Peer-reviewedCC BY-NC-ND 4.0Scientific Reports
PolyTransGAN enables neuro-symbolic inverse design of 4D-printable shape-memory polymers
Related
- Machine learning-driven inverse design of high-hardness multi-principal element alloys through symbolic regression
- Bio-Based Levoglucosenone Enables Regioisomer-Driven Inversion of Optical Activity in Polymers via Stereoselective Thia-Michael Addition of 1,2- and 1,3-Benzenedithiols
- Differentiable mass transfer modeling enables wet lab validated inverse analysis of liquid chromatography
- Establishment of printable and pressureless sinterable ZrB2-B4C-C composite: a resin-free formulation with sintering aids compatible with aqueous suspensions
- 3D-Printable Granular Hydrogel Composed of Hyaluronic Acid-Chitosan Hybrid Polyelectrolyte Complex Microgels
BibTeX
@article{majeed2026polytransgan,
title = {{PolyTransGAN enables neuro-symbolic inverse design of 4D-printable shape-memory polymers}},
author = {Zainab Naeif Majeed and Estabraq Ali Hameed and Mohammed B. Wathiq AL-timim and Rasha M. Dadoosh and Amer N. Jarad and Amin Dolatabadi},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-74660-8},
url = {https://www.nature.com/articles/s41598-026-74660-8},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - PolyTransGAN enables neuro-symbolic inverse design of 4D-printable shape-memory polymers
AU - Zainab Naeif Majeed
AU - Estabraq Ali Hameed
AU - Mohammed B. Wathiq AL-timim
AU - Rasha M. Dadoosh
AU - Amer N. Jarad
AU - Amin Dolatabadi
PY - 2026
DA - 2026/10/07
JO - Scientific Reports
DO - 10.1038/s41598-026-74660-8
UR - https://www.nature.com/articles/s41598-026-74660-8
SN - 2045-2322
ER -