Candidate antimagnetic rotational band in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mrow /><mml:mn>112</mml:mn></mml:msup></mml:math>In

(李晓伟), X. W. Li; Li, J.; Lu, Jing; Y., K.; Wu, Yong‐Shi; Zhu, Lei; He, C. Y.; Li, X. Q.; Zheng, Y.; Li, G. S.; Wu, Xiaofeng; J., Y.; Liu, Y. Z.

doi:10.1103/physrevc.86.057305

Cited by 41 publications

(27 citation statements)

References 28 publications

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“…The dataset used in this study was generated by Li et al [10]. Li et al conducted experiments via OPERA software, which was based on the FEM theory, to simulate the 3D distribution of the magnetic field near the centre of the superconducting solenoid surrounded with a cold iron yoke (see Fig.…”

Section: Datasetmentioning

confidence: 99%

“…1), and analyzed the influence of the structural parameters on the magnetic field (B o ) in the centre of the solenoid using a MNR (9): Fig. 1 Configuration of the superconducting solenoid surrounded with an iron yoke [10] This dataset is composed of four structural descriptors of the iron yoke, including its inner radius (r), cylindrical shell wall thickness (h 1 ), cylindrical shell end-cap thickness (h 2 ) and its hight (2H ), which were employed as the input variables. The central magnetic flux density (B o ) of the superconducting solenoid, determined by OPERA software, was acted as the output.…”

Section: Datasetmentioning

confidence: 99%

“…In light of Li et al's previous work [10], we proposed the SVR approach combined with PSO to regress and predict the B o in the centre of the superconducting solenoid in terms of the geometrical parameters of the assembled iron yoke via leave-one-out cross validation (LOOCV), and compared the result with that of the previous study in Ref. [10].…”

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confidence: 98%

“…Cobham CTS Ltd., 24 Bankside, Kidlington, Oxfordshire, OX5 1JE, UK. This software is based on the finite element method (FEM) to calculate the magnetic distribution) combined with multivariate nonlinear regression (MNR) to study the influence of the cold iron yoke geometry on the B o in the centre of the superconducting solenoid [10]. However, to our knowledge, research using the support vector regression (SVR) theory combined with particle swarm optimization (PSO) to model and predict the magnetic flux density in the centre of the superconducting solenoid surrounded with a cold iron yoke has not been reported previously.…”

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confidence: 99%

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Modeling and Predicting the Central Magnetic Flux Density of the Superconducting Solenoid Surrounded with Iron Yoke via SVR

Tang

Cai

Xiao

et al. 2012

J Supercond Nov Magn

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A novel machine learning method based on support vector regression (SVR) approach, combined with a particle swarm optimization (PSO) algorithm for its parameter optimization, was proposed to predict the magnetic field in the centre of a superconducting solenoid surrounded by a cold iron yoke in terms of the geometrical parameters of the yoke. The leave-one-out cross validation (LOOCV) test results of SVR reveal that the prediction ability of the SVR model is greater than that of the conventional multivariate nonlinear regression. The maximum absolute percentage error of 26 samples obtained by SVR did not exceed 0.50% and the statistical mean absolute percentage error was solely 0.05%, which was quite accurate and satisfactory with the requirement of ultraprecision engineering and manufacturing. This investigation provides a clue that the hybrid PSO-SVR approach elaborated in this paper is a promising and practical methodology to precisely design the physical dimension of the iron yoke surrounded around the superconducting solenoid.

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Section: Datasetmentioning

confidence: 99%

Section: Datasetmentioning

confidence: 99%

mentioning

confidence: 98%

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confidence: 99%

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Modeling and Predicting the Central Magnetic Flux Density of the Superconducting Solenoid Surrounded with Iron Yoke via SVR

Tang

Cai

Xiao

et al. 2012

J Supercond Nov Magn

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“…5,12) Mo can be separated from vanadium at pH 1.0 using EHEHPA and Mo in organic phase was completely stripped by the mixture of NH 4 OH and NH 4 Cl with excellent phase separation. 13) LIX 63 can extract simultaneously Mo and V from sulfuric acid solution containing Al, Co, Ni and Fe but in order to obtain purified products, the two metals loaded in organic must be separated. 14,15) The synergistic solvent extraction mixture of Cyanex 272 and TBP was found to be effective for the separation of Mo in the presence of V, Fe and As.…”

Section: Introductionmentioning

confidence: 99%

Separation of Mo from Chloride Leach Liquors of Petroleum Refining Catalysts by Ion Exchange

2013

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Separation of molybdenum from the synthetic chloride leach liquors of spent hydrodesulphurization catalysts was studied by employing cationic (Diphonix) and anionic resins (AG1-x8). The composition of the solution was Mo 394 ppm, Co 119 ppm and Al 1782 ppm. In the HCl concentration range from 1 to 6 kmol/m 3 , the loading of Co and Al was negligible. As the concentration of HCl increased, the loading percentage of Mo by AG1-x8 increased, while that by Diphonix decreased. The Mo in the loaded AG1-x8 was successfully eluted by using NaOH solution. In terms of the possibility of producing Mo compound from the eluant, AG1-x8 was found to be better than Diphonix. The loading capacity of AG1-x8 for molybdenum was determined. Column experiments verified that it was possible to separate Mo from Co and Al by ion exchange with AG1-x8.

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Modulating excited‐state intramolecular proton transfer of 2‐(5‐(4‐carboxyphenyl)‐2‐hydroxyphenyl)benzothiazole depending on substituents: A DFT/TD‐DFT study

Fang

2020

J of Physical Organic Chem

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The OH‐based excited‐state intramolecular proton transfer (ESIPT) of 2‐(5‐(4‐carboxyphenyl)‐2‐hydroxyphenyl)benzothiazole (CHBT) derivatives (4R‐CHBT) that were replaced by electron‐donating groups (CH3, OH) and electron‐withdrawing groups (COOH, CF3, CN) have been studied by the time‐dependent density functional theory (TD‐DFT) method. We analyzed structural parameters, infrared (IR) vibrational spectrum, frontier molecular orbitals (FMOs), and electronic spectra, which can describe the trend of ESIPT process. The constructed potential energy surfaces showed that the ESIPT potential energy barriers of 4R‐CHBT are in the range of 0.25 to 0.62 kcal/mol, which are just a little bigger than that value of CHBT. All the chosen substituents, no matter electron‐donating or electron‐withdrawing groups, make ESIPT processes slightly more difficult.

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Candidate antimagnetic rotational band in112In

Cited by 41 publications

References 28 publications

Modeling and Predicting the Central Magnetic Flux Density of the Superconducting Solenoid Surrounded with Iron Yoke via SVR

Modeling and Predicting the Central Magnetic Flux Density of the Superconducting Solenoid Surrounded with Iron Yoke via SVR

Separation of Mo from Chloride Leach Liquors of Petroleum Refining Catalysts by Ion Exchange

Modulating excited‐state intramolecular proton transfer of 2‐(5‐(4‐carboxyphenyl)‐2‐hydroxyphenyl)benzothiazole depending on substituents: A DFT/TD‐DFT study

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