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Visual detection of ciprofloxacin using a multi-emission ratiometric fluorescence sensor based on the molecularly imprinted polymers doped with terbium(III) ions.
Talanta
January 2025
School of Pharmacy, Binzhou Medical University, Yantai, 264003, China. Electronic address:
Ciprofloxacin (CIP) is a commonly used antibiotic, but its abuse may cause bacterial resistance, posing a high risk to the environment and human health. Herein, based on the molecular imprinting technology, this study proposed a ratiometric fluorescence sensor employing the "post-doping" strategy, which aims to be rapid, selective, and visually easy-to-use for CIP detection to address antibiotic residues and environmental risks. Specifically, by exploiting the "antenna effect" of lanthanide metal ions (Ln), terbium (III) (Tb) chosen as a fluorescence-assisted functional monomer as well as the red emitting CdTe quantum dots (QDs) as the internal reference signal were introduced into multi-emission Tb-CdTe@SiO@MIPs (TbMIPs).
View Article and Find Full Text PDFBeyond the random phase approximation for calculating Curie temperatures inferromagnets: application to Fe, Ni, Co and monolayer CrI3.
J Phys Condens Matter
January 2025
Department of Physics, Danmarks Tekniske Universitet, Department of Physics, Technical University of Denmark, Kgs Lyngby, 2800, DENMARK.
The magnetic properties of solids are typically analyzed in terms of Heisenberg models where the electronic structure is approximated by interacting localized spins. However, even in such models the evaluation of thermodynamic properties constitutes a major challenge and is usually handled by a mean field decoupling scheme. The random phase approximation (RPA) comprises a common approach and is often applied to evaluate critical temperatures although it is well known that the method is only accurate well below the critical temperature.
View Article and Find Full Text PDFCorrigendum to "" [Heliyon Vol. 9, Iss. 1, January 2023, Article e12599].
Heliyon
December 2024
Research Centre for Synthesis and Catalysis, Department of Chemical Sciences, University of Johannesburg, South Africa.
[This corrects the article DOI: 10.1016/j.heliyon.
View Article and Find Full Text PDFEvaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.
J Chem Theory Comput
January 2025
Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several times more computationally demanding than MM simulations, so there is a trade-off between speed and accuracy. One possible compromise are hybrid machine learning/molecular mechanics (ML/MM) approaches with mechanical embedding that treat the intramolecular interactions of the ligand at the ML level and the protein-ligand interactions at the MM level.
View Article and Find Full Text PDFPM6-ML: The Synergy of Semiempirical Quantum Chemistry and Machine Learning Transformed into a Practical Computational Method.
J Chem Theory Comput
January 2025
Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
Machine learning (ML) methods offer a promising route to the construction of universal molecular potentials with high accuracy and low computational cost. It is becoming evident that integrating physical principles into these models, or utilizing them in a Δ-ML scheme, significantly enhances their robustness and transferability. This paper introduces PM6-ML, a Δ-ML method that synergizes the semiempirical quantum-mechanical (SQM) method PM6 with a state-of-the-art ML potential applied as a universal correction.
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