A modified Miedema model using four atomic parameters and pattern recognition or artificial neural network has been used to study the factors that affect the entropy of mixing of liquid binary alloy systems. It has be...A modified Miedema model using four atomic parameters and pattern recognition or artificial neural network has been used to study the factors that affect the entropy of mixing of liquid binary alloy systems. It has been found that the systems with larger electronegativity difference (△Φ) usuallg have negative △Sxs of mixing, while the systems with larger valence electron density difference(denoted by △n) and small △Φ usually have positive △Sxs of mixing. The artificial neural network-atomic parameter method can be used to predict the △Sxs of binary alloy systems consisting of non-transition elements.展开更多
To investigate the nature of the Ψ（3770） resonance and to measure the cross section for e^＋e^-→DD, a cross-section scan data sample, distributed among 41 center-of-mass energy points from 3.73 to 3.89 GeV, was ta...To investigate the nature of the Ψ（3770） resonance and to measure the cross section for e^＋e^-→DD, a cross-section scan data sample, distributed among 41 center-of-mass energy points from 3.73 to 3.89 GeV, was taken with the BESIII detector operated at the BEPCII collider in the year 2010. By analyzing the large angle Bhabha scattering events, we measure the integrated luminosity of the data sample at each center-of-mass energy point. The total integrated luminosity of the data sample is 76.16±0.04±0.61 pb^-1, where the first uncertainty is statistical and the second systematic.展开更多
文摘A modified Miedema model using four atomic parameters and pattern recognition or artificial neural network has been used to study the factors that affect the entropy of mixing of liquid binary alloy systems. It has been found that the systems with larger electronegativity difference (△Φ) usuallg have negative △Sxs of mixing, while the systems with larger valence electron density difference(denoted by △n) and small △Φ usually have positive △Sxs of mixing. The artificial neural network-atomic parameter method can be used to predict the △Sxs of binary alloy systems consisting of non-transition elements.
基金Supported by National Key Basic Research Program of China(2015CB856700)National Natural Science Foundation of China(NSFC)(11235011,11335008,11425524,11625523,11635010)+13 种基金the Chinese Academy of Sciences(CAS)Large-Scale Scientific Facility Programthe CAS Center for Excellence in Particle Physics(CCEPP)Joint Large-Scale Scientific Facility Funds of the NSFCCAS(U1332201,U1532257,U1532258)CAS Key Research Program of Frontier Sciences(QYZDJ-SSW-SLH003,QYZDJ-SSW-SLH040)100 Talents Program of CASNational 1000 Talents Program of China,INPACShanghai Key Laboratory for Particle Physics and Cosmology,German Research Foundation DFG under Contracts Nos.Collaborative Research Center CRC 1044,FOR 2359Istituto Nazionale di Fisica Nucleare,Italy,Koninklijke Nederlandse Akademie van Wetenschappen(KNAW)(530-4CDP03)Ministry of Development of Turkey(DPT2006K-120470)National Science and Technology fundThe Swedish Research Council,U.S.Department of Energy(DEFG02-05ER41374,DE-SC-0010118,DE-SC-0010504,DE-SC-0012069)University of Groningen(RuG)and the Helmholtzzentrum fuer Schwerionenforschung GmbH(GSI)Darmstadt,WCU Program of National Research Foundation of Korea(R32-2008-000-10155-0)
文摘To investigate the nature of the Ψ（3770） resonance and to measure the cross section for e^＋e^-→DD, a cross-section scan data sample, distributed among 41 center-of-mass energy points from 3.73 to 3.89 GeV, was taken with the BESIII detector operated at the BEPCII collider in the year 2010. By analyzing the large angle Bhabha scattering events, we measure the integrated luminosity of the data sample at each center-of-mass energy point. The total integrated luminosity of the data sample is 76.16±0.04±0.61 pb^-1, where the first uncertainty is statistical and the second systematic.
