Ο κλάδος των πολυμερών και των πλαστικών εξελίσσεται ραγδαία, με την Τεχνητή Νοημοσύνη και την Υπολογιστική Μάθηση να αναλαμβάνουν πλέον κεντρικό ρόλο στη σχεδίαση νέων υλικών, στη μοντελοποίηση των ιδιοτήτων τους και στη βελτιστοποίηση παραγωγικών διεργασιών. Η ενσωμάτωση τεχνικών βαθιάς μάθησης, γραφικών αναπαραστάσεων και surrogate models οδηγεί σε ταχύτερη και πιο ακριβή πρόβλεψη συμπεριφοράς πολυμερών, μειώνοντας τον χρόνο και το κόστος ανάπτυξης και επιτρέποντας την ανακάλυψη καινοτόμων υλικών.

Στην παρούσα σελίδα συγκεντρώνουμε πρόσφατες ερευνητικές δημοσιεύσεις από τον διεθνή χώρο, οι οποίες προτείνουν σύγχρονες μεθοδολογίες και αποτελέσματα στον τομέα των πολυμερών, των προσομοιώσεων ιδιοτήτων υλικών και των αλγοριθμικών προσεγγίσεων για προβλεπτική μοντελοποίηση. Η συλλογή ενημερώνεται τακτικά με νέα άρθρα από κορυφαίες ερευνητικές ομάδες και διεθνή συνέδρια, προσφέροντας μια ολοκληρωμένη εικόνα της προόδου που σημειώνεται στη διασύνδεση επιστήμης υλικών και τεχνητής νοημοσύνης.

Title Authors Published PDF URL
When does deep learning fail and how to tackle it? A critical analysis on polymer sequence-property surrogate models Himanshu, Tarak K Patra 2022-10-12 http://arxiv.org/pdf/2210.06622v1
Representing Polymers as Periodic Graphs with Learned Descriptors for Accurate Polymer Property Predictions Evan R. Antoniuk, Peggy Li, Bhavya Kailkhura, Anna M. Hiszpanski 2022-05-27 http://arxiv.org/pdf/2205.13757v1
Unifying Polymer Modeling and Design via a Conformation-Centric Generative Foundation Model Fanmeng Wang, Shan Mei, Wentao Guo, Hongshuai Wang, Qi Ou, Zhifeng Gao, Hongteng Xu 2025-10-15 http://arxiv.org/pdf/2510.16023v1
Copolymer Informatics with Multi-Task Deep Neural Networks Christopher Künneth, William Schertzer, Rampi Ramprasad 2021-03-25 http://arxiv.org/pdf/2103.14174v1
Data-based Polymer-Unit Fingerprint (PUFp): A Newly Accessible Expression of Polymer Organic Semiconductors for Machine Learning Xinyue Zhang, Genwang Wei, Ye Sheng, Jiong Yang, Caichao Ye, Wenqing Zhang 2022-11-03 http://arxiv.org/pdf/2211.01583v1
A machine learning platform for development of low flammability polymers Duy Nhat Phan, Alexander B. Morgan, Lokendra Poudel, Rahul Bhowmik 2025-03-31 http://arxiv.org/pdf/2504.00223v1
A Machine Learning Method for Material Property Prediction: Example Polymer Compatibility Zhilong Liang, Zhiwei Li, Shuo Zhou, Yiwen Sun, Changshui Zhang, Jinying Yuan 2022-02-28 http://arxiv.org/pdf/2202.13554v1
Graph Convolutional Neural Networks for Polymers Property Prediction Minggang Zeng, Jatin Nitin Kumar, Zeng Zeng, Ramasamy Savitha, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar 2018-11-15 http://arxiv.org/pdf/1811.06231v1
Molecular topological deep learning for polymer property prediction Cong Shen, Yipeng Zhang, Fei Han, Kelin Xia 2024-10-07 http://arxiv.org/pdf/2410.04765v1
Augmenting Control over Exploration Space in Molecular Dynamics Simulators to Streamline De Novo Analysis through Generative Control Policies Paloma Gonzalez-Rojas, Andrew Emmel, Luis Martinez, Neil Malur, Gregory Rutledge 2023-06-26 http://arxiv.org/pdf/2306.14705v2
Scaling Law of Sim2Real Transfer Learning in Expanding Computational Materials Databases for Real-World Predictions Shunya Minami, Yoshihiro Hayashi, Stephen Wu, Kenji Fukumizu, Hiroki Sugisawa, Masashi Ishii, Isao Kuwajima, Kazuya Shiratori, Ryo Yoshida 2024-08-07 http://arxiv.org/pdf/2408.04042v1
Predicting Mechanical Properties from Microstructure Images in Fiber-reinforced Polymers using Convolutional Neural Networks Yixuan Sun, Imad Hanhan, Michael D. Sangid, Guang Lin 2020-10-07 http://arxiv.org/pdf/2010.03675v1
AI-guided inverse design and discovery of recyclable vitrimeric polymers Yiwen Zheng, Prakash Thakolkaran, Agni K. Biswal, Jake A. Smith, Ziheng Lu, Shuxin Zheng, Bichlien H. Nguyen, Siddhant Kumar, Aniruddh Vashisth 2023-12-06 http://arxiv.org/pdf/2312.03690v4
Polymer Informatics with Multi-Task Learning Christopher Künneth, Arunkumar Chitteth Rajan, Huan Tran, Lihua Chen, Chiho Kim, Rampi Ramprasad 2020-10-28 http://arxiv.org/pdf/2010.15166v1
Theory and implementation of inelastic Constitutive Artificial Neural Networks Hagen Holthusen, Lukas Lamm, Tim Brepols, Stefanie Reese, Ellen Kuhl 2023-11-10 http://arxiv.org/pdf/2311.06380v1
A Temporal Filter to Extract Doped Conducting Polymer Information Features from an Electronic Nose Wiem Haj Ammar, Aicha Boujnah, Antoine Baron, Aimen Boubaker, Adel Kalboussi, Kamal Lmimouni, Sebastien Pecqueur 2024-01-01 http://arxiv.org/pdf/2401.00684v1
Computational Discovery of Microstructured Composites with Optimal Stiffness-Toughness Trade-Offs Beichen Li, Bolei Deng, Wan Shou, Tae-Hyun Oh, Yuanming Hu, Yiyue Luo, Liang Shi, Wojciech Matusik 2023-02-01 http://arxiv.org/pdf/2302.01078v2
POINT$^{2}$: A Polymer Informatics Training and Testing Database Jiaxin Xu, Gang Liu, Ruilan Guo, Meng Jiang, Tengfei Luo 2025-03-30 http://arxiv.org/pdf/2503.23491v1
A Comprehensive and Versatile Multimodal Deep Learning Approach for Predicting Diverse Properties of Advanced Materials Shun Muroga, Yasuaki Miki, Kenji Hata 2023-03-29 http://arxiv.org/pdf/2303.16412v1
Deep Learning Approaches for Dynamic Mechanical Analysis of Viscoelastic Fiber Composites Victor Hoffmann, Ilias Nahmed, Parisa Rastin, Guénaël Cabanes, Julien Boisse 2023-10-20 http://arxiv.org/pdf/2310.15188v1
Bioplastic Design using Multitask Deep Neural Networks Christopher Kuenneth, Jessica Lalonde, Babetta L. Marrone, Carl N. Iverson, Rampi Ramprasad, Ghanshyam Pilania 2022-03-22 http://arxiv.org/pdf/2203.12033v1
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics Christopher Kuenneth, Rampi Ramprasad 2022-09-29 http://arxiv.org/pdf/2209.14803v1
polyGen: A Learning Framework for Atomic-level Polymer Structure Generation Ayush Jain, Rampi Ramprasad 2025-04-24 http://arxiv.org/pdf/2504.17656v3
Multimodal machine learning with large language embedding model for polymer property prediction Tianren Zhang, Dai-Bei Yang 2025-03-29 http://arxiv.org/pdf/2503.22962v2
Polymer Data Challenges in the AI Era: Bridging Gaps for Next-Generation Energy Materials Ying Zhao, Guanhua Chen, Jie Liu 2025-05-15 http://arxiv.org/pdf/2505.13494v1
Extrapolative ML Models for Copolymers Israrul H. Hashmi, Himanshu, Rahul Karmakar, Tarak K Patra 2024-09-15 http://arxiv.org/pdf/2409.09691v1
Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties Tian Xie, Arthur France-Lanord, Yanming Wang, Jeffrey Lopez, Michael Austin Stolberg, Megan Hill, Graham Michael Leverick, Rafael Gomez-Bombarelli, Jeremiah A. Johnson, Yang Shao-Horn, Jeffrey C. Grossman 2021-01-13 http://arxiv.org/pdf/2101.05339v2
Exploring the 3D architectures of deep material network in data-driven multiscale mechanics Zeliang Liu, C. T. Wu 2019-01-02 http://arxiv.org/pdf/1901.04832v3
Machine Learning 1- and 2-electron reduced density matrices of polymeric molecules David Pekker, Chungwen Liang, Sankha Pattanayak, Swagatam Mukhopadhyay 2022-08-09 http://arxiv.org/pdf/2208.04976v1
Machine learning enables polymer cloud-point engineering via inverse design Jatin N. Kumar, Qianxiao Li, Karen Y. T. Tang, Tonio Buonassisi, Anibal L. Gonzalez-Oyarce, Jun Ye 2018-11-21 http://arxiv.org/pdf/1812.11212v1
Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction Julian Konrad, Janina Mittelhaus, David M. Wilkins, Bodo Fiedler, Robert Meißner 2025-09-18 http://arxiv.org/pdf/2509.16266v2
Interpretable Spectral Features Predict Conductivity in Self-Driving Doped Conjugated Polymer Labs Ankush Kumar Mishra, Jacob P. Mauthe, Nicholas Luke, Aram Amassian, Baskar Ganapathysubramanian 2025-09-06 http://arxiv.org/pdf/2509.21330v1
Machine Learning for Analyzing Atomic Force Microscopy (AFM) Images Generated from Polymer Blends Aanish Paruchuri, Yunfei Wang, Xiaodan Gu, Arthi Jayaraman 2024-09-15 http://arxiv.org/pdf/2409.11438v2
Polygrammar: Grammar for Digital Polymer Representation and Generation Minghao Guo, Wan Shou, Liane Makatura, Timothy Erps, Michael Foshey, Wojciech Matusik 2021-05-05 http://arxiv.org/pdf/2105.05278v1
Reducing Data Requirements for Sequence-Property Prediction in Copolymer Compatibilizers via Deep Neural Network Tuning Md Mushfiqul Islam, Nishat N. Labiba, Lawrence O. Hall, David S. Simmons 2025-07-29 http://arxiv.org/pdf/2507.21902v1
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains Qiaohao Liang, Aldair E. Gongora, Zekun Ren, Armi Tiihonen, Zhe Liu, Shijing Sun, James R. Deneault, Daniil Bash, Flore Mekki-Berrada, Saif A. Khan, Kedar Hippalgaonkar, Benji Maruyama, Keith A. Brown, John Fisher III, Tonio Buonassisi 2021-05-23 http://arxiv.org/pdf/2106.01309v1
Viscoelastic Constitutive Artificial Neural Networks (vCANNs) $-$ a framework for data-driven anisotropic nonlinear finite viscoelasticity Kian P. Abdolazizi, Kevin Linka, Christian J. Cyron 2023-03-21 http://arxiv.org/pdf/2303.12164v1
AI-Driven Discovery of High Performance Polymer Electrodes for Next-Generation Batteries Subhash V. S. Ganti, Lukas Woelfel, Christopher Kuenneth 2025-02-19 http://arxiv.org/pdf/2502.13899v1
Explainable machine learning to enable high-throughput electrical conductivity optimization and discovery of doped conjugated polymers Ji Wei Yoon, Adithya Kumar, Pawan Kumar, Kedar Hippalgaonkar, J Senthilnath, Vijila Chellappan 2023-08-08 http://arxiv.org/pdf/2308.04103v2
A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations Tian Xie, Ha-Kyung Kwon, Daniel Schweigert, Sheng Gong, Arthur France-Lanord, Arash Khajeh, Emily Crabb, Michael Puzon, Chris Fajardo, Will Powelson, Yang Shao-Horn, Jeffrey C. Grossman 2022-08-02 http://arxiv.org/pdf/2208.01692v1
Unifying Mixed Gas Adsorption in Molecular Sieve Membranes and MOFs using Machine Learning Subhadeep Dasgupta, Amal R S, Prabal K. Maiti 2024-06-19 http://arxiv.org/pdf/2406.13389v1
Multi-objective Bayesian Optimization with Human-in-the-Loop for Flexible Neuromorphic Electronics Fabrication Benius Dunn, Javier Meza-Arroyo, Armi Tiihonen, Mark Lee, Julia W. P. Hsu 2025-10-08 http://arxiv.org/pdf/2510.11727v1
Mono/Multi-material Characterization Using Hyperspectral Images and Multi-Block Non-Negative Matrix Factorization Mahdiyeh Ghaffari, Gerjen H. Tinnevelt, Marcel C. P. van Eijk, Stanislav Podchezertsev, Geert J. Postma, Jeroen J. Jansen 2023-08-15 http://arxiv.org/pdf/2309.12329v1
Data-Centric Mixed-Variable Bayesian Optimization For Materials Design Akshay Iyer, Yichi Zhang, Aditya Prasad, Siyu Tao, Yixing Wang, Linda Schadler, L Catherine Brinson, Wei Chen 2019-07-04 http://arxiv.org/pdf/1907.02577v1
Unified Cross-Scale 3D Generation and Understanding via Autoregressive Modeling Shuqi Lu, Haowei Lin, Lin Yao, Zhifeng Gao, Xiaohong Ji, Yitao Liang, Weinan E, Linfeng Zhang, Guolin Ke 2025-03-20 http://arxiv.org/pdf/2503.16278v3
Polymer informatics at-scale with multitask graph neural networks Rishi Gurnani, Christopher Kuenneth, Aubrey Toland, Rampi Ramprasad 2022-09-27 http://arxiv.org/pdf/2209.13557v2
Machine Learning and Polymer Self-Consistent Field Theory in Two Spatial Dimensions Yao Xuan, Kris T. Delaney, Hector D. Ceniceros, Glenn H. Fredrickson 2022-12-16 http://arxiv.org/pdf/2212.10478v2
Deep Learning Order Parameter for Polymer Phase Transition Debjyoti Bhattacharya, Tarak K Patra 2021-02-24 http://arxiv.org/pdf/2102.12009v1
Gas permeability, diffusivity, and solubility in polymers: Simulation-experiment data fusion and multi-task machine learning Brandon K. Phan, Kuan-Hsuan Shen, Rishi Gurnani, Huan Tran, Ryan Lively, Rampi Ramprasad 2024-06-21 http://arxiv.org/pdf/2406.14809v1
nanoNET: Machine Learning Platform for Predicting Nanoparticles Distribution in a Polymer Matrix Kumar Ayush, Abhishek Seth, Tarak K Patra 2022-08-24 http://arxiv.org/pdf/2208.11448v1
Feature-based prediction of properties of cross-linked epoxy polymers by molecular dynamics and machine learning techniques Sindu B. S., Jan Hamaekers 2023-12-12 http://arxiv.org/pdf/2312.07149v2
dPOLY: Deep Learning of Polymer Phases and Phase Transition Debjyoti Bhattacharya, Tarak K Patra 2020-12-06 http://arxiv.org/pdf/2012.03184v1
Descriptor and Graph-based Molecular Representations in Prediction of Copolymer Properties Using Machine Learning Elaheh Kazemi-Khasragh, Rocío Mercado, Carlos Gonzalez, Maciej Haranczyk 2025-09-15 http://arxiv.org/pdf/2509.11874v1
Machine Learning on Neutron and X-Ray Scattering Zhantao Chen, Nina Andrejevic, Nathan Drucker, Thanh Nguyen, R Patrick Xian, Tess Smidt, Yao Wang, Ralph Ernstorfer, Alan Tennant, Maria Chan, Mingda Li 2021-02-05 http://arxiv.org/pdf/2102.03024v1
EllipBench: A Large-scale Benchmark for Machine-learning based Ellipsometry Modeling Yiming Ma, Xinjie Li, Xin Sun, Zhiyong Wang, Lionel Z. Wang 2024-07-25 http://arxiv.org/pdf/2407.17869v1
Deep Learning Potential of Mean Force between Polymer Grafted Nanoparticles Sachin Gautham, Tarak Patra 2022-07-18 http://arxiv.org/pdf/2207.08681v1
Deep Learning Interatomic Potential Connects Molecular Structural Ordering to Macroscale Properties of Polyacrylonitrile (PAN) Polymer Rajni Chahal, Michael D. Toomey, Logan T. Kearney, Ada Sedova, Joshua T. Damron, Amit K. Naskar, Santanu Roy 2024-04-24 http://arxiv.org/pdf/2404.16187v1
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning Reza Sepasdar, Anuj Karpatne, Maryam Shakiba 2021-04-09 http://arxiv.org/pdf/2104.04485v1
Machine Learning-Assisted Exploration of Thermally Conductive Polymers Based on High-Throughput Molecular Dynamics Simulations Ruimin Ma, Hanfeng Zhang, Jiaxin Xu, Yoshihiro Hayashi, Ryo Yoshida, Junichiro Shiomi, Tengfei Luo 2021-09-07 http://arxiv.org/pdf/2109.02794v1
Polymer Sequence Design via Active Learning Praneeth S Ramesh, Tarak K Patra 2021-11-18 http://arxiv.org/pdf/2111.09659v1
Electronic Defects in Metal Oxide Photocatalysts Ernest Pastor, Michael Sachs, Shababa Selim, James R. Durrant, Artem A. Bakulin, Aron Walsh 2022-01-08 http://arxiv.org/pdf/2201.02808v1
Deep Learning for Quantitative Dynamic Fragmentation Analysis Erwin Cazares, Brian E. Schuster 2024-07-17 http://arxiv.org/pdf/2407.12972v1
PolyCL: Contrastive Learning for Polymer Representation Learning via Explicit and Implicit Augmentations Jiajun Zhou, Yijie Yang, Austin M. Mroz, Kim E. Jelfs 2024-08-14 http://arxiv.org/pdf/2408.07556v1
Spinodal Surface Fluctuations on Polymer Films Y. J. Wang, Ophelia K. C. Tsui 2005-08-14 http://arxiv.org/pdf/cond-mat/0508339v1
Charge Trapping in Ferroelectric Polymers A. F. Butenko 2009-02-25 http://arxiv.org/pdf/0902.4473v1
Reinforcement Feature Transformation for Polymer Property Performance Prediction Xuanming Hu, Dongjie Wang, Wangyang Ying, Yanjie Fu 2024-09-23 http://arxiv.org/pdf/2409.15616v1
Machine Learning of polymer types from the spectral signature of Raman spectroscopy microplastics data Sheela Ramanna, Danila Morozovskii, Sam Swanson, Jennifer Bruneau 2022-01-14 http://arxiv.org/pdf/2201.05445v1
Machine Learning Inversion from Small-Angle Scattering for Charged Polymers Lijie Ding, Chi-Huan Tung, Jan-Michael Y. Carrillo, Wei-Ren Chen, Changwoo Do 2025-01-24 http://arxiv.org/pdf/2501.14647v1
Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures Manav Ramprasad, Chiho Kim 2019-08-06 http://arxiv.org/pdf/1908.02398v1
SPACIER: On-Demand Polymer Design with Fully Automated All-Atom Classical Molecular Dynamics Integrated into Machine Learning Pipelines Shun Nanjo, Arifin, Hayato Maeda, Yoshihiro Hayashi, Kan Hatakeyama-Sato, Ryoji Himeno, Teruaki Hayakawa, Ryo Yoshida 2024-08-09 http://arxiv.org/pdf/2408.05135v1
Quantitative calculations of the excitonic energy spectra of semiconducting single-walled carbon nanotubes within a $π$-electron model Zhendong Wang, Hongbo Zhao, Sumit Mazumdar 2006-06-02 http://arxiv.org/pdf/cond-mat/0606077v1
Calibrating constitutive models with full-field data via physics informed neural networks Craig M. Hamel, Kevin N. Long, Sharlotte L. B. Kramer 2022-03-30 http://arxiv.org/pdf/2203.16577v1
Joint Embedding Predictive Architecture for self-supervised pretraining on polymer molecular graphs Francesco Piccoli, Gabriel Vogel, Jana M. Weber 2025-06-22 http://arxiv.org/pdf/2506.18194v1
Polymer Composites Informatics for Flammability, Thermal, Mechanical and Electrical Property Predictions Huan Tran, Chiho Kim, Rishi Gurnani, Oliver Hvidsten, Justin DeSimpliciis, Rampi Ramprasad, Karim Gadelrab, Charles Tuffile, Nicola Molinari, Daniil Kitchaev, Mordechai Kornbluth 2024-12-11 http://arxiv.org/pdf/2412.08407v1
Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter, Wei-Ren Chen, Changwoo Do 2025-03-11 http://arxiv.org/pdf/2503.08913v1
Preparation of Metal Mixed Plastic Superconductors: Electrical Properties of Tin-Antimony Thin Films on Plastic Substrates Andrew P. Stephenson, Ujjual Divakar, Adam P. Micolich, Paul Meredith, Ben J. Powell 2008-09-24 http://arxiv.org/pdf/0809.4096v2
Metallic Oxides and the Overlooked Role of Bandwidth Aurland K. Watkins, Anthony K. Cheetham, Ram Seshadri 2025-10-01 http://arxiv.org/pdf/2510.00424v1
Modelling and simulation of adhesive curing processes in bonded piezo metal composites Ralf Landgraf, Martin Rudolph, Robert Scherzer, Jörn Ihlemann 2013-10-30 http://arxiv.org/pdf/1310.8264v2
Band bending at the interface in Polyethylene-MgO nanocomposite dielectric Elena Kubyshkina, Mikael Unge, B. L. G. Jonsson 2016-11-30 http://arxiv.org/pdf/1611.10251v1
Defect detection in glass fabric reinforced thermoplastics by laboratory-based X-ray scattering Özgül Öztürk, Rolf Brönnimann, Peter Modregger 2022-06-25 http://arxiv.org/pdf/2206.12607v2
Optical properties of Ag-doped polyvinyl alcohol nanocomposites: a statistical analysis of the film thickness effect on the resonance parameters Corentin Guyot, Michel Voué 2015-06-04 http://arxiv.org/pdf/1506.01581v1
Direct Testing of Gradual PostPeak Softening of Notched Specimens of Fiber Composites Stabilized by Enhanced Stiffness and Mass Zdenek P. Bazant, Viet T. Chau, Gianluca Cusatis, Marco Salviato 2016-07-04 http://arxiv.org/pdf/1607.00741v1
Active Learning and Explainable AI for Multi-Objective Optimization of Spin Coated Polymers Brendan Young, Brendan Alvey, Andreas Werbrouck, Will Murphy, James Keller, Mattias J. Young, Matthew Maschmann 2025-09-10 http://arxiv.org/pdf/2509.08988v1
Organic nanofibers embedding stimuli-responsive threaded molecular components Vito Fasano, Massimo Baroncini, Maria Moffa, Donata Iandolo, Andrea Camposeo, Alberto Credi, Dario Pisignano 2014-10-08 http://arxiv.org/pdf/1410.2009v2
A Method for Inferring Polymers Based on Linear Regression and Integer Programming Ryota Ido, Shengjuan Cao, Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu 2021-08-24 http://arxiv.org/pdf/2109.02628v1
PolyGET: Accelerating Polymer Simulations by Accurate and Generalizable Forcefield with Equivariant Transformer Rui Feng, Huan Tran, Aubrey Toland, Binghong Chen, Qi Zhu, Rampi Ramprasad, Chao Zhang 2023-09-01 http://arxiv.org/pdf/2309.00585v1
Understanding Creep Suppression Mechanism in Polymer Nanocomposites through Machine Learning Entao Yang, James F. Pressly, Bharath Natarajan, Robert Colby, Karen I. Winey, Robert A. Riggleman 2022-04-25 http://arxiv.org/pdf/2204.11996v1
Reactive Two-Step Additive Manufacturing of Ultra-high Temperature Carbide Ceramics Adam B. Peters, Dajie Zhang, Dennis C. Nagle, James B. Spicer 2022-07-29 http://arxiv.org/pdf/2208.00052v3
Quantitative Prediction of Fracture Toughness $(K_{{\rm I}c})$ of Polymer by Fractography Using Deep Neural Networks Yoh-ichi Mototake, Kaita Ito, Masahiko Demura 2022-04-29 http://arxiv.org/pdf/2204.13912v1
Machine Learning-Assisted Profiling of Ladder Polymer Structure using Scattering Lijie Ding, Chi-Huan Tung, Zhiqiang Cao, Zekun Ye, Xiaodan Gu, Yan Xia, Wei-Ren Chen, Changwoo Do 2024-10-31 http://arxiv.org/pdf/2411.00134v1
Machine Learning for Polymer Chemical Resistance to Organic Solvents Shogo Kunieda, Mitsuru Yambe, Hiromori Murashima, Takeru Nakamura, Toshiaki Shintani, Hitoshi Kamijima, Yoshihiro Hayashi, Yosuke Hanawa, Ryo Yoshida 2025-09-02 http://arxiv.org/pdf/2509.05344v1
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors Xiang Huang, Shengluo Ma, C. Y. Zhao, Hong Wang, Shenghong Ju 2023-01-08 http://arxiv.org/pdf/2301.03030v1
Toward Sustainable Polymer Design: A Molecular Dynamics-Informed Machine Learning Approach for Vitrimers Yiwen Zheng, Agni K. Biswal, Yaqi Guo, Prakash Thakolkaran, Yash Kokane, Vikas Varshney, Siddhant Kumar, Aniruddh Vashisth 2025-03-26 http://arxiv.org/pdf/2503.20956v1
RAAD-LLM: Adaptive Anomaly Detection Using LLMs and RAG Integration Alicia Russell-Gilbert, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jabour, Thomas Arnold, Joshua Church 2025-03-04 http://arxiv.org/pdf/2503.02800v3
Impact of buckypaper on the mechanical properties and failure modes of composites Kartik Tripathi, Mohamed H. Hamza, Aditi Chattopadhyay, Todd C. Henry, Asha Hall 2025-03-13 http://arxiv.org/pdf/2503.10073v1
An Informatics Framework for the Design of Sustainable, Chemically Recyclable, Synthetically-Accessible and Durable Polymers Joseph Kern, Yongliang Su, Will Gutekunst, Rampi Ramprasad 2024-09-13 http://arxiv.org/pdf/2409.15354v1
Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures Nhat Khang Ngo, Truong Son Hy, Risi Kondor 2023-02-17 http://arxiv.org/pdf/2302.08647v4
DeePN$^2$: A deep learning-based non-Newtonian hydrodynamic model Lidong Fang, Pei Ge, Lei Zhang, Weinan E, Huan Lei 2021-12-29 http://arxiv.org/pdf/2112.14798v3
TransPolymer: a Transformer-based language model for polymer property predictions Changwen Xu, Yuyang Wang, Amir Barati Farimani 2022-09-03 http://arxiv.org/pdf/2209.01307v4
Artificial Neural Networks for Predicting Mechanical Properties of Crystalline Polyamide12 via Molecular Dynamics Simulations Caglar Tamur, Shaofan Li, Danielle Zeng 2023-07-19 http://arxiv.org/pdf/2307.10139v3
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