English
Related papers

Related papers: Informatics-Driven Selection of Polymers for Fuel-…

200 papers

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the…

Materials Science · Physics 2007-05-23 D. J. Scott , P. V. Coveney , J. A. Kilner , J. C. H. Rossiny , N. Mc N. Alford

The use of polymer nanocomposites as gas barrier materials has seen increasing interest, including applications involving hydrogen transport and storage. Better understanding of gas transport through those polymeric systems requires 3D…

The transport of water and protons in the cathode catalyst layer (CCL) of proton exchange membrane (PEM) fuel cells is critical for cell performance, but the underlying mechanism is still unclear. Herein, the ionomer structure and the…

Chemical Physics · Physics 2024-02-08 Yichao Huang , Panagiotis E. Theodorakis , Zhen Zeng , Tianyou Wang , Zhizhao Che

The morphology and transport properties of thin films of the ionomer Nafion, with thicknesses on the order of the bulk cluster size, have been investigated as a model system to explain the anomalous behaviour of catalyst/electrode-polymer…

Materials Science · Physics 2018-01-16 Peter Vanya , Jonathan Sharman , James A. Elliott

Widespread adoption of high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) and HT-PEM electrochemical hydrogen pumps (HT-PEM ECHPs) requires models and computational tools that provide accurate scale-up and optimization.…

Machine Learning · Computer Science 2022-03-01 Luis A. Briceno-Mena , Christopher G. Arges , Jose A. Romagnoli

The physio-chemical properties of Nafion 115 and a composite Nafion 115/Zirconium Phosphate (25wt%) membranes are compared. The composite membrane takes up more water than Nafion at the same water activity. However, the proton conductivity…

Chemical Physics · Physics 2007-05-23 Chris Yang , S. Srinivasan , A. B. Bocarsly , S. Tulyani , J. B. Benziger

Water produced in a Polymer Electrolyte Membrane (PEM) fuel cell enhances membrane proton conductivity; this positive feedback loop can lead to current ignition. Using a segmented anode fuel cell we study the effect of gas phase convection…

Pattern Formation and Solitons · Physics 2007-05-23 J. B. Benziger , E. -S. Chia , Y. De Decker , I. G. Kevrekidis

A central endeavour in bioelectronics is the development of logic elements to transduce and process ionic to electronic signals. Motivated by this challenge, we report fully monolithic, nanoscale logic elements featuring n- and p-type…

This article presents new hexagonal and pentagonal PEM fuel cell models. The models have been optimized after achieving improved cell performance. The input parameters of the multi-objective optimization algorithm were pressure and…

Neural and Evolutionary Computing · Computer Science 2023-10-18 Ali Jabbary , Nader Pourmahmoud , Mir Ali Asghar Abdollahi , Marc A. Rosen

The escalating global issue of plastic waste accumulation, specifically polyolefins, necessitates an urgent solution for upcycling these materials into beneficial compounds. Yet, achieving such upcycling without introducing carbon dioxide…

Applied Physics · Physics 2024-01-17 Yuexiang Sun , Xin Ma , Qiao Gu , Ping Gao

To discover novel materials with high performance, there have been many attempts to adopt Bayesian optimization (BO) to materials science, owing to its efficiency in navigating complex and high-dimensional design spaces. However, the…

Materials Science · Physics 2025-05-12 Sanghyeon Park , Yoonsu Shim , Junpyo Hur , Dongmin Jeon , Jong Min Yuk , Chan-Woo Lee

AI-powered autonomous experimentation (AI/AE) can accelerate materials discovery but its effectiveness for electronic materials is hindered by data scarcity from lengthy and complex design-fabricate-test-analyze cycles. Unlike experienced…

Polymers are increasingly used in the transport sector due to their many advantages; lightness, corrosion resistance, ease to process... However, most of them have limited mechanical properties. To improve these latter, one of the solutions…

Classical Physics · Physics 2024-04-23 Nicolas Raoux , Abdelkibir Benelfellah , Nourredine Aït Hocine

Field sensor networks have important applications in environmental monitoring, particularly climate change, air, water and soil quality, in disaster monitoring and in border security. The reduced cost of electronics, sensors and actuators…

Applied Physics · Physics 2017-10-10 Jekan Thangavelautham , Daniel Strawser , Steven Dubowsky

Recently there has been an increase in demand for soft and biocompatible electronic devices capable of withstanding large stretch. Ionically conductive polymers present a promising class of soft materials for these emerging applications due…

Soft Condensed Matter · Physics 2022-09-07 Nikola Bosnjak , Max Tepermeister , Meredith Silberstein

In this work, we develop a combined convolutional neural networks (CNNs) and finite element method (FEM) to examine the effective thermal properties of composite phase change materials (CPCMs) consisting of paraffin and copper foam. In this…

Computational Physics · Physics 2021-03-25 Felix Kolodziejczyk , Bohayra Mortazavi , Timon Rabczuk , Xiaoying Zhuang

Ammonia has strong poisoning effects on cathode catalyst layers of proton exchange membrane (PEM) fuel cells, but the poisoning mechanism is still unclear. In this study, all-atom molecular dynamics simulations are employed to investigate…

Chemical Physics · Physics 2026-05-13 Yichao Huang , Zhen Zeng , Tianyou Wang , Zhizhao Che

Properties of engineering materials are generally influenced by defects such as point defects (vacancies, interstitials, substitutional defects), line defects (dislocations), planar defects (grain boundaries, free surfaces/nanostructures,…

Materials Science · Physics 2016-05-27 Kamal Choudhary

Efficient screening of chemicals is essential for exploring new materials. However, the search space is astronomically large, making calculations with conventional computers infeasible. For example, an $N$-component system of organic…

Computational Physics · Physics 2021-01-13 Kan Hatakeyama-Sato , Takahiro Kashikawa , Koichi Kimura , Kenichi Oyaizu

Informatics-driven approaches, such as machine learning and sequential experimental design, have shown the potential to drastically impact next-generation materials discovery and design. In this perspective, we present a few guiding…