Here we report the synthesis of nanoparticles based on a conjugated oligomer which is synthesized through Heckcoupling of divinylfluorene and dibromobenzothiodiazole monomers. These water dispersible nanoparticles emit in the region of red tailing to the near-infrared region of the spectrum with high fluorescent quantum yield and brightness. The nanoparticles were found to be stable in water for a prolonged time without forming any aggregates and could carry camptothecin, an anticancer drug with high loading efficiency. MTT cell viability studies performed with breast cancer cell lines showed that halfmaximal inhibitory concentration (IC 50 ) values of nanoparticles for MCF7 and MDA-MB-231 were 44.7 μM and 24.8 μM, respectively. In order to further decrease the cytotoxicity and increase the stability of nanoparticles, amine groups were disguised by capping with cucurbit [7]uril (CB7). Drug release studies showed that drugs were released at low pH (at 5.0) faster than physiological pH (7.4) confirming the pH-responsive nature of the nanoparticles. On the other hand, CB7-capped drug-loaded nanoparticles regulated the release rate by providing slower release at pH 7.4 than the nanoparticles in the absence of CB7s. IC 50 values for camptothecin in the presence of nanoparticles with or without CB7 were significantly reduced in MCF7 and MDA-MB-231 cells. ■ INTRODUCTIONConjugated polymer nanoparticles (CPNs) are highly appealing for various advanced applications such as in vivo imaging, cell labeling, and delivery of therapeutic agents, as well as nanophotonics, owing to their high quantum yields and molar absorptivity, tunable properties, easy functionalization, photostability, and so forth. 1−7 To date, the use of CPNs has been demonstrated successfully in cell imaging, oxygen sensing, drug delivery, and nucleic acid delivery. 8−16 When these nanostructures are judiciously designed, they can be utilized in theranostic applications by combining more than one functionality to deliver therapeutic and imaging agents. 17−21 For the controlled delivery of therapeutic agents to the targets the nanoparticles could also include responsive groups that will respond to stimuli such as pH, oxidation−reduction, and enzymes. However, in the literature, examples are scarce regarding the multifunctional conjugated polymer nanoparticles (CPNs) and even less with conjugated oligomer-based nanoparticles (CONs). 22,23 Recently, Schenning et al. compared the capabilities of conjugated polymer nanoparticles to selfassembled oligomer-based nanoparticles in terms of their fluorescent quantum yields, stabilities, molar absorptivity, guest-holding, and releasing. 24 They demonstrated that oligomer nanoparticles have higher fluorescent quantum yields and comparable stabilities and molar absorptivity, but they release the guest faster than the conjugated polymer nanoparticles. Thus, this feature should be considered for the further design of oligomer-based nanoparticles for theranostic applications. CONs also offer some useful addi...
Performance modeling of electrochemical energy storage systems is gathering increasingly higher attention in recent years. With the ever increasing power demand of mobile applications, predicting voltage behavior under different load profiles is of utmost importance for communications, automotive and consumer electronics. The ideal modelling approach needs not only to accurately predict the response of the battery, but also be robust, easy to implement and have low computational complexity. We will present a new algorithm that is algebraically straightforward, that has no adjustable parameters and that can accurately predict the voltage response of batteries and supercapacitors. The approach works well in a variety of discharge profiles ranging from simple long DC discharge/charge profiles to pulse schemes based on drive schedules published by regulatory bodies. Our approach is based on Electrochemical Impedance Spectroscopy measurements done on the system to be predicted. The spectrum is used in the frequency domain without any further processing to predict the fast moving portion of the voltage in the frequency domain. DC response is added in through a straightforward lookup Batterya performance in a variety of conditions is one of the most crucial design criteria in modern consumer electronics, electric vehicles and various defense related equipment. The parameters of the battery generally limit not only operation time between charge cycles, but also size of the finished product. Charge capacity of the battery is the first important specification that controls the lifetime and size of the finished product. However, a simple capacity estimation does not provide the complete picture. Battery capacity is specified under very specific conditions that are mostly at constant current. The exact value of this current, how the battery is charged beforehand and how long the charge and the discharge will proceed depend heavily on the chemistry and the standards (and conventions) that are developed for the system in question. However, in real life applications, the discharge demands on the battery is far from a constant current discharge.1,2 Behavior of the battery under the non-uniform discharge conditions needs to be determined, understood and accounted for, in order to achieve the best design and choice for any application. With the ever-increasing number of mobile powered applications, an accurate and easy to implement modeling approach to evaluate various batteries is of utmost necessity. The vast number of different discharge/charge use-cases makes measurement of all possible discharge profiles distinctly impractical.In a recent review Fotouhi et al. 3 covered various perspectives of understanding and predicting battery behavior based on different assumptions. As we will discuss below, all methods have their advantages and drawbacks. Methods with low computational complexity tend to have high inaccuracies whereas methods that are accurate tend to be algebraically and computationally complex.In another recent revie...
In a recently published article (J. Electrochem. Soc. 164 (2017) A1274-A1280), we described a new method to predict the voltage response of electrochemical energy storage systems during arbitrary load profiles. Our work shows that the impedance spectrum can be employed in the frequency domain in order to ultimately calculate the time domain behavior of the electrochemical energy storage system. The big advantage of this method is the fact that there are no free parameters and fits throughout.The present work deals with the sources of error in the above-mentioned prediction approach and looks for the effects of the various sources of error. The current analysis concludes that two big contributors to the overall error are the inaccuracies in the DC part of the prediction and the non-linearities that are not modeled by a linear impedance spectrum.Discussions are also made regarding ways to improve the performance of the modeling approach the most and where future work is going to be looking to improve.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.