Results 151 to 160 of about 755,747 (299)

Analytical theory of the hydrophobic effect of solutes in water. [PDF]

Phys Rev E, 2017
Urbic T, Dill KA.
europepmc   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Inactivating SARS‐CoV‐2 Virus with MOF‐Composites as Smart Face Masks

Advanced Functional Materials, EarlyView.
In situ preparation and functionalization of MOF@Cotton fabrics as smart face masks for the immobilization of proteins and inactivation viruses, such as SARS‐CoV‐2. Abstract The significant impact of the SARS‐CoV‐2 (COVID‐19) pandemic outbreak on people's lives has highlighted the urgent need for effective personal protective equipment.
Romy Ettlinger, Aamod V. Desai, Hau Lam Jody Cheong, Louise L. Major, Terry K. Smith, Aaron B. Naden, Jane Hilton, Catherine S. Adamson, A. Robert Armstrong, Russell E. Morris   +9 more
wiley   +1 more source

The hydrophobic effect, and fluctuations: The long and the short of it. [PDF]

Proc Natl Acad Sci U S A, 2016
Xi E, Patel AJ.
europepmc   +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

Hydrophobic Effect from Conjugated Chemicals or Drugs on In Vivo Biodistribution of RNA Nanoparticles. [PDF]

Hum Gene Ther, 2018
Jasinski DL, Yin H, Li Z, Guo P.
europepmc   +1 more source

Rapid Sintering of Porous Organic Polymer Powders Into Mechanically Strong Monoliths for Efficient CO2 Capture

Advanced Functional Materials, EarlyView.
Spark plasma sintering enables rapid processing of porous organic polymer (POP) from fine powders to a freestanding and mechanically robust monolith. The sintering process retains the CO2 adsorption capacity and CO2/N2 selectivity, making the monolith more suitable as a solid sorbent for practical carbon capture applications.
Duan Li, Tianhui Shi, Sirui Ran, Lei Zeng, Chao Xu   +4 more
wiley   +1 more source

Towards a structural biology of the hydrophobic effect in protein folding. [PDF]

Sci Rep, 2016
Camilloni C, Bonetti D, Morrone A, Giri R, Dobson CM, Brunori M, Gianni S, Vendruscolo M.   +7 more
europepmc   +1 more source

Reducing Open‐Circuit Voltage Losses in Wide‐Bandgap FAPbBr3 Perovskite Solar Cells for Continuous Unassisted Light‐Driven Water Splitting

Advanced Functional Materials, EarlyView.
The combination of formamidinium thiocyanate and 1,3‐propane diammonium iodide for bulk and top‐surface passivation, and a ternary fullerene blend to improve energy band alignment, suppresses energy losses in wide‐bandgap FAPbBr3 perovskite solar cells.
Laura Bellini, Daniël Grosfeld, Bruno Branco, Guus J. W. Aalbers, Lana M. Kessels, Willemijn H. M. Remmerswaal, Nicolas Daub, Kunal Datta, Martijn M. Wienk, René A. J. Janssen   +9 more
wiley   +1 more source

The Hydrophobic Effect in Solute Partitioning and Interfacial Tension. [PDF]

Sci Rep, 2016
Jackson MB.
europepmc   +1 more source