From Subjects to Partners: Rethinking Research Methodologies through Citizen Science. [PDF]
De Marchi B.
europepmc +1 more source
In this study, the interplay of dipolar dynamics and ionic charge transport in MOF compounds is investigated. Synthesizing the novel structure CFA‐25 with integrated freely rotating dipolar groups, local and macroscopic effects, including interactions with Cs cations are explored.
Ralph Freund +6 more
wiley +1 more source
Quantum technologies and geopolitics: comparing parliamentary rhetoric. [PDF]
Suter V, Pöhlmann G, Ma C, Meckel M.
europepmc +1 more source
Positive‐Tone Nanolithography of Antimony Trisulfide with Femtosecond Laser Wet‐Etching
A butyldithiocarbamic acid (BDCA) etchant is used to fabricate various micro‐ and nanoscale structures on amorphous antimony trisulfide (a‐Sb2S3) thin film via femtosecond laser etching. Numerical analysis and experimental results elucidate the patterning mechanism on gold (reflective) and quartz (transmissive) substrates.
Abhrodeep Dey +12 more
wiley +1 more source
Understanding Spanglish and Flemch : A Comparative Analysis of American and Belgian Language Politics [PDF]
Wattal, Urvashi
core +1 more source
Patient Involvement in Health Technology Assessments: Lessons for EU Joint Clinical Assessments. [PDF]
Pickaert AP.
europepmc +1 more source
Electroactive Metal–Organic Frameworks for Electrocatalysis
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source
Citizenship, official language, bilingual education in Latvia: public policy in the last 10 years [PDF]
Zepa, Brigita
core
Impact of Additional Monitoring on Pharmacovigilance and Pharmacists' Role: A Scoping Review. [PDF]
Aizpurua-Arruti X +7 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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 +7 more
wiley +1 more source

