4.2 Article

Bioplastic design using multitask deep neural networks

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Chemistry, Physical

Machine Learning for Melting Temperature Predictions and Design in Polyhydroxyalkanoate-Based Biopolymers

Karteek K. Bejagam et al.

Summary: This article discusses the potential of using machine learning techniques to establish efficient structure-property mappings in the chemical space of PHAs. An example of predicting melting temperature is used to demonstrate the promise of this approach.

JOURNAL OF PHYSICAL CHEMISTRY B (2022)

Article Polymer Science

Predicting the Mechanical Response of Polyhydroxyalkanoate Biopolymers Using Molecular Dynamics Simulations

Karteek K. Bejagam et al.

Summary: Polyhydroxyalkanoates (PHAs) are promising biosynthesizable, biocompatible, and biodegradable polymers that can replace petroleum-based plastics to address plastic pollution. However, the structure-property relationships and experimental data on the mechanical properties of PHAs are limited. In this study, molecular dynamics simulations were used to predict the mechanical properties of PHAs. The results show that Young's modulus and yield stress decrease with increasing carbon atom number in the side chain and polymer backbone. The mechanical properties are also strongly correlated with the chemical nature of the functional group.

POLYMERS (2022)

Review Nanoscience & Nanotechnology

Bioplastics for a circular economy

Jan-Georg Rosenboom et al.

Summary: Bioplastics have the potential to contribute to a more sustainable and circular economy by reducing carbon footprint and offering advantageous material properties. However, they also face challenges such as negative agricultural impacts, competition with food production, unclear end-of-life management, and higher costs. Emerging chemical and biological methods can enable the upcycling of plastic waste into higher-quality materials. Standardization and guidelines are needed to guide purchasing choices, and clear regulations and financial incentives are essential for the large-scale adoption of bioplastics in a truly sustainable manner.

NATURE REVIEWS MATERIALS (2022)

Article Multidisciplinary Sciences

Machine learning strategies for the structure-property relationship of copolymers

Lei Tao et al.

Summary: Establishing the structure-property relationship is crucial for molecular design of copolymers. Machine learning models that consider both chemical composition and sequence distribution of monomers, and have the ability to process different types of copolymers, are needed. In this study, we propose four different machine learning models and find that a recurrent neural network (RNN) architecture that processes monomer sequence information in both forward and backward directions performs better for copolymers.

ISCIENCE (2022)

Review Biotechnology & Applied Microbiology

A New Wave of Industrialization of PHA Biopolyesters

Martin Koller et al.

Summary: The increasing use of plastics and their negative impact on the environment has led to the development of renewable and biodegradable materials. Polyhydroxyalkanoates (PHAs), a class of biopolymers synthesized by microorganisms, have properties similar to petrochemical plastics but can biodegrade in various environments. The emergence of the PHA industry has attracted the attention of chemical companies, start-ups, and brand owners who are now producing and utilizing PHAs in various applications. This commercialization wave of PHAs holds great potential in reducing plastic pollution and fighting climate change.

BIOENGINEERING-BASEL (2022)

Article Polymer Science

Polyhydroxyalkanoate (PHA): Properties and Modifications

Vibhuti Sharma et al.

Summary: PHA is gaining attention for its biodegradability, biocompatibility, and hydrophobic properties, but it also has limitations in competing with synthetic polymers. To overcome these limitations and improve its properties for potential applications in various fields, different modification methods are being researched, such as physical blending, chemical modification, and biological modification.

POLYMER (2021)

Article Chemistry, Medicinal

Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature

Lei Tao et al.

Summary: The utilization of machine learning techniques in polymer informatics for evaluating properties such as glass transition temperature (T-g) has gained significant attention. A benchmark study was conducted to compare different ML models and explore key factors affecting the prediction of T-g, including structure representations, feature representations, and ML algorithms. This study not only provides guidance for Tg prediction, but also serves as a valuable reference for other polymer informatics tasks.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)

Article Chemistry, Multidisciplinary

Hybrid monomer design for unifying conflicting polymerizability, recyclability, and performance properties

Changxia Shi et al.

Summary: The article introduces a new hybrid monomer design strategy that combines high ceiling temperature (HCT) and low ceiling temperature (LCT) sub-structures within the same monomer to achieve high polymerizability and depolymerizability. This innovative approach resulted in a polymer with high performance properties, demonstrating that the HCT/LCT hybrid monomer strategy is a powerful method for designing circular polymers with conflicting properties.
Review Materials Science, Multidisciplinary

Polymer informatics: Current status and critical next steps

Lihua Chen et al.

Summary: Artificial intelligence is making significant impact in the field of polymer informatics, with surrogate models being trained on polymer data for instant property prediction. Challenges include lack of curated data availability and the need for machine-readable representations capturing the complexity of polymer structures.

MATERIALS SCIENCE & ENGINEERING R-REPORTS (2021)

News Item Multidisciplinary Sciences

MICROPLASTICS ARE EVERYWHERE - BUT ARE THEY HARMFUL?

XiaoZhi Lim

Summary: Scientists are urgently studying the tiny plastic specks found in marine animals and in humans.

NATURE (2021)

Article Multidisciplinary Sciences

Bias free multiobjective active learning for materials design and discovery

Kevin Maik Jablonka et al.

Summary: This study utilizes an active learning algorithm and Pareto dominance relation to compute a set of Pareto optimal materials for multi-objective material design. By conducting molecular simulations, the number of materials that need to be evaluated is drastically reduced, enhancing design efficiency.

NATURE COMMUNICATIONS (2021)

Article Chemistry, Multidisciplinary

Roadmap to Biodegradable Plastics-Current State and Research Needs

Koushik Ghosh et al.

Summary: Plastics, though ubiquitous in daily life and environment, require consideration for their impact on the ecological milieu. While biodegradable plastics offer appeal in returning carbon to ecosystems, they have yet to replace conventional plastics commercially, necessitating collaboration for success.

ACS SUSTAINABLE CHEMISTRY & ENGINEERING (2021)

Review Engineering, Environmental

Knowledge Gaps in Polymer Biodegradation Research

Vurtice C. Albright et al.

Summary: The environmental fate of polymers, especially biodegradable ones, is receiving increasing attention. Key aspects of study design are crucial for determining the outcomes of polymer biodegradation research. Overcoming knowledge gaps and providing key recommendations are necessary for assessing polymer biodegradation effectively.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2021)

Article Engineering, Environmental

Machine Learning: New Ideas and Tools in Environmental Science and Engineering

Shifa Zhong et al.

Summary: The article discusses the potential of machine learning to revolutionize data analysis in the field of environmental science and engineering, covering applications and considerations.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2021)

Article Polymer Science

Composition and Configuration Dependence of Glass-Transition Temperature in Binary Copolymers and Blends of Polyhydroxyalkanoate Biopolymers

Karteek K. Bejagam et al.

Summary: Polyhydroxyalkanoates (PHAs) are a class of biomaterials with excellent biocompatibility and biodegradability, which have gained attention as substitutes for petroleum-based plastics. However, the composition and configuration dependence of properties in the vast PHA copolymer chemical space remains largely unexplored.

MACROMOLECULES (2021)

Article Polymer Science

Copolymer Informatics with Multitask Deep Neural Networks

Christopher Kuenneth et al.

Summary: Polymer informatics tools are increasingly used to develop new polymers efficiently, with a recent focus on homopolymers. This study introduces a copolymer property prediction method utilizing advanced polymer fingerprinting and deep-learning schemes.

MACROMOLECULES (2021)

Review Polymer Science

Review of Hybrid Materials Based on Polyhydroxyalkanoates for Tissue Engineering Applications

Artyom Pryadko et al.

Summary: This review focuses on hybrid polyhydroxyalkanoate-based biomaterials for tissue engineering applications, which have improved physico-mechanical, chemical, and piezoelectric properties, as well as controlled biodegradation rate. PHAs are biodegradable, biocompatible, and piezoelectric polymers derived from a wide range of bacteria, making them attractive for various biomedical applications. The chemical structure of PHAs allows for the formation of hybrid composites with improved properties, and research is ongoing to optimize their performance for tissue regeneration.

POLYMERS (2021)

Article Polymer Science

Predicting Polymers' Glass Transition Temperature by a Chemical Language Processing Model

Guang Chen et al.

Summary: A chemical language processing model was proposed to predict the glass transition temperature (Tg) of polymers using SMILES strings. The model showed reasonable prediction performance on unseen polymer Tg and was used for high-throughput screening of high-temperature polymers.

POLYMERS (2021)

Article Physics, Applied

Data-assisted polymer retrosynthesis planning

Lihua Chen et al.

Summary: Polymer informatics is used to speed up polymer discovery, but challenges in synthesis still exist. Researchers have developed a data-driven approach to assist in polymer retrosynthesis planning, aiming to expedite the synthesis process.

APPLIED PHYSICS REVIEWS (2021)

Review Chemistry, Multidisciplinary

Poly(lactic acid) (PLA) and polyhydroxyalkanoates (PHAs), green alternatives to petroleum-based plastics: a review

Ahmed Z. Naser et al.

Summary: Petroleum-based plastics have significant negative impacts on the environment, leading to a growing interest in alternative materials like bio-based polymers such as PLA and PHAs. The drive to reduce dependence on fossil fuels and address concerns about natural resource preservation and climate change has pushed researchers to explore the feasibility of these alternative materials. This paper provides an overview of the properties, recyclability, sustainability, and potential applications of PLA and PHAs as replacements for petroleum-based plastics.

RSC ADVANCES (2021)

Article Computer Science, Artificial Intelligence

Polymer informatics with multi-task learning

Christopher Kuenneth et al.

Summary: Modern data-driven tools are transforming the development cycles of application-specific polymers, with multi-task learning approaches effectively utilizing inherent correlations within datasets to open up new design possibilities for specific application polymers.

PATTERNS (2021)

Review Nanoscience & Nanotechnology

Emerging materials intelligence ecosystems propelled by machine learning

Rohit Batra et al.

Summary: The age of cognitive computing and artificial intelligence is emerging, with AI ecosystems flourishing in materials science and engineering. Machine learning algorithms are utilized to create surrogate models of materials properties, transforming the computational and physical laboratory infrastructural landscapes. Integration of various ML landscape parts may lead to materials-savvy digital assistants and human-machine partnerships for efficient materials screening and discovery.

NATURE REVIEWS MATERIALS (2021)

Article Chemistry, Multidisciplinary

Biodegradable Polyhydroxyalkanoates by Stereoselective Copolymerization of Racemic Diolides: Stereocontrol and Polyolefin-Like Properties

Xiaoyan Tang et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2020)

Review Biotechnology & Applied Microbiology

Polyester-based biodegradable plastics: an approach towards sustainable development

S. M. Satti et al.

LETTERS IN APPLIED MICROBIOLOGY (2020)

Article Multidisciplinary Sciences

Designing exceptional gas-separation polymer membranes using machine learning

J. Wesley Barnett et al.

SCIENCE ADVANCES (2020)

Article Physics, Applied

Machine-learning predictions of polymer properties with Polymer Genome

Huan Doan Tran et al.

JOURNAL OF APPLIED PHYSICS (2020)

Article Chemistry, Physical

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Karteek K. Bejagam et al.

PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2020)

Article Polymer Science

Polymerization of ε-caprolactone with degraded PET for its functionalization

Karina Espinoza-Garcia et al.

JOURNAL OF POLYMER RESEARCH (2019)

Article Materials Science, Multidisciplinary

Active-learning and materials design: the example of high glass transition temperature polymers

Chiho Kim et al.

MRS COMMUNICATIONS (2019)

Article Chemistry, Medicinal

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers

Ghanshyam Pilania et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)

Article Materials Science, Multidisciplinary

Impact of dataset uncertainties on machine learning model predictions: the example of polymer glass transition temperatures

Anurag Jha et al.

MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2019)

Article Multidisciplinary Sciences

Soft Matter Informatics: Current Progress and Challenges

James S. Peerless et al.

ADVANCED THEORY AND SIMULATIONS (2019)

Article Chemistry, Physical

Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions

Chiho Kim et al.

JOURNAL OF PHYSICAL CHEMISTRY C (2018)

Review Polymer Science

Biosynthesis and Characteristics of Aromatic Polyhydroxyalkanoates

Manami Ishii-Hyakutake et al.

POLYMERS (2018)

Article Polymer Science

Polymer Informatics: Opportunities and Challenges

Debra J. Audus et al.

ACS MACRO LETTERS (2017)

Article Multidisciplinary Sciences

Production, use, and fate of all plastics ever made

Roland Geyer et al.

SCIENCE ADVANCES (2017)

Review Chemistry, Physical

Machine learning in materials informatics: recent applications and prospects

Rampi Ramprasad et al.

NPJ COMPUTATIONAL MATERIALS (2017)

Article Multidisciplinary Sciences

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

Arun Mannodi-Kanakkithodi et al.

SCIENTIFIC REPORTS (2016)

Article Polymer Science

Synthesis and Characterization of Aliphatic-Aromatic Copolyesters From Pet Waste and ε-Caprolactone

M. Ben Gara et al.

JOURNAL OF MACROMOLECULAR SCIENCE PART A-PURE AND APPLIED CHEMISTRY (2015)

Article Materials Science, Multidisciplinary

Accelerated materials property predictions and design using motif-based fingerprints

Tran Doan Huan et al.

PHYSICAL REVIEW B (2015)

Article Chemistry, Physical

Structure and Barrier Properties of Biodegradable Polyhydroxyalkanoate Films

Nadege Follain et al.

JOURNAL OF PHYSICAL CHEMISTRY C (2014)

Review Chemistry, Multidisciplinary

Quantitative Structure-Property Relationship Modeling of Diverse Materials Properties

Tu Le et al.

CHEMICAL REVIEWS (2012)

Review Biochemistry & Molecular Biology

Topological Polar Surface Area: A Useful Descriptor in 2D-QSAR

S. Prasanna et al.

CURRENT MEDICINAL CHEMISTRY (2009)

Article Polymer Science

Engineering polymer informatics: Towards the computer-aided design of polymers

Nico Adams et al.

MACROMOLECULAR RAPID COMMUNICATIONS (2008)

Article Chemistry, Multidisciplinary

Ordered nanoporous polymers from polystyrene-polylactide block copolymers

AS Zalusky et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2002)

Review Polymer Science

Chemical syntheses of biodegradable polymers

M Okada

PROGRESS IN POLYMER SCIENCE (2002)