Po­rous Metal Ge­no­mics for Tailo­ring Me­cha­ni­cal Pro­per­ties of Light-​weight 3D-​Printed Ar­chi­tec­tu­res - POR­ME­TA­LO­MICS

Pro­ject sum­ma­ry

Po­rous me­tals are in­crea­sin­gly im­portant in tech­no­lo­gy. Due to their tun­able me­cha­ni­cal pro­per­ties, they are pro­mi­sing can­di­da­tes in va­rious emer­ging ap­p­li­ca­ti­ons such as me­tal­lic scaf­folds for load-​bearing bones, light­weight struc­tu­res for trans­port tech­no­lo­gies, elec­tro­des for elec­tro­che­mi­cal en­er­gy sto­rage de­vices, and more. This pro­ject aims at de­ve­lo­ping a com­pu­ta­tio­nal model to es­tab­lish a quan­ti­ta­ti­ve un­der­stan­ding of the re­la­ti­ons bet­ween the enor­mous va­rie­ty of pos­si­ble mor­pho­lo­gies of po­rous struc­tu­res and their me­cha­ni­cal pro­per­ties. The machine-​learning-based model will be em­ploy­ed to iden­ti­fy va­rious pro­to­ty­pe struc­tu­res of new mor­pho­lo­gies via the im­ple­men­ta­ti­on of hier­ar­chi­cal scree­ning and a ma­te­ri­al ge­no­me ap­proach. The op­ti­mal and/or sta­tis­ti­cal­ly re­le­vant struc­tu­res will be 3D prin­ted and tested me­cha­ni­cal­ly in ex­pe­ri­ments, with the re­sults con­tri­bu­ting to both tu­ning and va­li­da­ti­on of the com­pu­ta­tio­nal de­signs.