Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels

Schilling, Markus; Marschall, Niklas; Niebergall, Ute; Wachtendorf, Volker; Böhning, Martin

doi:10.1016/j.polymertesting.2024.108547

Polymer Testing

2024

DOI: 10.1016/j.polymertesting.2024.108547

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Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels

Markus Schilling,

Niklas Marschall,

Ute Niebergall

et al.

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Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review

Malashin,

Tynchenko,

Gantimurov

et al. 2024

Polymers

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This review explores the application of Long Short-Term Memory (LSTM) networks, a specialized type of recurrent neural network (RNN), in the field of polymeric sciences. LSTM networks have shown notable effectiveness in modeling sequential data and predicting time-series outcomes, which are essential for understanding complex molecular structures and dynamic processes in polymers. This review delves into the use of LSTM models for predicting polymer properties, monitoring polymerization processes, and evaluating the degradation and mechanical performance of polymers. Additionally, it addresses the challenges related to data availability and interpretability. Through various case studies and comparative analyses, the review demonstrates the effectiveness of LSTM networks in different polymer science applications. Future directions are also discussed, with an emphasis on real-time applications and the need for interdisciplinary collaboration. The goal of this review is to connect advanced machine learning (ML) techniques with polymer science, thereby promoting innovation and improving predictive capabilities in the field.

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Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review

Malashin,

Tynchenko,

Gantimurov

et al. 2024

Polymers

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels

Cited by 1 publication

References 42 publications

Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review

Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review

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