Cellulose nanofibrils (CNFs) are a class of cellulosic nanomaterials with high aspect ratios that can be extracted from various natural sources. Their highly crystalline structures provide the nanofibrils with excellent mechanical and thermal properties. The main challenges of CNFs in nanocomposite applications are associated with their high hydrophilicity, which makes CNFs incompatible with hydrophobic polymers. In this study, highly transparent and toughened poly(methyl methacrylate) (PMMA) nanocomposite films were prepared using various percentages of CNFs covered with surface carboxylic acid groups (CNF-COOH). The surface groups make the CNFs interfacial interaction with PMMA favorable, which facilitate the homogeneous dispersion of the hydrophilic nanofibrils in the hydrophobic polymer and the formation of a percolated network of nanofibrils. The controlled dispersion results in high transparency of the nanocomposites. Mechanical analysis of the resulting films demonstrated that a low percentage loading of CNF-COOH worked as effective reinforcing agents, yielding more ductile and therefore tougher films than the neat PMMA film. Toughening mechanisms were investigated through coarse-grained simulations, where the results demonstrated that a favorable polymer-nanofibril interface together with percolation of the nanofibrils, both facilitated through hydrogen bonding interactions, contributed to the toughness improvement in these nanocomposites.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acsami.5b08317 | DOI Listing |
Corporate Social Responsibility (CSR) refers to initiatives undertaken by corporations that aim to make a positive impact on society. It is unclear to what extent these aims are achieved in relation to population health. We explored the evidence for mechanisms by which CSR has positive or negative effects on population health through a systematic-narrative hybrid review of 97 relevant articles.
View Article and Find Full Text PDFJ Med Educ Curric Dev
January 2025
Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, NY, USA.
Objectives: Instilling the principles of ethical and responsible medical research is critical for educating the next generation of clinical researchers. We developed a responsible conduct of research (RCR) workshop and associated curriculum for undergraduate trainees in a quantitative clinical research program.
Methods: Topics in this 7-module RCR workshop are relevant to undergraduate trainees in quantitative fields, many of whom are learning about these concepts for the first time.
Health Aff Sch
January 2025
Mathematica, Princeton, NJ 08540, United States.
Consolidation of independent hospitals and physician practices into integrated health systems has reshaped the delivery of health care. While the literature suggests that provider consolidation raises prices, few studies have examined the interplay of health systems and insurers in relation to prices. Using negotiated price data that commercial insurers recently released under the Transparency in Coverage Final Rule, we examined the association between hospital concentration under health systems and prices for outpatient procedures in local health care markets with different levels of insurer concentration.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Engineering, Qatar University, 2713, Doha, Qatar.
Effective energy management is crucial in greenhouse farming to ensure efficient operations and optimal crop growth. This study investigates the energy autonomy-defined as the ratio of on-site energy generation to the total energy demand-of greenhouses equipped with semi-transparent photovoltaic (STPV) systems under two scenarios: with and without a Battery Energy Storage System (BESS). STPV systems are beneficial because they generate energy while still allowing enough light to pass through for healthy plant development.
View Article and Find Full Text PDFCrit Rev Oncog
January 2025
Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School (MHH), Hannover, Germany.
Machine learning (ML) holds great promise in advancing risk prediction and stratification for neuroblastoma, a highly heterogeneous pediatric cancer. By utilizing large-scale biological and clinical data, ML models can detect complex patterns that traditional approaches often overlook, enabling more personalized treatments and better patient outcomes. Various ML techniques, such as support vector machines, random forests, and deep learning, have shown superior performance in predicting survival, relapse, and treatment responses in neuroblastoma patients compared to conventional methods.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!