Magnetocaloric performance is of vital importance for Mn-Fe-P-Si alloys.However,when processes and compositions are considered,designing alloys with large magnetic entropy changes(ΔS_(m)),low thermal hysteresis(ΔT_(...Magnetocaloric performance is of vital importance for Mn-Fe-P-Si alloys.However,when processes and compositions are considered,designing alloys with large magnetic entropy changes(ΔS_(m)),low thermal hysteresis(ΔT_(hys)),and Curie temperatures(T_(C))around room temperature become relatively complicated.In this study,we adopt machine learning methods to predict the magnetocaloric performance of Mn-Fe-P-Si compounds for the first time.To achieve this goal,503,465,and 660 data points for datasets with T_(C),ΔT_(hys),andΔS_(m)are collected,respectively.The collected datasets contain parameters of compositions,preparations,heat treatment,and magnetic field changes.We search for the optimal configuration using various methods and also compare their mean squared errors(MSE)and allowable errors.Evaluation results show that the performance of neural networks(NNs)is better than other methods.Therefore,we select NN to explore the T_(C),ΔT_(hys),andΔS_(m)values as a function of Mn,Si,metal/non-metal ratios,and B(Boron).We also propose to use the composition window with excellent magnetocaloric performance.These results not only help us gain deep insights into Mn-Fe-P-Si alloys but also accelerate the design process of alloys suitable for magnetocaloric materials.This work has the potential to solve the challenges and boost the research of Mn-Fe-P-Si alloys.展开更多
Q&P钢的连续退火工艺是一种广泛采用的热处理办法,本文从热力学的角度讨论了连续退火工艺均热过程数种Q&P钢奥氏体化的程度。重新计算了Fe-Si-Mn-C四元系固溶相BCC_A2和FCC_A1的热力学性质。结合连续退火工艺均热段的快速加热,...Q&P钢的连续退火工艺是一种广泛采用的热处理办法,本文从热力学的角度讨论了连续退火工艺均热过程数种Q&P钢奥氏体化的程度。重新计算了Fe-Si-Mn-C四元系固溶相BCC_A2和FCC_A1的热力学性质。结合连续退火工艺均热段的快速加热,短时保温,快速冷却的热处理工艺特点,按照PLE(Partition local equilibrium)和NPLE(Negligible partition local equilibrium)局部平衡计算了当前几种Q&P钢成分的FCC相线和奥氏体体积分数,并根据试验观测结果,提出了一种符合连续退火生产Q&P钢实际需求的准平衡相图计算方法:“准PLE”(Quasi-partition local equilibrium)计算方法,实际观测结果与理论预测结果符合较好。展开更多
（MnFe）2（P, Si）-type compounds are, to date, one of the best candidates for magnetic refrigeration and energy conversion applications due to the combination of giant magnetocaloric effect （MCE）, tunable working t...（MnFe）2（P, Si）-type compounds are, to date, one of the best candidates for magnetic refrigeration and energy conversion applications due to the combination of giant magnetocaloric effect （MCE）, tunable working temperature range and low material cost. The giant MCE in the （Mn, Fe）2（P, Si）-type compounds originates from strong mag- netoelastic coupling, where the lattice degrees of freedom and spin degrees of freedom are efficiently coupled. The tunability of the phase transition, in terms of the critical temperature and the character of the phase transition, is essentially attributed to the changes in the magnetoelastic coupling in the （Mn, Fe）2（P, Si）-type compounds. In this review, not only the fundamentals of the magnetoelastic coupling but also the related practical aspects such as magnetocaloric performance, hysteresis issue and mechanical stability are discussed for the （Mn, Fe）2（P, Si）- type compounds. Additionally, some future fundamental studies on the MCE as well as possible ways of solving the hysteresis and fracture issues are proposed.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.52074182 and 51821001)。
文摘Magnetocaloric performance is of vital importance for Mn-Fe-P-Si alloys.However,when processes and compositions are considered,designing alloys with large magnetic entropy changes(ΔS_(m)),low thermal hysteresis(ΔT_(hys)),and Curie temperatures(T_(C))around room temperature become relatively complicated.In this study,we adopt machine learning methods to predict the magnetocaloric performance of Mn-Fe-P-Si compounds for the first time.To achieve this goal,503,465,and 660 data points for datasets with T_(C),ΔT_(hys),andΔS_(m)are collected,respectively.The collected datasets contain parameters of compositions,preparations,heat treatment,and magnetic field changes.We search for the optimal configuration using various methods and also compare their mean squared errors(MSE)and allowable errors.Evaluation results show that the performance of neural networks(NNs)is better than other methods.Therefore,we select NN to explore the T_(C),ΔT_(hys),andΔS_(m)values as a function of Mn,Si,metal/non-metal ratios,and B(Boron).We also propose to use the composition window with excellent magnetocaloric performance.These results not only help us gain deep insights into Mn-Fe-P-Si alloys but also accelerate the design process of alloys suitable for magnetocaloric materials.This work has the potential to solve the challenges and boost the research of Mn-Fe-P-Si alloys.
文摘Q&P钢的连续退火工艺是一种广泛采用的热处理办法,本文从热力学的角度讨论了连续退火工艺均热过程数种Q&P钢奥氏体化的程度。重新计算了Fe-Si-Mn-C四元系固溶相BCC_A2和FCC_A1的热力学性质。结合连续退火工艺均热段的快速加热,短时保温,快速冷却的热处理工艺特点,按照PLE(Partition local equilibrium)和NPLE(Negligible partition local equilibrium)局部平衡计算了当前几种Q&P钢成分的FCC相线和奥氏体体积分数,并根据试验观测结果,提出了一种符合连续退火生产Q&P钢实际需求的准平衡相图计算方法:“准PLE”(Quasi-partition local equilibrium)计算方法,实际观测结果与理论预测结果符合较好。
基金financially supported by the Key Research & Development Program of Jiangsu Province(No.BE2017102)
文摘（MnFe）2（P, Si）-type compounds are, to date, one of the best candidates for magnetic refrigeration and energy conversion applications due to the combination of giant magnetocaloric effect （MCE）, tunable working temperature range and low material cost. The giant MCE in the （Mn, Fe）2（P, Si）-type compounds originates from strong mag- netoelastic coupling, where the lattice degrees of freedom and spin degrees of freedom are efficiently coupled. The tunability of the phase transition, in terms of the critical temperature and the character of the phase transition, is essentially attributed to the changes in the magnetoelastic coupling in the （Mn, Fe）2（P, Si）-type compounds. In this review, not only the fundamentals of the magnetoelastic coupling but also the related practical aspects such as magnetocaloric performance, hysteresis issue and mechanical stability are discussed for the （Mn, Fe）2（P, Si）- type compounds. Additionally, some future fundamental studies on the MCE as well as possible ways of solving the hysteresis and fracture issues are proposed.
