Applied Research最新文献

The bio-based methacrylates 9-(methacryloyloxy)-10,18-dihydroxyoctadecanoic acid/9,18-dihydroxy-10-(methacryloyloxy)octadecanoic acid isomer mixture and 22-methacryloyloxydocosanoic acid were synthesized from 9,10-epoxy-18-hydroxyoctadecanoic acid and 22-hydroxydocosanoic acid. The white crystalline 9,10-epoxy-18-hydroxyoctadecanoic acid and cream-colored 22-hydroxydocosanoic acid were isolated from both the bark of Betula pendula and cork of Quercus suber after extraction of the milled plant materials with methanol, treating the insoluble residues with 2-propanole containing suspended sodium hydroxide, application of a working up procedure developed in this work for the resulting mixture, and purification of the products obtained. The new bio-based methacrylates show higher reactivity in the photoinitiated polymerization in comparison with the commercial laurylmethacrylate as detected by photo-differential scanning calorimetry (DSC). For comparison, traditional free radical polymerization of the new bio-based methacrylates was carried out in dimethylsulfoxide using 2,2'-azobis-(2-propionitrile) as initiator. Furthermore, the quantitative conversion of the bio-based monomers during the photoinitiated polymerization makes these bio-based monomers interesting for application in coatings. As expected, the photopolymer made from the 9-(methacryloyloxy)-10,18-dihydroxyoctadecanoic acid/9,18-dihydroxy-10-(methacryloyloxy)octadecanoic acid isomer mixture is amorphous. Interestingly, the photopolymer made from the 22-methacryloyloxydocosanoic acid contains crystalline structures as detected by DSC investigation.

This work elucidates the control of integrating a nonminimum phase system via a series cascade scheme with fractional-order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional-filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error. Two illustrative problems are utilized to examine the recommended control structure's virtue.

The prevalence of coronavirus disease 2019 (Covid-19) in the community has become more difficult to gauge utilizing clinical testing due to a decrease in reported test results stemming from the availability of at-home test kits and a reduction in the number of cases seeking medical treatment. The purpose of this study was to examine the trend of diminishing correlation between reported clinical cases of Covid-19 and wastewater-based surveillance epidemiological data as home testing became available in the Eastern Upper Peninsula of Michigan. Wastewater grab samples were collected weekly from 16 regional locations from June 2021 to December 2022. Samples were analyzed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) N1 and N2 viral particles using reverse transcriptase digital droplet polymerase chain reaction (RT ddPCR). N1 and N2 gene copies were correlated with clinical cases. The t test was used to determine the correlation deterioration point. Clinical cases postdeterioration were calculated for high-correlated predeterioration locations using linear regression. Correlation between the wastewater-based surveillance of SARS-CoV-2 and reported clinical cases deteriorated after February 1, 2022. This corresponds with the timeframe in which commercially available at-home test kits became available in the United States. The increase in at-home testing for SARS-CoV-2 likely contributed to the decrease in reported clinical positive tests in early 2022, providing an unrealistic picture of the presence of Covid-19 in the community. As measures to reduce exposure such as personal masking, clinical testing, social isolating, and quarantining continue to decline, wastewater surveillance for the presence of SARS-CoV-2 may be the best method for public health professionals to remain aware of virus dynamics in localized regions. Time-series modeling adds another layer of information when clinical data is unobtainable or underreported.

Academic translational research efforts to industry are often an underlying sought-after goal among various researchers. Through the interchanges of research endeavors between academia-industry, great innovations can/has been achieved that cater to the real-world application by bridging “industrially relevant” problem solving with pursuing fundamental studies. It is pertinent that most of the studies from university-level research works may not translate into demonstrable market products due to various reasons. Funding support, individual researcher goals, socioeconomic factors, and most importantly the technical know-how of generating revenue strategies for startups, are a few of the factors that have slowed the pace of collaborative efforts. However, we believe that the most crucial component is the identification of the critical parameters that solve long-standing problems that hinder the scale-up of the lab scale research into marketable products considering the techno-economic analysis. To illustrate this, we take the three most relevant examples of devices for fuel generation, devices to utilize solar radiation, and devices for detection and other related applications. In this perspective, we provide an in-depth case study of each of these critical parameters to comment on the direction of research avenues that can serve as step-stones for the commercialization of university-level lab research studies.

Silicon epitaxy is an essential building block in the manufacturing of complementary metal-oxide semiconductor (CMOS) devices. Accurate determination of epitaxial layer thickness is indispensable for a uniform and reproducible process. In this paper, we compare thickness values of the transition zone (TZ) in silicon epitaxial wafers obtained by two of Semilab's production-compatible electrical and optical characterization techniques: Fourier-transform infrared (FTIR) reflectometry and spreading resistance profiling (SRP). We demonstrate a high correlation between TZ thicknesses obtained from the optical modeling of FTIR reflectance spectra and SRP profiles. The dependence of TZ thickness change on the high-temperature annealing steps is also examined. FTIR reflectometry thus offers a quick, contactless alternative for obtaining structural parameters of an epitaxial layer, and these values can be well matched to those given by SRP.

Cadmium telluride is an efficient light absorbing material successfully used in solar cell technology. The efficiency of such photovoltaic devices is strongly dependent on post-deposition thermal treatments in the presence of chlorine. The benefits of this process on the absorbing layer include removal of intragrain defects, grain growth enhancement, and grain boundaries passivation. The absorber chlorination is a crucial step for which CdCl₂ is the most common choice. Its use, however, has been overshadowed by the toxicity of Cd- and Cl-containing vapors and residues. In this work, chlorine was incorporated in CdTe films during growth using sputtering targets with different chloride compounds: CdCl₂, TeCl₄, BaCl₂, CaCl₂, or LiCl. After characterizing these films, CdTe:CdCl₂ and CdTe:TeCl₄ were selected as feasible absorbers for testing their performance in photovoltaic devices. Efficiencies near 7% were obtained in as-grown unoptimized cells in which the absorber consisted of two layers: pristine CdTe and CdTe:CdCl₂ or CdTe:TeCl₄. The chlorinated layers acted as Cl sources for the adjacent CdTe and CdS, which produced a homogeneous distribution of chlorine throughout the cell. In the during-growth activating-layer (DG-AL) method used here, the chlorine diffusion during growth had a doping effect, passivated grain boundaries and defects, improved the back contact characteristics by reducing the CdTe work function, and lowered the pinhole formation probability by producing a compact chlorinated CdTe layer.

Geopolymers (GPs) are emerging, low-density ceramic materials that are simple to manufacture, with high elastic modulus and strength, albeit with low toughness. Fiber reinforcements have been used to achieve varied ductile behaviors, but little is known about the GP addition to polymeric frame structures. Thus, drawing inspiration from the nanostructure of bones, this paper investigated an interpenetrating, co-continuous composite consisting of a GP as the stiff but brittle phase, and a 3D-printed polymer (PA12 White) as the soft and deformable phase. The composite mechanical properties and failure modes were studied experimentally using uniaxial compression and four-point bending tests. The co-continuous network constrained brittle cracking within the GP and reduced strain localization in the polymer. The results showed that the composite had higher strength (56.11 ± 2.12 MPa) and elastic modulus (6.08 ± 1.37 GPa) than the 3D-printed polymer and had higher toughness (5.98 ± 0.24 MJ/mm³) than the GP for the specific geometries examined. The shape effect study demonstrated that cubic structures had higher elastic modulus and strength but at the expense of lower toughness when compared to rectangular prism structures. The study of scale effects indicated that increasing the number of periodic unit cells while maintaining consistent bulk dimensions led to augmented strength and toughness, albeit without statistically significant alterations in elastic modulus. Thus, this paper presents an experimental realization of a novel, bio-inspired, interpenetrating, GP–polymer composite design, offering improved strength and toughness. It also provides valuable insights into the shape and size effects on the mechanical properties of this new composite.

The biggest obstacles in treating cancer with traditional chemotherapy are unpleasant side effects and drug resistance. A growing amount of interest has been exhibited in using aptamers as target ligands for targeted cancer therapy and specific cancer cell identification due to their distinct benefits. Aptamer-conjugated nano-materials have recently provided new prospects in cancer treatment with their improved therapeutic efficacy and capability of reducing toxicity. Consequently, they are not perceived as alien substances our body, which allows their comfortable acceptance. Several tumor markers such as nucleolin, mucin, and the epidermal growth factor receptor can be effectively recognized by aptamers. In addition, glycoproteins on the surface of tumor cells can be recognized using aptamers. So surface modification of drug by aptamer are accomplished for enhanced tumor-specific recognition by which drug-specific accretion, internalization, and drug retention in tumors increased through specific ligand-mediated interactions and thus therapeutic index is increased. Here, we highlight some promising classes of aptamer-conjugated nanoparticles for the specific recognition of cancer cells and targeted drug delivery and the molecular mechanism and immunomodulatory regulation of these aptamer have been focused.

For the manufacture of extrusion dies, three-dimensional (3D) printing with photopolymers offers numerous advantages including flexibility, high surface quality, decent build speed, low costs and a reduced amount of waste. However, the majority of photocurable resins used in vat photopolymerization 3D printing rely on acrylates, which entail 3D-printed objects with poor mechanical properties. In particular, the high brittleness limits their application in rapid tooling, for which tough materials with high glass transition temperatures (T_g) are required. In the present study, we highlight the use of dual curable acrylate-epoxy resins with dynamic covalent bonds for the direct fabrication of extrusion dies. During digital light processing (DLP) 3D printing the acrylate network is formed, whose toughness and thermal stability are significantly enhanced by the thermoactivated formation of a second network. By following a postbaking procedure, aminoglycidiyl monomers are cured with an anhydride hardener bearing bulky norbornene groups yielding interpenetrating polymer networks with a T_g > 100°C. The tertiary amine groups present in the structure of the aminoglycidyl derivatives do not only accelerate the ring-opening reaction but also act as internal catalysts and activate bond exchange reactions between free –OH groups and ester moieties available in the photopolymer. This is confirmed by rheometer studies showing a distinctive stress relaxation at elevated temperature and giving rise to a possible reprocessability of the 3D-printed dies. With a selected resin formulation, a set of dies is printed by DLP 3D printing, with which a highly filled rubber compound is successfully extruded. The results clearly show that dual curable resins with dynamic covalent bonds are a promising class of material for rapid tooling and pave the way towards a customized and convenient fabrication of extrusion dies for rubber processing.

Today, controlling the photopolymerization process during the 3D printing in vat photopolymerization is a key challenge. In this work, it is shown that using a relatively limited set of parameter, it is possible to estimate key factors involved in such process. On the basis of 16 formulations containing different concentrations of photoinitiator and UV filter, attempt was made to rationalize the photonic parameters used in the 3D printing process, that is, the depth of penetration Dp and the critical energy Ec. It is shown that the experimental Dp values can be correlated with calculated ones from Bouguer–Beer–Lambert law. Real-time Fourier-transform infrared spectroscopy (RT-FTIR) experiments were performed under similar conditions as in 3D printing. The conversion profiles were used to estimate the Ec values. The limits of this approach was discussed as a function of the UV filter concentration. Finally, the RT-FTIR curves are exploited to predict the in-depth conversion of the different 3D printed layers and compared to experimental results obtained by confocal Raman microscopy.