Antimicrobial Effect of Electrospun Nanofibers Loaded with Silver Nanoparticles: Influence of Ag Incorporation Method

The antimicrobial bioactivity of silver nanoparticles is well known, and they can be used widely in many applications, becoming especially important in the biomedical industry. On the other hand, the electrospun nanofibers possess properties that can enhance silver nanoparticle applicability. However, silver nanoparticle bioactivity differs depending on the loading of silver ions into electrospun nanofibers. This review is aimed at comparing different silver incorporation methods into electrospun nanofibers and their antimicrobial activity, discussing each procedure’s limitations, and presenting the most promising one. This review showed that the preferred techniques for incorporating silver nanoparticles were direct blending and ultraviolet irradiation methods due to their simplicity and efficient results. Besides, polyacrylonitrile nanofibers (PAN) have been the most reported system loaded with silver nanoparticles. Finally, independently of the technique used, silver nanoparticle-loaded nanofibers show high antimicrobial activity in all cases.

Enhanced Performance of the OMS-2-Supported CuOx Catalysts for Carbon Monoxide, Ethyl Acetate, and Toluene Oxidation

Different Cu contents (x wt%) were supported on the cryptomelane-type manganese oxide octahedral molecular sieve (OMS-2) (xCu/OMS-2; x = 1, 5, 15, and 20) via a pre-incorporation method. Physicochemical properties of the OMS-2 and xCu/OMS-2 samples were characterized by means of the XRD, FT-IR, SEM, TG/DTG, ICP-OES, XPS, O2-TPD, H2-TPR, and in situ DRIFTS techniques, and their catalytic activities were measured for the oxidation of CO, ethyl acetate, and toluene. The results show that the Cu species were homogeneously dispersed in the tunnel and framework structure of OMS-2. Among all of the samples, 15Cu/OMS-2 sample exhibited the best activities with the T50% of 65, 165, and 240 °C as well as the T90% of 85, 215, and 290 °C for CO, ethyl acetate and toluene oxidation, respectively, which was due to the existence of the Cu species and Mn3+/Mn4+ redox couples, rich oxygen vacancies, good oxygen mobility, low-temperature reducibility, and strong interaction between the Cu species and the OMS-2 support. The reaction mechanisms were also deduced by analyzing the in situ DRIFTS spectra of the 15Cu/OMS-2 sample. The excellent oxygen mobility associated with the electron transfer between Cu species and Mn3+/Mn4+ redox couples might be conducive to the continuous replenishment of active oxygen species and the constantly generated reactant intermediates, thereby increasing the reactant reaction rate.

Engendering persistent organic room temperature phosphorescence by trace ingredient incorporation

Pure organic persistent room temperature phosphorescence (RTP) has shown great potential in information encryption, optoelectronic devices, and bio-applications. However, trace impurities are generated in synthesis, causing unpredictable effects on the luminescence properties. Here, an impurity is isolated from a pure organic RTP system and structurally characterized that caused an unusual ultralong RTP in matrix even at 0.01 mole percent content. Inspired by this effect, a series of compounds are screened out to form the bicomponent RTP system by the trace ingredient incorporation method. The RTP quantum yields reach as high as 74.2%, and the lifetimes reach up to 430 ms. Flexible application of trace ingredients to construct RTP materials has become an eye-catching strategy with high efficiency, economy, and potential for applications as well as easy preparation.

Catalytic Elimination of Carbon Monoxide, Ethyl Acetate, and Toluene over the Ni/OMS-2 Catalysts

The Ni-loaded cryptomelane-type manganese oxide octahedral molecular sieve (OMS-2) catalysts (xNi/OMS-2: x = 1, 3, 5, and 10 wt%) were prepared by a pre-incorporation method. Physicochemical properties of the as-synthesized materials were characterized by means of various techniques, and their catalytic activities for CO, ethyl acetate, and toluene oxidation were evaluated.The loading of Ni played an important role in improving physicochemical propertiesof OMS-2. Among all of the samples, 5Ni/OMS-2 exhibited the best catalytic activity, with the T90 being 155 °C for CO oxidation at a space velocity (SV) of 60,000 mL/(g·h), 225°C for ethyl acetate oxidation at an SV of 240,000 mL/(g·h), and 300 °C for toluene oxidation at an SV of 240,000 mL/(g·h), which was due to its high Mn3+ content and Oads concentration, good low-temperature reducibility and lattice oxygen mobility, and strong interaction between the Ni species and the OMS-2 support. In addition, catalytic mechanisms of the oxidation of three pollutants over 5Ni/OMS-2 were also studied. The oxidation of CO, ethyl acetate, and toluene over the catalysts took place first via the activated adsorption, then intermediates formation, and finally complete conversion of the formed intermediates to CO2 and H2O.

Effect of the Profile of the Decision Maker in the Search for Solutions in the Decision-Making Process

Many real-world optimization problems involving several conflicting objective functions frequently appear in current scenarios and it is expected they will remain present in the future. However, approaches combining multi-objective optimization with the incorporation of the decision maker’s (DM’s) preferences through multi-criteria ordinal classification are still scarce. In addition, preferences are rarely associated with a DM’s characteristics; the preference selection is arbitrary. This paper proposes a new hybrid multi-objective optimization algorithm called P-HMCSGA (preference hybrid multi-criteria sorting genetic algorithm) that allows the DM’s preferences to be incorporated in the optimization process’ early phases and updated into the search process. P-HMCSGA incorporates preferences using a multi-criteria ordinal classification to distinguish solutions as good and bad; its parameters are determined with a preference disaggregation method. The main feature of P-HMCSGA is the new method proposed to associate preferences with the characterization profile of a DM and its integration with ordinal classification. This increases the selective pressure towards the desired region of interest more in agreement with the DM’s preferences specified in realistic profiles. The method is illustrated by solving real-size multi-objective PPPs (project portfolio problem). The experimentation aims to answer three questions: (i) To what extent does allowing the DM to express their preferences through a characterization profile impact the quality of the solution obtained in the optimization? (ii) How sensible is the proposal to different profiles? (iii) How much does the level of robustness of a profile impact the quality of final solutions (this question is related with the knowledge level that a DM has about his/her preferences)? Concluding, the proposal fulfills several desirable characteristics of a preferences incorporation method concerning these questions.