Results 91 to 100 of about 365,316 (225)

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

Geometric and singularities insights of swept surfaces via the Bishop frame in Euclidean 3-Space. [PDF]

PLoS One
Mofarreh F, Abdel-Baky R, Alsahli M.
europepmc   +1 more source

Covalent Organic Frameworks for Water Sorption: The Importance of Framework Physical Stability

Advanced Functional Materials, EarlyView.
This study explores the water‐vapor stability of 2D covalent organic frameworks (COFs) with varying pore sizes. Results reveal microporous COFs demonstrate superior stability compared to mesoporous ones, despite lower water uptake. Mesoporous keto‐enamine‐linked COFs show enhanced stability due to intralayer hydrogen bonds, confirmed by simulations and
Wei Zhao, He Li, Bui Duc Thuan, Weidong Chen, Qiang Zhu, Mounib Bahri, Boyu Li, Kexin Yu, Chengjun Kang, Ting Chen, Zekun Wang, Nigel D. Browning, Kian Jon Chua, Dan Zhao   +13 more
wiley   +1 more source

Geometry-aware point cloud clustering for spherical-component aggregate modeling. [PDF]

Sci Rep
Muramatsu Y, Sato S, Sakurai K.
europepmc   +1 more source

Ice Lithography: Recent Progress Opens a New Frontier of Opportunities

Advanced Functional Materials, EarlyView.
This review focuses on recent advancements in ice lithography, including breakthroughs in compatible precursors and substrates, processes and applications, hardware, and digital methods. Moreover, it offers a roadmap to uncover innovation opportunities for ice lithography in fields such as biological, nanoengineering and microsystems, biophysics and ...
Bingdong Chang, Gwendoline A. E. Anand, Rubaiyet Haque, Dylan A. Chiaro, Mona Sharma, Andrew R. Williams, Frank Niklaus, Daryl W. Yee, Gavin M. King, Anpan Han   +9 more
wiley   +1 more source

Mechanics of knee meniscus results from precise balance between material microstructure and synovial fluid viscosity. [PDF]

PLoS One
Afanador CAS, Urcun S, Sbalzarini IF, Bordas SPA, Barrera O, Rajabi MM, Seil R, Obeidat A.   +7 more
europepmc   +1 more source

The Realization of Multidirectional, Free‐Standing 3D Plasmonic Nanostructures via 3D Nanoprinting: A Case Study of Fractal Antennas

Advanced Functional Materials, EarlyView.
Free‐standing plasmonic gold‐based fractal antennas are fabricated by 3D nanoprinting, employing focused electron beam induced deposition and an optimized purification method to remove carbon while conserving structural fidelity. Simulation and experiment show broadband plasmonic activity, including customizable polarizability, thereby paving the way ...
Verena Reisecker, Robert Winkler, Ulrich Hohenester, Evelin Fisslthaler, Daniel Knez, Gerald Kothleitner, Georg Haberfehlner   +6 more
wiley   +1 more source

Bio-inspired unified model for representing geometric relations in robotic perception. [PDF]

Sci Rep
Yi Y, Zhuo W, Huifeng W, Danfeng S, Simon R.   +4 more
europepmc   +1 more source

Expanding Chemical Space of Nucleic Acid Nanoparticles for Tunable Antiviral‐Like Immunomodulatory Responses and Potent Adjuvant Activity

Advanced Functional Materials, EarlyView.
We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj, Hannah S. Newton, Jian Wang, Laxmi Pandey, Yelixza I. Avilla, Phong Nguyen, Morgan Chandler, Justin Halman, Yasmine Radwan, Stephanie Smith, Elijah Edmondson, Simone Difilippantonio, Chelsea Sanders, Bao Tran, Yongmei Zhao, Shaojun Xie, Edward Cedrone, Barry W. Neun, Meni Wanunu, Nikolay V. Dokholyan, Marina A. Dobrovolskaia, Kirill A. Afonin   +21 more
wiley   +1 more source

A systematic review of molecular representation learning foundation models. [PDF]

Brief Bioinform
Song B, Zhang J, Liu Y, Liu Y, Jiang J, Yuan S, Zhen X, Liu Y.   +7 more
europepmc   +1 more source