DID Code:A Bridge Connecting the Materials Genome Engineering Database w让h Inheritable Integrated Intelligent Manufacturing

A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet ofThings.With the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material informatics.This work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T 39-2005.Each build chain is made up of capital letters and numbers,with no symbols.Moreover,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC 10646.Based on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based platforms.Accordingly,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific machines.By utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.

Revealing the Local Microstates of Fe–Mn–Al Medium Entropy Alloy:A Comprehensive First-principles Study

Entropy-stabilized multi-component alloys have been considered to be prospective structural materials attributing to their impressive mechanical and functional properties.The local chemical complexions,microstates and configurational transformations are essential to reveal the structure–property relationship,thus,to promote the development of advanced multicomponent alloys.In the present work,effects of local lattice distortion(LLD)and microstates of various configurations on the equilibrium volume(V0),total energy,Fermi energy,magnetic moment(μMag)and electron work function(Φ)and bonding structures of the Fe–Mn–Al medium entropy alloy(MEA)have been investigated comprehensively by first-principles calculations.It is found that theΦandμMag of those MEA are proportional to the V 0,which is dominated by lattice distortion.In terms of bonding charge density,both the strengthened clusters or the so-called short-range order structures and the weakly bonded spots or weak spots are characterized.While the presence of weakly bonded Al atoms implies a large LLD/mismatch,the Fe–Mn bonding pairs result in the formation of strengthened clusters,which dominate the local microstates and the configurational transitions.The variations ofμMag are associated with the enhancement of the nearest neighbor magnetic Fe and Mn atoms,attributing to the LLD caused by Al atoms,the local changes in the electronic structures.This work provides an atomic and electronic insight into the microstate-dominated solid-solution strengthening mechanism of Fe–Mn–Al MEA.

Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses

Fe-based metallic glasses(MGs)have been extensively investigated due to their unique properties,especially the outstanding soft-magnetic properties.However,conventional design of soft-magnetic Fe-based MGs is heavily relied on“trial and error”experiments,and thus difficult to balance the saturation flux density(Bs)and thermal stability due to the strong interplay between the glass formation and magnetic interaction.Herein,we report an eXtreme Gradient Boosting(XGBoost)machine-learning(ML)model for developing advanced Fe-based MGs with a decent combination of Bs and thermal stability.

High-throughput investigations of configurational-transformation-dominated serrations in CuZr/Cu nanolaminates

Metallic amorphous/crystalline(A/C)nanolaminates exhibit excellent ductility while retaining their high strength.However,the underlying physical mechanisms and the resultant structural changes during plastic deformation still remain unclear.In the present work,the structure-property relationship of CuZr/Cu A/C nanolaminates is established through integrated high-throughput micro-compression tests and molecular dynamics simulations together with high-resolution transmission electron microcopy.The serrated flow of nanolaminates results from the formation of hexagonal-close-packed(HCP)-type stacking faults and twins inside the face-centered-cubic(FCC)Cu nano-grains,the body-centered-cubic(BCC)-type ordering at their grain boundaries,and the crystallization of the amorphous CuZr layers.The serration behavior of CuZr/Cu A/C nanolaminates is determined by several factors,including the formation of dense dislocation networks from the multiplication of initial dislocations that formed after yielding,weak-spots-related configurational-transitions and shear-transition-zone activities,and deformation-induced devitrification.The present work provides an insight into the heterogeneous deformation mechanism of A/C nanolaminates at the atomic scale,and mechanistic base for the microstructural design of self-toughening metallic-glass(MG)-based composites and A/C nanolaminates.