The attractive properties of single-wall carbon nanotubes (SWCNT) such as mechanical strength and high electrical and thermal conductivity are often undercut by their agglomeration and re-agglomeration tendencies. As a result, the application of SWCNT as additives in advanced composite materials remain far from their potential, with proper dispersion being the major inhibitor. This work presents a dispersion quality control approach for water-based SWCNT dispersions (dispersed by a unique combination of physical and chemical methods), using complementary and easily scalable, characterization methods. UV-Vis spectroscopy, rheological measurements, and precipitant sheet resistance were used to understand the properties of the initial solution through processing and application. From an industrial perspective, these methods are fast and easy to measure while giving a repetitive and quick indication of dispersion quality and stability. The methods were correlated with microscopy and Raman spectroscopy to validate dispersion and SWCNT quality under various dispersing energies. The protocol was then applied to estimate the stability of SWCNT solutions, as well as the effectiveness of different surfactants in aiding dispersion. The simple, fast, and scalable combination of different characterizations provides good SWCNT dispersion and can be used as a quality control system for industrial production and usage.
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http://dx.doi.org/10.3390/nano11102618 | DOI Listing |
PLoS One
January 2025
Department of Anesthesiology, Henan Provincial Chest Hospital & Chest Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background: Postoperative nausea and vomiting (PONV) is a common complication of general anesthesia. This affects 30-80% of patients, and leads to discomfort and extended hospital stays. The effectiveness of penehyclidine for preventing PONV remains a subject of debate in the literature.
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January 2025
Department of Geography, University College London, London, England, United Kingdom.
Evaluating the dynamic co-evolution and feedback mechanisms within socio-ecological systems is crucial for determining the resilience and sustainability of environmental governance strategies. The grass-livestock system, as a complex entity encompassing livestock nutrition, foraging behavior, vegetation ecology, pastoralists' economic income, and policy interventions, indicates that any change in a single element may trigger a chain reaction within the system. This paper uses a system dynamics approach to construct a simulation model of the grass-livestock system in alpine pastoral areas, simulating the long-term dynamic co-evolution of the socio-ecological system in the Qilian Mountains region of China.
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January 2025
Institute of Endocrinology, Prague, Czech Republic.
Objectives: Hearing impairment can have major impacts on behavior, educational attainment, social status, and quality of life. In congenital hypothyroidism, the incidence of hearing impairment reaches 35-50%, while in acquired hypothyroidism there is a reported incidence of 25%. Despite this, knowledge of the pathogenesis, incidence and severity of hearing impairment remains greatly lacking.
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January 2025
Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
Background: Anemia in pregnancy is an important public health challenge; however, it has not been thoroughly studied in Georgia. We assessed the prevalence of anemia during pregnancy across Georgia and the association between anemia in the third trimester of pregnancy and adverse maternal outcomes.
Methods: We used data from the Georgian Birth Registry and included pregnant women who delivered between January 1, 2019, and August 31, 2022 (n = 158,668).
PLoS One
January 2025
Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy.
Plant viruses pose a significant threat to global agriculture and require efficient tools for their timely detection. We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. The pipeline uses Biopython to automatically retrieve different genomic sequences from the NCBI database to increase the robustness of the subsequent primer design.
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