climate policy.Satellite-based remote sensing provides a promising means to obtain global measurements of the column-averaged CO_(2) dry air mole fraction(XCO_(2)).However,traditional retrieval algorithms are computationally intensive due to their reliance on iterative radiative transfer simulations.In this study,we introduce the Spectrum Transformer(SpT),a novel neural network model that employs a Transformer-based architecture to enable fast and accurate XCO_(2) retrievals directly from satellite-measured spectra.Unlike previous machine learning approaches,the SpT model effectively handles data drift caused by increasing atmospheric CO_(2) levels without requiring synthetic future data or additional assumptions.Trained exclusively on historical OCO-2 spectra and retrievals from 2017 to 2019,the SpT model demonstrates unbiased generalization to data from 2020 to 2022,achieving high accuracy(root mean square error[RMSE]∼1.5 parts per million[ppm])in“future”retrievals.Through periodic fine-tuning with minimal new data(<10%of all available data),the model maintains even higher accuracy(RMSE∼1.2 ppm),demonstrating its applicability for ongoing missions up to the most recent measurements(2024 April 1).The SpT model reduces computational time from minutes to milliseconds per retrieval,offering an important advancement over traditional methods.Validation against TCCON ground-based measurements confirms the model’s ability to capture seasonal and regional variations in XCO_(2),highlighting its potential for real-time global CO_(2) monitoring.
