Enhancing the strain hardening and ductility of Mg-Y alloy by introducing stacking faults

Due to the insufficient slip systems,Mg and its alloys exhibit poor ductility during plastic deformation at room temperature.To solve this problem,alloying is considered as a most effective method to improve the ductility of Mg alloys,which attracts wide attentions of industries.However,it is still a challenge to understand the ductilization mechanism,because of the complicated alloying elements and their interactions with Mg matrix.In this work,pure Mg and Mg-Y alloys were comparatively studied to investigate the effect of Y addition on microstructure evolution and mechanical properties.A huge increase of uniform elongation,from 5.3%to 20.7%,was achieved via only 3 wt%addition of yttrium.TEM results revealed that the only activated slip system in pure Mg was basalslip,led to its poor ductility at room temperature.In contrast,a large number of stacking faults and non-basal dislocations with<c>component were observed in the deformed Mg-Y alloy,which was proposed as the main reason for significant improvement of strain hardening and ductility.High resolution TEM indicated that most of the stacking faults were II and 12 intrinsic faults,which played a critical role in improving the ductility of Mg-Y alloy.Addition of Y into Mg alloy decreased the stacking fault energy,which induced high density stacking faults in the grain interior.

Thermo-kinetic connectivity by integrating thermo-kinetic correlation and generalized stability

Designing structured materials with optimized mechanical properties generally focuses on engineering microstructures,which are closely determined by the processing routes,such as phase transformations(PTs)and plastic deformations(PDs).Both PTs and PDs follow inherent trade-off relation between thermodynamic driving force ΔG and kinetic energy barrier Q,i.e.,so-called thermo-kinetic correlation.By analyzing nucleation and growth and proposing a conception of negative driving force integrating strain energy,interface energy and any kind of energy that equivalently inhibits the PT itself,ΔG^(S),unified expressions for the thermo-kinetic correlation and generalized stability(GS)were derived for three kinds of PTs,i.e.,diffusive PTs with simultaneously decreasedΔG and increased Q,diffusive PTs with simultaneously increasedΔG and decreased Q,and displacive PTs with simultaneously increased ΔG and decreased Q.This leads to so-called thermo-kinetic connectivity by integrating the thermo-kinetic correlation and the GS,where,by application in typical PTs,it was clearly shown,a criterion of high ΔG-high GS can be predicted by modulating chemical driving force,negative driving force and kinetic energy barrier for diffusion or nucleation.Following thermo-kinetic connectivity,analogous procedure for dislocation evolution upon PDs was performed,and materials design in terms of the highΔG-high GS criterion was discussed and prospected.

Synthesis of Visible-Light-Driven g-C3N4/PPy/Ag Ternary Photocatalyst with Improved Photocatalytic Performance

g-C3N4/PPy/Ag ternary photocatalyst was synthesized by a three-step method. Firstly, graphitic carbon nitride （g-C3N4） photocatalyst was obtained by sintering melamine at high temperature, then a series ofg-C3N4/PPy com- posite photocatalysts were prepared by in-situ polymerization of pyrrole, and finally the g-C3N4/PPy/Ag ternary composite photocatalyst was obtained by depositing Ag on the surface of g-C3N4/PPy. The photocatalytic activities of as-prepared samples were evaluated by degradation of antibiotic tetracycline （TC） under visible light. The influ- ence of the amounts of polypyrrole （PPy） and Ag on the photocatalytic activity of g-C3N4/PPy/Ag ternary photo- catalyst was investigated. Both PPy and Ag played critical roles for the enhanced photocatalytic activity of g-C3N4/PPy/Ag. The g-C3N4/PPy/Ag composites exhibited remarkably improved photocatalytic activities for de- grading TC compared with g-C3N4, g-C3N4/PPy and g-C3N4/Ag. Besides, the photocatalytic mechanism was also analyzed. The band match of PPy with g-C3N4 benefited the separation of photo-generated carriers in g-C3N4, and the deposited Ag nanoparticles played important roles as an electron mediator due to the surface plasmon resonance （SPR） effects. The present study offered new insight into the design of the economical and gently environ- ment-friendly synthesis of highly efficient photocatalysts.

Excellent strength-ductility combination of Cr_(26)Mn_(20)Fe_(20)Co20Ni_(14) high-entropy alloy at cryogenic temperatures

In the present study,a face-centered cubic non-equiatomic Cr_(26)Mn_(20)Fe_(20)Co20Ni_(14) high-entropy alloy(HEA)with a low stacking fault energy of 17.6 mJ m^(−2) was prepared by vacuum induction melting,forging and annealing processes.The recrystallized sample is revealed to exhibit an excellent combination of strength and ductility over a wide temperature range of 4.2–293 K.With decreasing temperature from 293 to 77 K,the ductility and ultimate tensile strength(UTS)gradually increase by 30% to 95% and 137% to 1020 MPa,respectively.At the lowest temperature of 4.2 K,the ductility keeps 65% and the UTS increases by 200% to 1300 MPa,which exceed those published in the literature,including conventional 300 series stainless steels.Detailed microstructural analyses of this alloy reveal a change of deformation mechanisms from dislocation slip and nano-twinning at 293 K to nano-phase transformation at 4.2 K.The cooperation and competition of multiple nano-twinning and nano-phase transformation are responsible for the superior tensile properties at cryogenic temperatures.Our study provides experimental evidence for potential cryogenic applications of HEAs.

Trade Credit and Buyer Financing

This study investigates trade credit and early payment financing in a three-party supply chain consisting of a manufacturer,a capital-constrained distributor,and a retail platform.The manufacturer or the platform provides the financing service to the distributor.Two different leadership structures are investigated,namely,platform and manufacturer leadership Stackelberg game,where the platform or manufacturer first makes the decision,respectively.Under trade credit financing,the manufacturer and the whole supply chain face loss when the commission rate increases.However,under buyer financing,they benefit from the high commission rate.Under platform leadership,the distributor,the manufacturer,and the supply chain perform better with trade credit if and only if the commission rate is small or the production cost is high,while the platform always prefers buyer financing.Under manufacturer leadership,the distributor,manufacturer,and supply chain perform better with trade credit under low production cost and commission rate.The platform prefers trade credit when production cost is in the intermediate range.By further analyzing the case that both financing channels are available and the distributor decides which one to choose,we find that the financing services competition hurts only the platform's profits.And under certain conditions,trade credit and early payment can achieve the same performance for every supply chain member.These findings enhance our understanding of the supply chain risk allocation efficiency of trade credit and early payment financing under different leadership structures.Neither risk allocation form outperforms the other,and the relative efficiency depends on supply chain characteristics.

Predicting single-phase solid solutions in as-sputtered high entropy alloys:High-throughput screening with machine-learning model

Searching for single-phase solid solutions(SPSSs)in high-entropy alloys(HEAs)is a prerequisite for the intentional design and manipulation of microstructures of alloys in vast composition space.However,to date,reported SPSS HEAs are still rare due to the lack of reliable guiding principles for the synthesis of new SPSS HEAs.Here,we demonstrate an ensemble machine-learning method capable of discovering SPSS HEAs by directly predicting quinary phase diagrams based only on atomic composition.A total of 2198 experimental structure data are extracted from as-sputtered quinary HEAs in the literature and used to train a random forest classifier(termed AS-RF)utilizing bagging,achieving a prediction accuracy of 94.6%compared with experimental results.The AS-RF model is then utilized to predict 224 quinary phase diagrams including∼32,000 SPSS HEAs in Cr-Co-Fe-Ni-Mn-Cu-Al composition space.The extrapolation capability of the AS-RF model is then validated by performing first-principle calculations using density functional theory as a benchmark for the predicted phase transition of newly predicted HEAs.Finally,interpretation of the AS-RF model weighting of the input parameters also sheds light on the driving forces behind HEA formation in sputtered systems with the main contributors being:valance electron concentration,work function,atomic radius difference and elementary symmetries.

An efficient scheme for accelerating the calculation of stacking fault energy in multi-principal element alloys

We present the High-Throughput Computing and Statistical Analysis(HCSA)scheme,which efficiently and accurately predicts the stacking fault energies(SFEs)of multi-principal element alloys(MPEAs).Our approach estimates the SFE of a single complex supercell by averaging numerous SFEs from small supercells,resulting in superior accuracy compared to traditional density functional theory(DFT)calculations.To validate our scheme,we applied it to NiFe and Ni_(10)Co_(60)Cr_(25)W_(5)alloys,achieving an SFE error of only 11%,in contrast to the 45%error obtained from traditional DFT calculations for NiFe.We observed a strong correlation between the average SFEs of samples with the same valence electron concentration as that of the experimental data.Our scheme provides an efficient and reliable tool for predicting SFEs in MPEAs and holds the potential to significantly accelerate materials design and discovery processes.