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SUMMARY:Inverse Design of Architected Materials: From Mechanics-Based Meth
 ods to Data-Driven Methods    - Professor Wei Tan\, Queen Mary University 
 of London
DTSTART:20241206T140000Z
DTEND:20241206T150000Z
UID:TALK221215@talks.cam.ac.uk
CONTACT:46601
DESCRIPTION:The potential of architected materials in engineering structur
 es is immense\, offering tailorable mechanical\, thermal\, and other multi
 -physical properties. However\, their design space is vast\, presenting ch
 allenges in identifying optimal configurations for specific functions. Thi
 s motivates the need for inverse design methods. In this talk\, I will fir
 st introduce an analytical approach for the inverse design of shape-morphi
 ng composites. This framework employs modulus grading and multi-material a
 dditive manufacturing to engineer composite structures capable of morphing
  into target shapes. Through a novel model based on graded beam theory\, w
 e predict tapering patterns that fulfil both tessellation and modulus grad
 ing requirements to achieve the desired bending stiffness. Modulus grading
  is realised by discretising the geometry and using the rule of mixtures t
 o determine the volume fractions needed for specific cross-sectional modul
 i.\n\nIn the second part\, I will present a new data-driven method for the
  inverse design of materials with multi-physics properties. Mapping physic
 al properties to microstructural topology space is challenging\, as divers
 e topologies can produce similar effective properties. Our inverse design 
 approach effectively addresses this issue using a conditional Generative A
 dversarial Network (cGAN) method\, enabling the design of architected mate
 rials with tunable permeability\, diffusivity\, and mechanical properties.
  Results demonstrate this method’s ability to balance permeability-diffu
 sivity-mechanical synergy\, enhancing the tunable range of multi-physical 
 performance and enabling functionally graded metamaterials with tailored m
 ulti-functionality. In summary\, we have proposed two distinct inverse des
 ign frameworks\, which can be employed in a variety of applications involv
 ing multi-physical environments.\n\nBiography:\n\nDr Wei Tan is currently 
 a Reader in Mechanics of Materials at Queen Mary University of London. He 
 joined Queen Mary as a Lecturer in Jan 2020. Prior to this\, he was a Rese
 arch Associate at the University of Cambridge\, working with Prof. Norman 
 Fleck. He pursued his PhD at Queen’s University Belfast under the superv
 ision of Prof. Brian Falzon (2012-2016). With over a decade of research ex
 perience\, he has contributed to fields in the mechanics of materials\, co
 mputational modelling and multifunctional materials. Dr. Tan has published
  over 40 papers in prestigious journals (JMPS\, EML\, CSTE\, Composites Pa
 rt A/B)\, accumulating 2200+ citations with an H-index of 21. In recent ye
 ars\, he has secured substantial funding (over £1.8 million) as PI\, incl
 uding an ERC Starting Grant\, an EPSRC New Investigator Award\, and a Roya
 l Society grant. In recognition of his outstanding research contributions\
 , Dr. Tan has received several awards\, including the ESCM 2024 Young Rese
 archer Award\, Queen Mary Faculty Research Excellence Award\, Cambridge Bl
 uesky Award and the Royal Aeronautical Society Bronze Paper Award. Additio
 nally\, Dr. Tan was featured among the World’s Top 2% Scientists by Stan
 ford University in 2023 and 2024 (Materials).
LOCATION:Oatley 1 Meeting Room\, Department of Engineering
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