Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1021/ma60038a012 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Adsorption Structure and Selectivity of Phenols in Water-Immersed Organomontmorillonite Investigated by Molecular Simulation.
Langmuir
January 2025
Department of Environmental Chemistry and Chemical Engineering, School of Advanced Engineering, Kogakuin University, 2665-1 Nakano, Tokyo, Hachioji 192-0015, Japan.
The two-dimensional interlayer space of layered materials has been highlighted due to their adsorption property, whose nanostructure in the water-immersed state is scarcely understood by experiment. Recent developments in molecular simulation have enabled researchers to investigate the interlayer structure, but water content is necessary for accurate modeling. In the present study, we proposed a theoretical method to estimate the saturated water content and adsorption selectivity of trichlorophenol and phenol in montmorillonite modified with hexadecyltrimethylammonium ions.
View Article and Find Full Text PDFThe Importance and Psychometric Soundness of an Instrument to Measure Holistic Nursing in NP Care.
J Holist Nurs
January 2025
University of Central Florida, College of Nursing, Orlando, FL, USA.
The Nurse Practitioner Holistic Caring Instrument (NPHCI) is a 19-item, investigator-developed instrument designed to measure holistic caring in nurse practitioner (NP) practice. This paper evaluates multi-sample psychometric testing of the instrument, describing data from three samples, with analysis supporting the NPHCI as a valid and reliable instrument. Methods: The NPHCI has been administered in patient, NP program faculty, and NP convenience samples.
View Article and Find Full Text PDFUnlocking new possibilities in ionic thermoelectric materials: a machine learning perspective.
Natl Sci Rev
January 2025
Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China.
The high thermopower of ionic thermoelectric (-TE) materials holds promise for miniaturized waste-heat recovery devices and thermal sensors. However, progress is hampered by laborious trial-and-error experimentations, which lack theoretical underpinning. Herein, by introducing the simplified molecular-input line-entry system, we have addressed the challenge posed by the inconsistency of -TE material types, and present a machine learning model that evaluates the Seebeck coefficient with an of 0.
View Article and Find Full Text PDFMedication non-adherence: reflecting on two decades since WHO adherence report and setting goals for the next twenty years.
Front Pharmacol
December 2024
Syreon Research Institute, Budapest, Hungary.
Background: Non-adherence to medication remains a persistent and significant challenge, with profound implications for patient outcomes and the long-term sustainability of healthcare systems. Two decades ago, the World Health Organization (WHO) dedicated its seminal report to adherence to long-term therapies, catalysing notable changes that advanced both research and practice in medication adherence. The aim of this paper was to identify the most important progress made over the last 2 decades in medication adherence management and to initiate a discussion on future objectives, suggesting priority targets for the next 20 years.
View Article and Find Full Text PDFMachine learning analysis of factors affecting college students' academic performance.
Front Psychol
December 2024
Department of Science and Technology, Hebei Agricultural University, Huanghua, China.
This study aims to explore various key factors influencing the academic performance of college students, including metacognitive awareness, learning motivation, participation in learning, environmental factors, time management, and mental health. By employing the chi-square test to identify features closely related to academic performance, this paper discussed the main influencing factors and utilized machine learning models (such as LOG, SVC, RFC, XGBoost) for prediction. Experimental results indicate that the XGBoost model performs the best in terms of recall and accuracy, providing a robust prediction for academic performance.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!