Results 41 to 50 of about 1,595 (181)

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

Calcium Imparts Advanced Functionalities to Silk Hydrogels for Biofabrication and Biomedical Innovation

Advanced Functional Materials, EarlyView.
The addition of calcium ions to silk fibroin enhances the hydrogel properties and, when combined with visible light crosslinking, enables compatibility with advanced light‐based fabrication techniques. Calcium ions extend the shelf‐life of silk and facilitate the fabrication of multizonal, multilayered constructs for advanced stimuli‐responsive ...
Hien A. Tran, Anton Maraldo, Chi Cong Nguyen, Trinh Thi‐Phuong Ho, Lauryn Srethbhakdi, Habib Joukhdar, Quinn van Hilst, Syamak Farajikhah, Fariba Dehghani, Thanh Nho Do, Khoon S. Lim, Jelena Rnjak‐Kovacina   +11 more
wiley   +1 more source

Recycling of Thermoplastics with Machine Learning: A Review

Advanced Functional Materials, EarlyView.
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque, Florian Stephan, Annalena Pongratz, Christian Brütting, Katharina Krause, Holger Ruckdäschel   +5 more
wiley   +1 more source

The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue Fabrication

Advanced Functional Materials, EarlyView.
Advances in integrating artificial intelligence into 3D bioprinting are systematically reviewed here. Machine learning, computer vision, robotics, natural language processing, and expert systems are examined for their roles in optimizing bioprinting parameters, real‐time monitoring, quality control, and predictive maintenance.
Joao Vitor Silva Robazzi, Irem Deniz Derman, Deepak Gupta, Logan Haugh, Yogendra Pratap Singh, Vaibhav Pal, Yasar Ozer Yilmaz, Suihong Liu, Andre Luis Dias, Rogerio Andrade Flauzino, Ibrahim Tarik Ozbolat   +10 more
wiley   +1 more source

Understanding Functional Materials at School

Advanced Functional Materials, EarlyView.
This review outlines strategies for effectively teaching nanoscience in schools, focusing on challenges such as scale comprehension and curriculum integration. Emphasizing inquiry‐based learning and chemistry core concepts, it showcases hands‐on activities, digital tools, and interdisciplinary approaches.
Johannes Claußnitzer, Jürgen Paul
wiley   +1 more source

Revealing the Auxetic Behavior of Biomimetic Multimaterial and Region‐Specific Nanofibrous Fascicle‐Inspired Scaffolds via Synchrotron Multiscale Digital Volume Correlation: Innovative Building Blocks for the Enthesis Regeneration

Advanced Functional Materials, EarlyView.
Enthesis injuries are a worldwide healthcare problem. Biomimetic electrospun enthesis fascicle‐inspired scaffolds, with and without nano‐mineralization are developed. Human Mesenchymal Stromal cells (hMSCs) express the most balanced enthesis markers on the non‐mineralized scaffolds.
Alberto Sensini, Francesca Giacomini, Olga Stamati, Bratislav Lukic, Julie Villanova, Henry Proudhon, Maryse Gille, Zeinab Tahmasebi Birgani, Roman Truckenmüller, Gianluca Tozzi, Martijn van Griensven, Lorenzo Moroni   +11 more
wiley   +1 more source

Dynamic Control of Synaptic Plasticity by Competing Ferroelectric and Trap‐Assisted Switching in IGZO Transistors with Al2O3/HfO2 Dielectrics

Advanced Functional Materials, EarlyView.
A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon, Dong Ho Lee, Seyoung Oh, Jongwon Yoon, Hyo‐Bae Kim, Ji‐Hoon Ahn, Woojin Park, Han Seul Kim, Byungjin Cho   +8 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Ten quick tips for bioinformatics analyses using an Apache Spark distributed computing environment. [PDF]

PLoS Comput Biol, 2023
Chicco D, Ferraro Petrillo U, Cattaneo G.   +2 more
europepmc   +1 more source