Article
Chemistry, Physical
Kaito Miyamoto, Scott R. Broderick, Krishna Rajan
Summary: Microbatteries are crucial for powering microelectronics in internet-of-things applications. This paper presents a data-driven 3D battery optimization system that combines automatic geometry generation and accurate performance simulation. The proposed method achieves significant improvements in efficiency and power density compared to existing approaches.
JOURNAL OF POWER SOURCES
(2022)
Article
Materials Science, Multidisciplinary
W. Trehern, R. Ortiz-Ayala, K. C. Atli, R. Arroyave, I. Karaman
Summary: An AI-enabled materials discovery framework was used to identify SMA chemistries and thermo-mechanical processing steps that result in narrow transformation hysteresis and range under applied stress. The framework successfully predicted and confirmed an SMA composition with the narrowest thermal hysteresis and transformation range achieved thus far for a NiTi-based SMA. The methodology and dataset introduced have the potential to design novel SMAs with other target functions.
Article
Energy & Fuels
Ali Malek, Qianpu Wang, Stefan Baumann, Olivier Guillon, Michael Eikerling, Kourosh Malek
Summary: In the search for next-generation electrocatalyst materials for electrochemical energy technologies, finding more active, selective, and stable materials for the CO2 reduction reaction is challenging and time-consuming. A material recommendation and screening framework has been introduced to recommend viable materials and reveal relevant correlations governing catalyst performance under different temperature conditions.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Clement Achille, Cesar Parra-Cabrera, Ruben Dochy, Henry Ordutowski, Agnese Piovesan, Pieter Piron, Lore Van Looy, Shashwat Kushwaha, Dominiek Reynaerts, Pieter Verboven, Bart Nicolai, Jeroen Lammertyn, Dragana Spasic, Rob Ameloot
Summary: Rapid diagnostic testing at the site of the patient is essential when a fully equipped laboratory is not accessible. 3D-printed microfluidic devices offer a scalable route to low-cost diagnostics and eliminate the need for assembly of discrete components. The seamless transition between digital data and physical objects allows for rapid design iterations and opens up perspectives on distributed manufacturing.
ADVANCED MATERIALS
(2021)
Article
Automation & Control Systems
Zhiwen Chen, Rongjie Guo, Zhi Lin, Tao Peng, Xia Peng
Summary: This article introduces a new data-driven health monitoring method using multiobjective optimization and stacked autoencoder for health indicator construction. Through simulation experiments, the proposed method accurately identifies equipment status and effectively reduces the complexity of the diagnostic model.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Nanoscience & Nanotechnology
Rangasayee Kannan, Peeyush Nandwana
Summary: The search for new alloys with improved properties is a continuous process with infinite combinations and amounts of alloying elements. Advancements in machine learning have made navigating this vast search space possible. However, training machine learning models and tuning their hyper-parameters to make accurate predictions can be time-consuming and require high-performance computing resources. In this study, a generic approach is presented to accelerate alloy discovery using high throughput CALPHAD calculations, synthetic data generation, and data mining. As a demonstration, super bainitic steels that form bainite at 200 degrees C in lower transformation times are designed.
SCRIPTA MATERIALIA
(2023)
Article
Materials Science, Multidisciplinary
Yonggang Yan, Yalin Liao, Kun Wang
Summary: This paper attempts to use a high-throughput experiments (HTEs) assisted data-driven strategy to predict the oxidation recession of transition metal diboride-SiC ceramic composites, aiming to accelerate the discovery of ultra-high temperature ceramics (UHTCs) with excellent oxidation resistance. The data generated by HTEs enables the application of machine learning (ML) method to discover novel oxidation-resistant UHTCs. The Artificial Neural Network (ANN) and Kernel logistic regression (KLR) models show outstanding performance compared to other ML models, and the trained KLR model rapidly identifies optimum compositions with exceptional oxidation resistance.
Article
Engineering, Mechanical
Xiaoqi Wang, Jianfu Cao, Ye Cao
Summary: This study aims to develop an adaptive layering algorithm that balances printing quality and efficiency. By using a multiobjective optimization model and an improved solution method, the adaptive layering can provide different results based on different needs. The proposed method outperforms other adaptive layering methods, as demonstrated through verification.
RAPID PROTOTYPING JOURNAL
(2023)
Article
Chemistry, Multidisciplinary
Wenjie Shang, Minxiang Zeng, A. N. M. Tanvir, Ke Wang, Mortaza Saeidi-Javash, Alexander Dowling, Tengfei Luo, Yanliang Zhang
Summary: A hybrid data-driven strategy combining Bayesian optimization and Gaussian process regression is proposed to optimize the composition of AgSe-based thermoelectric materials. Through active collection of experimental data, a significant improvement in material performance is achieved within seven iterations.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Jie Jin, Fangzhou Zhang, Yulong Yang, Chengqian Zhang, Haidong Wu, Yang Xu, Yong Chen
Summary: This article introduces a novel hybrid 3D printing technique that combines the strengths of vat photopolymerization and direct-ink-writing processes to achieve multimaterial and high-resolution printing of functional structures and devices. The method involves dispensing liquid-like materials into a photocurable matrix material and using a controlled laser beam to selectively photocure the dispensed material trace or the matrix material. The versatility of the method is demonstrated by fabricating intricate 3D prototypes using various materials available for vat photopolymerization and direct-ink-writing technologies.
Review
Dentistry, Oral Surgery & Medicine
Alvaro Della Bona, Viviane Cantelli, Vitor T. Britto, Kaue F. Collares, Jeffrey W. Stansbury
Summary: This systematic review analyzes studies on stereolithography-based 3D printing of restorative materials, highlighting the trend in dental restoration. The research focuses on the properties, methods, and clinical applicability of different materials, with limited studies applying 3D printed structures on patients, indicating a gap between research and clinical implementation.
Article
Engineering, Manufacturing
Abdul Wahab Ziaullah, Sanjay Chawla, Fedwa El-Mellouhi
Summary: Artificial intelligence is extensively used to optimize and discover new materials through data-driven search. One popular technique is Bayesian optimization, which incorporates a machine learning model to suggest suitable material candidates for further evaluation. In this work, we propose a batch optimization method using faux-data injection to speed up the material discovery process and maximize the utilization of high-performance computing.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
(2023)
Article
Multidisciplinary Sciences
Kevin Maik Jablonka, Giriprasad Melpatti Jothiappan, Shefang Wang, Berend Smit, Brian Yoo
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
Jiangang He, Yi Xia, Wenwen Lin, Koushik Pal, Yizhou Zhu, Mercouri G. Kanatzidis, Chris Wolverton
Summary: An effective strategy of weakening interatomic interactions and suppressing lattice thermal conductivity based on chemical bonding principles is presented, leading to the discovery of 30 compounds with (ultra)low lattice thermal conductivities by screening the local coordination environments of crystalline compounds. This work not only provides insights into the physical origin of low lattice thermal conductivity in a large family of copper/silver-based compounds, but also offers an efficient approach to discover and design materials with targeted thermal transport properties.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Engineering, Petroleum
Xiaopeng Ma, Kai Zhang, Timing Zhang, Chuanjin Yao, Jun Yao, Haochen Wang, Wang Jian, Yongfei Yan
Summary: The proposed algorithm effectively tackles the nonuniqueness of inversion by locating multiple solutions for complex multimodal problems within a limited computational budget. The integration of convolutional variational autoencoder for parameterization enhances the robustness of prediction results.
Article
Chemistry, Multidisciplinary
Bernhard von Vacano, Hannah Mangold, Christian Seitz
Summary: Plastics have seen significant growth in production in recent decades, leading to a waste management issue that can be addressed through circular economy principles. The key to sustainable plastic cycles lies in systematic consideration of every step, along with the development of dedicated recycling processes and innovations in material and product design.
CHEMIE IN UNSERER ZEIT
(2021)
Article
Computer Science, Software Engineering
Yifei Li, Tao Du, Kui Wu, Jie Xu, Wojciech Matusik
Summary: This work presents a differentiable cloth simulator that utilizes gradient information for cloth-related applications. A fast and novel method for obtaining gradients in PD-based cloth simulation with dry frictional contact is proposed. The usefulness of gradients in contact-rich cloth simulation is comprehensively analyzed and evaluated. The efficacy of the simulator is demonstrated in various downstream applications.
ACM TRANSACTIONS ON GRAPHICS
(2023)
Article
Polymer Science
Hannah Mangold, Bernhard von Vacano
Summary: Recycling is an important component of the circular economy to separate the value of materials from consumption. However, current recycling methods face challenges in effectively diverting waste towards reuse. Sustainable advancements are needed in the design of products and polymers, recycling technologies, business models, and enabling technologies to achieve circularity and greenhouse gas emission neutrality in the industry.
MACROMOLECULAR CHEMISTRY AND PHYSICS
(2022)
Article
Multidisciplinary Sciences
Stefan Muellers, Mara Florea-Huering, Bernhard von Vacano, Bernd Bruchmann, Juergen Ruehe
Summary: This article presents a technique for fabricating surfaces covered with densely packed high aspect ratio nanoscale polymer hairs. The structures are formed by filling templates with polymer melt, cooling, and mechanically removing the templates. The resulting surfaces exhibit high hair densities and can dramatically alter the wetting properties of common polymers.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Multidisciplinary
Minghao Guo, Wan Shou, Liane Makatura, Timothy Erps, Michael Foshey, Wojciech Matusik
Summary: In this study, we propose a parametric, context-sensitive grammar called PolyGrammar specifically designed for polymers. By using symbolic hypergraph representation and simple production rules, PolyGrammar can clearly represent and generate all valid polyurethane structures. We also test the representative power of PolyGrammar and demonstrate its ease of extension to other copolymers and homopolymers. The introduction of PolyGrammar is significant for the discovery and exploration of polymers and serves as a critical blueprint for the design of similar grammars in other chemical fields.
Review
Chemistry, Physical
Avinash Alagumalai, Wan Shou, Omid Mahian, Mortaza Aghbashlo, Meisam Tabatabaei, Somchai Wongwises, Yong Liu, Justin Zhan, Antonio Torralba, Jun Chen, ZhongLin Wang, Wojciech Matusik
Summary: Self-powered intelligent sensing systems, augmented with machine learning, enable large-scale deployment of IoT. Challenges include stable power harvesting, privacy, and ethical implications.
Review
Chemistry, Multidisciplinary
Bernhard von Vacano, Hannah Mangold, Guido W. M. Vandermeulen, Glauco Battagliarin, Maximilian Hofmann, Jessica Bean, Andreas Kuenkel
Summary: To achieve a sustainable circular economy of polymers, the production of polymers must transition to recycled and biobased feedstock and achieve CO2 emission neutrality. Collecting and recycling polymers or utilizing biodegradable options at their end of life is crucial. Advances in polymer chemistry and applications, supported by computational material science, offer opportunities for designing polymers with recyclability and biodegradability. This Review explores the pathways for transforming the polymer industry towards a circular economy, taking into account scientific progress, regulatory frameworks, societal expectations, and economic factors.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Chemistry, Physical
Yue Sun, Yide Zheng, Run Wang, Tongda Lei, Jian Liu, Jie Fan, Wan Shou, Yong Liu
Summary: This article reports a waterproof and humidity-resistant triboelectric nanogenerator (TENG) composed of a three-dimensional polydimethylsiloxane (PDMS) film and polyacrylonitrile (PAN) nanofiber/zinc oxide nanorods (ZnO NRs) composite membrane. The TENG exhibits excellent electrical output performance even in high-humidity environments, making it highly promising for various applications.
Article
Chemistry, Physical
Chuanyong Liu, Liang Wang, Zhaopeng Xia, Wan Shou, Yong Liu
Summary: In this work, hollow porous carbon fiber (HPCF) cathodes were prepared via a spinning-co-foaming technique, followed by zinc oxide nanoparticles as a template and activation process. The aligned channels and hierarchical cavities in HPCF wall provide a high-speed diffusion path for electrolyte penetration via capillary force. The optimized ZHPCF-5 cathode displays a capacity of 220 mAh g-1 at 0.2 A g-1 and an energy density of 224 Wh kg-1 at a 14400 W kg-1 of power density. The assembled quasi-solid-state self-standing ZIC exhibits a high capacity of 153.5 mAh g-1 at 0.5 A g-1.
JOURNAL OF POWER SOURCES
(2023)
Article
Polymer Science
Bernhard von Vacano, Oliver Reich, Gregor Huber, Gazi Tuerkoglu
Summary: Mechanical recycling is crucial for a sustainable circular economy of polypropylene (PP), but it faces challenges of molecular damage caused by processing and use-phase accumulation, especially in multiple loop recycling. This study analyzes the molecular origin of PP degradation under up to 30 repetitive reprocessing loops, and explores the influence of stabilization and processability data on changes in the entire molecular weight distribution. Comparing experiments with Monte Carlo simulations, the findings reveal a coupled mechanism of random scission and shear-induced cleavage, while stabilizing additives effectively protect the material from degradation along this combined pathway.
JOURNAL OF POLYMER SCIENCE
(2023)
Article
Computer Science, Software Engineering
Liane Makatura, Bohan Wang, Yi-Lu Chen, Bolei Deng, Chris Wojtan, Bernd Bickel, Wojciech Matusik
Summary: This article introduces a compact and intuitive procedural graph representation for cellular metamaterials, which provides a concise way to represent the construction process and create complex structures such as triply periodic minimal surfaces (TPMS).
ACM TRANSACTIONS ON GRAPHICS
(2023)
Review
Materials Science, Multidisciplinary
Soyeon Park, Wan Shou, Liane Makatura, Wojciech Matusik, Kun (Kelvin) Fu
Summary: This review provides an overview of the application of additive manufacturing technology in polymer composites, highlighting the current challenges and future research directions.
Article
Chemistry, Physical
Yaping Li, Jie Fan, Run Wang, Wan Shou, Liang Wang, Yong Liu
Summary: Researchers have developed a unique TBFF-PDA-PPy material inspired by the natural transpiration process of trees, showing excellent performance in water transport. This material exhibits high water transport rate and solar energy conversion efficiency, making it suitable for large-scale applications in water purification and seawater desalination.
JOURNAL OF MATERIALS CHEMISTRY A
(2021)