03315nas a2200409 a 4500 20260817161322.0 260114s20249999th u ms t 000 eng d .b1247017x AIT Thesis no.ISE-24-20 Rima, Sarmin Akter A machine learning approach to predict the mechanical properties of zeolitic imidazolate frameworks (ZIFs) Pathum Thani : Asian Institute of Technology, 2024 100 leaves : ill.+ 1 online resource Thesis ; no. ISE-24-20 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Bio-Nano Material Science and Engineering Thesis (M. Eng.) - Asian Institute of Technology, 2024 Zeolitic imidazolate frameworks (ZIFs), which are porous crystalline materials composed of metal centers (mostly Zn (II) or Co (II)) and imidazole-based ligands, have garnered significant attention due to their versatile applications in gas separation and catalysis. In this regard, the mechanical properties of ZIFs are relevant to study, to obtain information on their flexibility and the effect on species adsorption and release. Traditional methods for predicting the properties of ZIFs are time-consuming and computationally intensive. This research explores the application of machine learning techniques to predict the mechanical properties of a set of ZIFs with sufficient accuracy and computational efficiency. By leveraging a dataset of ZIF structures and their corresponding mechanical properties, machine learning was trained and used to predict key mechanical attributes such as shear modulus (G) and bulk modulus (K). The results will be used not only to assess the potential of machine learning as a valuable tool for calculating and predicting the mechanical performance of ZIF materials but also to enable the design of novel ZIF-based materials with tailored mechanical characteristics for various applications. This research can offer valuable insights into the synergy between traditional computational chemistry and machine learning, opening new avenues for the efficient exploration and development of ZIFs with desired mechanical properties. Machine learning Molecular dynamics Porous materials Ricco, Raffaele, Chairperson Bora, Tanujjal, Examination Committee Chaklam Silpasuwanchai, Examination Committee His Majesty the King{u2019}s Scholarship (Thailand), Scholarship Donor Asian Institute of Technology. Thesis ; no. ISE-24-20 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B23356 .b1247017x mnarc a 260127 0 260121 m h a 0 mnarc mnarc 40 61 Barcode : 30050120422430 CREATED : 2026-01-14 RECORD # : i13566088 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : - CREATED : 2026-01-14 RECORD # : i1356609x LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 834 834 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT Thesis no.ISE-24-20 30050120422430 2026-08-17 16:13:22 1 2026-08-17 40 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT Thesis no.ISE-24-20 2026-08-17 16:13:22 1 2026-08-17 61