Towards high-throughput microstructure simulation in compositionally complex alloys via machine learning

The coupling of computational thermodynamics and kinetics has been the central research theme in Integrated Computational Material Engineering (ICME). Two major bottlenecks in implementing this coupling and performing efficient ICME-guided high-throughput multi-component industrial alloys discovery or process parameters optimization, are slow responses in kinetic calculations to a given set of compositions and processing conditions and the quality of a large amount of calculated thermodynamic data. Here, we employ machine learning techniques to eliminate them, including (1) intelligent corrupt data detection and re-interpolation (i.e. data purge/cleaning) to a big tabulated thermodynamic dataset based on an unsupervised learning algorithm and (2) parameterization via artificial neural networks of the purged big thermodynamic dataset into a non-linear equation consisting of base functions and parameterization coefficients. The two techniques enable the efficient linkage of high-quality data with a previously developed microstructure model. This proposed approach not only improves the model performance by eliminating the interference of the corrupt data and stability due to the boundedness and continuity of the obtained non-linear equation but also dramatically reduces the running time and demand for computer physical memory simultaneously. The high computational robustness, efficiency, and accuracy, which are prerequisites for high-throughput computing, are verified by a series of case studies on multi-component aluminum, steel, and high-entropy alloys. The proposed data purge and parameterization methods are expected to apply to various microstructure simulation approaches or to bridging the multi-scale simulation where handling a large amount of input data is required. It is concluded that machine learning is a valuable tool in fueling the development of ICME and high throughput materials simulations.publishedVersio

Precipitation and strengthening modeling for disk-shaped particles in aluminum alloys: Size distribution considered

For an ICME (Integrated Computational Material Engineering) modeling framework used for the age-hardening aluminum alloy design and heat treatment parameters optimization, it is critical to take into account the geometric shape of precipitates, as it is tightly related to the precipitation kinetics and particles' hardening effect. The aim of this paper is to present such an ICME modeling approach to describe the precipitation of disk-shaped hardening particles during aging treatment and predict the final yield strength. The classical Kampmann–Wagner Numerical (KWN) model is extended to consider the influence of disk-shaped particle morphology on growth kinetics. The extension consists of two correction factors to the growth rate equation and to the Gibbs-Thomson effect. The extended model, coupled with a metastable thermodynamic database, is applied to simulate precipitation kinetics of Al-Cu and Al-Mg-Zn alloys during aging treatment. The predicted microstructural features are in reasonable agreement with the reported experimental observations. Furthermore, a strengthening model for disk-shaped particles, which considers the size distributions of precipitates, is developed. The predicted yield strengths are compared with reported tensile test results and with predictions from other strength models. Unlike other models, the proposed strength model can reveal the strength contribution from disk-shaped precipitates without an additional tuning parameter for accounting for the impact of the mean particle spacing in the slip plane.acceptedVersio

Extremely improved formability of Al–Zn–Mg–Cu alloys via micro-domain heterogeneous structure

peer reviewedHere we report a heterogeneous microstructure in Al–Zn–Mg–Cu alloys by coupling control of solute gradient distribution, multiscale iron-rich phases and a novel thermomechanical processing that can produce a greatly improved formability (the average plastic strain ratio r = 0.719). A heterogeneous structure of coarse grains surrounded by fine grains is formed, and an unusual high formability is obtained by the synergy of soft/hard microdomains. The process discovered here is amenable to large-scale automotive industrial production at low cost, and might be applicable to other Al alloy systems

Synergistic improvement in bake-hardening response and natural aging stability of Al-Mg-Si-Cu-Zn alloys via non-isothermal pre-aging treatment

A new non-isothermal pre-aging treatment was proposed and utilized in Al-Mg-Si-Cu-Zn alloys, together with natural aging and artificial aging. The influence of cooling rates on subsequent precipitation behaviors was investigated by experimental and thermodynamic simulations. The results show that by controlling the formation of clusters/GP zones through changing pre-aging cooling rates, i.e. PA-0.2, PA-0.3 and PA-0.4 (°C/min, from 80 °C to 40 °C), an excellent bake hardening increment and natural aging stability can be obtained. The highest bake hardening increment can reach 180 MPa for PA-0.4 sample, which is twice higher than those of Al-Mg-Si-(Cu) alloys. The microhardness remains almost unchanged within NA for 14 days at a lower level of approximately 85 HV0.2. Thermodynamic simulations estimate the solvus temperatures and chemical composition for GP zones, revealing the strengthening and stabilising mechanisms behind: a) Mg-Zn- clusters formed during pre-aging can suppress Mg-Si- clusters formation in the natural aging process, b) non-isothermal hinders the precipitates growth, a faster cooling rate leads to smaller and softer Mg-Zn- clusters, and c) the formation of a heterogeneous microstructure contributes to the high bake-hardening response without changing the type of strengthening phase β″. Finally, the clustering and aging process was illustrated and explained.Team Maria Santofimia Navarr

Synergy of Sn micro-alloying and thermomechanical processing on formability and precipitation behavior of Al-Mg-Si-Cu-Zn alloys

The effect of Sn micro-alloying on microstructure evolution, formability and precipitation behaviour of Al-Mg-Si-Cu-Zn alloys were systematically studied by experimental techniques and theoretical calculations. Results show that Sn addition can accelerate both the precipitation and re-dissolution of the Fe-rich phase during casting and homogenising treatments, which thereby determined the final microstructure. A significant retarding effect to natural ageing precipitation was observed with increasing Sn content in quenching samples, but this effect was weakened in pre-aged samples, as explained by DSC and simulations. The different number densities of the strengthening phase β″at the same artificial aging state are mainly attributed to the changed activation energy of the β″ phase affected by the formed Sn-containing Mg-Zn clusters and Mg-Si clusters. Trace Sn participating in the formation of GP zones, Sn-containing MgZn2 phase and new precipitating sequences during ageing were proposed for the first time.Team Maria Santofimia Navarr

Understanding the bending behavior and through-thickness strain distribution during asymmetrical rolling of high-strength aluminium alloy plates

The asymmetric rolling (ASR) process is highly desired to improve the through-thickness deformation/strain uniformity by introducing additional shear strains for uniform through-thickness microstructures and mechanical properties of metallic/alloy plates. In this study, the bending behavior and mechanism during the ASR processing of high-strength AA7050 aluminium alloy plates were simulated along with rolling trials. It shows that the plate will bend upward (toward slower roll) at larger speed ratios and smaller thickness reductions but downward (toward faster roll) at smaller speed ratios and larger thickness reductions. The ASR processing can increase the central equivalent plastic strains and decrease the surface-to-center strain gradient compared with that caused by the conventional symmetric rolling. The high strain rate bands (HSRBs) as key plastic strain accumulation regions are intimately connected with the post-rolling equivalent plastic strain distribution and the outgoing curvature. Especially, when the HSRB approaches the plate upper surface near the end of the deformation zone, normally at larger thickness reductions, a downward bending occurs despite that the lower roll rotates faster, and vice versa. The through-thickness HSRB induced by the ASR processing is considered to mainly enhancing the equivalent plastic strain homogeneity. The formation and interactive mechanisms of the HSRBs and their connection with the bending behavior during the ASR processing were discussed

Flattening aluminum plates with tuning asymmetric rolling parameters

The asymmetric rolling (ASR) process can introduce shear strains inside the plate, resulting in the improvements of microstructures and mechanical properties. Its industrial application for rolling the (mid-)thick plates is impeded by the uncontrollable bending behavior. In this study, the influences of rolling parameters on the bending behavior of the rolled AA 7050 aluminum alloy plates were investigated. It is found that the plate will bend towards the slower roll with larger speed ratios and initial plate thickness as well as lower thickness reduction. A flat plate can be obtained by choosing appropriate rolling parameters. The equivalent plastic strain rate distribution is considered to be critical to the plate bending, the downward bending (towards faster roll) would be associated with an obvious increase of the equivalent plastic strain rate at the top surface of the plate near the end of the deformation zone. Multi-pass asymmetric rolling routes considering bending optimization were proposed and verified through rolling trials. As the speed ratio increased from 1.1 to 1.2, the through-thickness plastic strain became more homogeneous and the total rolling pass numbers decreased by 33 % (from 9 passes to 6 passes)

Fast age-hardening response of Al–Mg–Si–Cu–Zn–Fe–Mn alloy via coupling control of quenching rate and pre-aging

The coupling control of quenching rate and pre-aging and its positive effect on the age-hardening response of Al–Mg–Si–Cu–Zn–Fe–Mn alloy was systematically investigated. The larger and more stable solute clusters can be formed in alloy with fast age-hardening response by using the lower quenching rate (5.3 °C/min) and an appropriate pre-aging, in which the deterioration of natural aging also can be obviously suppressed. Additionally, the highest bake hardening increment of the alloy can reach 145.2 MPa, which is much higher than those of traditional Al–Mg–Si–(Cu) alloys (such as, 6016 and 6111 alloys). Based on the detailed precipitation behavior characterization of alloys with different quenching rates and the same pre-aging, the quenching rate change can result in the significant differences in the size, number density of precipitates in the both paint baking and peak aging states, but the type of precipitates basically keeps the same, i.e., Mg–Si precipitates, and no Mg–Zn precipitates can be observed. Finally, the related mechanisms of coupling control of quenching rate and pre-aging were also discussed in this paper. The developed coupling control method shows great potential and could significantly increase applications of Al–Mg–Si–Cu–Zn–Fe–Mn alloys with a fast age-hardening response.Team Maria Santofimia Navarr

Synergy of Ni micro-alloying and thermomechanical processing in Al–Mg–Si–Cu–Zn–Fe–Mn alloys with enhanced bendability

Synergy of Ni micro-alloying and thermomechanical processing on the phase distribution, formability and bendability of Al–Mg–Si–Cu–Zn–Fe–Mn alloys was systematically studied in this paper. With the addition of micro-alloying Ni, the Ni-containing Fe-rich phase can be formed, which not only serves as nucleation sites of Mg–Si precipitates (such as, Q phase) during the casting process, but also improves the uniform distribution level of Fe-rich phases after homogenization. The formability and bendability of Ni-containing alloy can be both improved to a certain level due to the positive effect of Ni micro-alloying. In comparison, if increasing the cold rolling deformation between hot rolling and annealing, the distribution of multi-scale Fe-rich phases can be significantly improved based on the synergy of Ni micro-alloying and thermomechanical processing. And finally, this improvement further results in the great improvements in the microstructure, texture, formability (average r = 0.688, △r = −0.09) and bendability of the alloy together. Based on the microstructure evolution, the synergy mechanism of Ni micro-alloying and thermomechanical processing is put forward in this paper.Team Maria Santofimia Navarr

Precipitation and strengthening modeling for disk-shaped particles in aluminum alloys: Size distribution considered

For an ICME (Integrated Computational Material Engineering) modeling framework used for the age-hardening aluminum alloy design and heat treatment parameters optimization, it is critical to take into account the geometric shape of precipitates, as it is tightly related to the precipitation kinetics and particles' hardening effect. The aim of this paper is to present such an ICME modeling approach to describe the precipitation of disk-shaped hardening particles during aging treatment and predict the final yield strength. The classical Kampmann–Wagner Numerical (KWN) model is extended to consider the influence of disk-shaped particle morphology on growth kinetics. The extension consists of two correction factors to the growth rate equation and to the Gibbs-Thomson effect. The extended model, coupled with a metastable thermodynamic database, is applied to simulate precipitation kinetics of Al-Cu and Al-Mg-Zn alloys during aging treatment. The predicted microstructural features are in reasonable agreement with the reported experimental observations. Furthermore, a strengthening model for disk-shaped particles, which considers the size distributions of precipitates, is developed. The predicted yield strengths are compared with reported tensile test results and with predictions from other strength models. Unlike other models, the proposed strength model can reveal the strength contribution from disk-shaped precipitates without an additional tuning parameter for accounting for the impact of the mean particle spacing in the slip plane