Silicon isotope analysis traditionally uses a standard-sample bracketing （SSB） method that relies upon greater instrument stability than can be consistently expected. The following proposed method reduces the level ...Silicon isotope analysis traditionally uses a standard-sample bracketing （SSB） method that relies upon greater instrument stability than can be consistently expected. The following proposed method reduces the level of instrumental stability required for the analysis process and provides a valid solution for high-precision and accurate studies of Si isotopic compositions. Rock samples were dissolved by using alkali fusion and acidification. Silicon isotopes were purified with an ion exchange resin. Interfering peaks for isotopes were separated by using a Nu Plasma 1700 multi-collector inductively coupled plasma mass spectrometry （MS） system in high-resolution mode （M/AM 〉 8000 RP）. Two magnesium isotopes （25Mg and 26Mg） and three silicon isotopes （28Si, 29Si, and 3;Si） were analyzed in the same data collection cycle. Mg isotopes were used as an internal standard to calibrate the mass discrimination effects in MS analysis of Si isotopes in combination with the SSB method in order to reduce the effects of MS interference and instrumental mass dis- crimination on the accuracy of measurements. The conventional SSB method without the Mg internal standard and the proposed SSB method with Mg calibration delivered consistent results within two standard deviations. When Mg was used as an internal standard for calibration, the analysis precision was better than 0.05 %0 amu.展开更多
The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,...The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions.Then,the optimization modeling with respect to the array error matrix(defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix)was constructed.Two preferable algorithms(called algorithm I and algorithm II)were developed to minimize the cost function.In algorithm I,the array error matrix was regarded as a whole parameter to be estimated,and the exact solution was available.Compared to some existing algorithms with the similar computation framework,algorithm I can make full use of the potentially linear characteristics of URA's error matrix,thus,the calibration precision was obviously enhanced.In algorithm II,the array error matrix was decomposed into two matrix parameters to be optimized.Compared to algorithm I,it can further decrease the number of unknowns and,thereby,yield better estimation accuracy.However,algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable.Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.展开更多
基金funded by the National Natural Science Foundation of China(Grant Nos.41427804,41421002,41373004)Beijing SHRIMP Center Open Foundation,and Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT1281)the MOST Research Foundation from the State Key Laboratory of Continental Dynamics(BJ08132-1)
文摘Silicon isotope analysis traditionally uses a standard-sample bracketing （SSB） method that relies upon greater instrument stability than can be consistently expected. The following proposed method reduces the level of instrumental stability required for the analysis process and provides a valid solution for high-precision and accurate studies of Si isotopic compositions. Rock samples were dissolved by using alkali fusion and acidification. Silicon isotopes were purified with an ion exchange resin. Interfering peaks for isotopes were separated by using a Nu Plasma 1700 multi-collector inductively coupled plasma mass spectrometry （MS） system in high-resolution mode （M/AM 〉 8000 RP）. Two magnesium isotopes （25Mg and 26Mg） and three silicon isotopes （28Si, 29Si, and 3;Si） were analyzed in the same data collection cycle. Mg isotopes were used as an internal standard to calibrate the mass discrimination effects in MS analysis of Si isotopes in combination with the SSB method in order to reduce the effects of MS interference and instrumental mass dis- crimination on the accuracy of measurements. The conventional SSB method without the Mg internal standard and the proposed SSB method with Mg calibration delivered consistent results within two standard deviations. When Mg was used as an internal standard for calibration, the analysis precision was better than 0.05 %0 amu.
基金Project(61201381)supported by the National Natural Science Foundation of ChinaProject(YP12JJ202057)supported by the Future Development Foundation of Zhengzhou Information Science and Technology College,China
文摘The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions.Then,the optimization modeling with respect to the array error matrix(defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix)was constructed.Two preferable algorithms(called algorithm I and algorithm II)were developed to minimize the cost function.In algorithm I,the array error matrix was regarded as a whole parameter to be estimated,and the exact solution was available.Compared to some existing algorithms with the similar computation framework,algorithm I can make full use of the potentially linear characteristics of URA's error matrix,thus,the calibration precision was obviously enhanced.In algorithm II,the array error matrix was decomposed into two matrix parameters to be optimized.Compared to algorithm I,it can further decrease the number of unknowns and,thereby,yield better estimation accuracy.However,algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable.Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.
