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Nanoparticles are recognized as highly attractive tunable materials for designing field-effect biosensors with enhanced performance. In this work, we present a theoretical model for electrolyte-insulator-semiconductor capacitors (EISCAP) decorated with ligand-stabilized charged gold nanoparticles. The charged AuNPs are taken into account as additional, nanometer-sized local gates. The capacitance-voltage (C–V) curves and constant-capacitance (ConCap) signals of the AuNP-decorated EISCAPs have been simulated. The impact of the AuNP coverage on the shift of the C–V curves and the ConCap signals was also studied experimentally on Al–p-Si–SiO₂ EISCAPs decorated with positively charged aminooctanethiol-capped AuNPs. In addition, the surface of the EISCAPs, modified with AuNPs, was characterized by scanning electron microscopy for different immobilization times of the nanoparticles.
Because of simple construction process, high energy efficiency, significant fire resistance and excellent sound isolation, masonry infilled reinforced concrete (RC) frame structures are very popular in most of the countries in the world, as well as in seismic active areas. However, many RC frame structures with masonry infills were seriously damaged during earthquake events, as the traditional infills are generally constructed with direct contact to the RC frame which brings undesirable infill/frame interaction. This interaction leads to the activation of the equivalent diagonal strut in the infill panel, due to the RC frame deformation, and combined with seismically induced loads perpendicular to the infill panel often causes total collapses of the masonry infills and heavy damages to the RC frames. This fact was the motivation for developing different approaches for improving the behaviour of masonry infills, where infill isolation (decoupling) from the frame has been more intensively studied in the last decade. In-plane isolation of the infill wall reduces infill activation, but causes the need for additional measures to restrain out-of-plane movements. This can be provided by installing steel anchors, as proposed by some researchers. Within the framework of European research project INSYSME (Innovative Systems for Earthquake Resistant Masonry Enclosures in Reinforced Concrete Buildings) the system based on a use of elastomers for in-plane decoupling and steel anchors for out-of-plane restrain was tested. This constructive solution was tested and deeply investigated during the experimental campaign where traditional and decoupled masonry infilled RC frames with anchors were subjected to separate and combined in-plane and out-of-plane loading. Based on a detailed evaluation and comparison of the test results, the performance and effectiveness of the developed system are illustrated.
FEM shakedown analysis of structures under random strength with chance constrained programming
(2022)
Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable.
A capacitive electrolyte-insulator-semiconductor (EISCAP) biosensor modified with Tobacco mosaic virus (TMV) particles for the detection of acetoin is presented. The enzyme acetoin reductase (AR) was immobilized on the surface of the EISCAP using TMV particles as nanoscaffolds. The study focused on the optimization of the TMV-assisted AR immobilization on the Ta 2 O 5 -gate EISCAP surface. The TMV-assisted acetoin EISCAPs were electrochemically characterized by means of leakage-current, capacitance-voltage, and constant-capacitance measurements. The TMV-modified transducer surface was studied via scanning electron microscopy.
An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.
Utilizing an appropriate enzyme immobilization strategy is crucial for designing enzyme-based biosensors. Plant virus-like particles represent ideal nanoscaffolds for an extremely dense and precise immobilization of enzymes, due to their regular shape, high surface-to-volume ratio and high density of surface binding sites. In the present work, tobacco mosaic virus (TMV) particles were applied for the co-immobilization of penicillinase and urease onto the gate surface of a field-effect electrolyte-insulator-semiconductor capacitor (EISCAP) with a p-Si-SiO₂-Ta₂O₅ layer structure for the sequential detection of penicillin and urea. The TMV-assisted bi-enzyme EISCAP biosensor exhibited a high urea and penicillin sensitivity of 54 and 85 mV/dec, respectively, in the concentration range of 0.1–3 mM. For comparison, the characteristics of single-enzyme EISCAP biosensors modified with TMV particles immobilized with either penicillinase or urease were also investigated. The surface morphology of the TMV-modified Ta₂O₅-gate was analyzed by scanning electron microscopy. Additionally, the bi-enzyme EISCAP was applied to mimic an XOR (Exclusive OR) enzyme logic gate.
Concentrating solar power
(2022)
The focus of this chapter is the production of power and the use of the heat produced from concentrated solar thermal power (CSP) systems.
The chapter starts with the general theoretical principles of concentrating systems including the description of the concentration ratio, the energy and mass balance. The power conversion systems is the main part where solar-only operation and the increase in operational hours.
Solar-only operation include the use of steam turbines, gas turbines, organic Rankine cycles and solar dishes. The operational hours can be increased with hybridization and with storage.
Another important topic is the cogeneration where solar cooling, desalination and of heat usage is described.
Many examples of commercial CSP power plants as well as research facilities from the past as well as current installed and in operation are described in detail.
The chapter closes with economic and environmental aspects and with the future potential of the development of CSP around the world.
Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.
Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.
Hydrogen is playing an increasingly important role in research and politics as an energy carrier of the future. Since hydrogen has commonly been produced from methane by steam reforming, the need for climate-friendly, alternative production routes is emerging. In addition to electrolysis, fermentative routes for the production of so-called biohydrogen are "green" alternatives. The application of microorganisms offers the advantage of sustainable production from renewable resources using easily manageable technologies. In this project, the hyperthermophilic, anaerobic microorganism Thermotoga neapolitana is used for the productio nof biohydrogen from renewable resources. The enzymatically hydrolyzed resources were used in fermentation leading to yield coefficients of 1.8 mole H₂ per mole glucose when using hydrolyzed straw and ryegrass supplemented with medium, respectively. These results are similar to the hydrogen yields when using Thermotoga basal medium with glucose (TBGY) as control group. In order to minimize the supplementation of the hydrolysate and thus increase the economic efficiency of the process, the essential media components were identified. The experiments revealed NaCl, KCl, and glucose as essential components for cell growth as well as biohydrogen production. When excluding NaCl, a decrease of 96% in hydrogen production occured.
Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as “colourization”) of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples’ total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization.
Nuclear magnetic resonance (NMR) spectrometric methods for the quantitative analysis of pure heparin in crude heparin is proposed. For quantification, a two-step routine was developed using a USP heparin reference sample for calibration and benzoic acid as an internal standard. The method was successfully validated for its accuracy, reproducibility, and precision. The methodology was used to analyze 20 authentic porcine heparinoid samples having heparin content between 4.25 w/w % and 64.4 w/w %. The characterization of crude heparin products was further extended to a simultaneous analysis of these common ions: sodium, calcium, acetate and chloride. A significant, linear dependence was found between anticoagulant activity and assayed heparin content for thirteen heparinoids samples, for which reference data were available. A Diffused-ordered NMR experiment (DOSY) can be used for qualitative analysis of specific glycosaminoglycans (GAGs) in heparinoid matrices and, potentially, for quantitative prediction of molecular weight of GAGs. NMR spectrometry therefore represents a unique analytical method suitable for the simultaneous quantitative control of organic and inorganic composition of crude heparin samples (especially heparin content) as well as an estimation of other physical and quality parameters (molecular weight, animal origin and activity).
Frequency mixing magnetic detection (FMMD) has been explored for its applications in fields of magnetic biosensing, multiplex detection of magnetic nanoparticles (MNP) and the determination of core size distribution of MNP samples. Such applications rely on the application of a static offset magnetic field, which is generated traditionally with an electromagnet. Such a setup requires a current source, as well as passive or active cooling strategies, which directly sets a limitation based on the portability aspect that is desired for point of care (POC) monitoring applications. In this work, a measurement head is introduced that involves the utilization of two ring-shaped permanent magnets to generate a static offset magnetic field. A steel cylinder in the ring bores homogenizes the field. By variation of the distance between the ring magnets and of the thickness of the steel cylinder, the magnitude of the magnetic field at the sample position can be adjusted. Furthermore, the measurement setup is compared to the electromagnet offset module based on measured signals and temperature behavior.
Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin’s molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6% and 12.9% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin’s molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems.
Heparin is a natural polysaccharide, which plays essential role in many biological processes. Alterations in building blocks can modify biological roles of commercial heparin products, due to significant changes in the conformation of the polymer chain. The variability structure of heparin leads to difficulty in quality control using different analytical methods, including infrared (IR) spectroscopy. In this paper molecular modelling of heparin disaccharide subunits was performed using quantum chemistry. The structural and spectral parameters of these disaccharides have been calculated using RHF/6-311G. In addition, over-sulphated chondroitin sulphate disaccharide was studied as one of the most widespread contaminants of heparin. Calculated IR spectra were analyzed with respect to specific structure parameters. IR spectroscopic fingerprint was found to be sensitive to substitution pattern of disaccharide subunits. Vibrational assignments of calculated spectra were correlated with experimental IR spectral bands of native heparin. Chemometrics was used to perform multivariate analysis of simulated spectral data.
An improved and convenient ninhydrin assay for aminoacylase activity measurements was developed using the commercial EZ Nin™ reagent. Alternative reagents from literature were also evaluated and compared. The addition of DMSO to the reagent enhanced the solubility of Ruhemann's purple (RP). Furthermore, we found that the use of a basic, aqueous buffer enhances stability of RP. An acidic protocol for the quantification of lysine was developed by addition of glacial acetic acid. The assay allows for parallel processing in a 96-well format with measurements microtiter plates.
The replacement of existing spillway crests or gates with labyrinth weirs is a proven techno-economical means to increase the discharge capacity when rehabilitating existing structures. However, additional information is needed regarding energy dissipation of such weirs, since due to the folded weir crest, a three-dimensional flow field is generated, yielding more complex overflow and energy dissipation processes. In this study, CFD simulations of labyrinth weirs were conducted 1) to analyze the discharge coefficients for different discharges to compare the Cd values to literature data and 2) to analyze and improve energy dissipation downstream of the structure. All tests were performed for a structure at laboratory scale with a height of approx. P = 30.5 cm, a ratio of the total crest length to the total width of 4.7, a sidewall angle of 10° and a quarter-round weir crest shape. Tested headwater ratios were 0.089 ≤ HT/P ≤ 0.817. For numerical simulations, FLOW-3D Hydro was employed, solving the RANS equations with use of finite-volume method and RNG k-ε turbulence closure. In terms of discharge capacity, results were compared to data from physical model tests performed at the Utah Water Research Laboratory (Utah State University), emphasizing higher discharge coefficients from CFD than from the physical model. For upstream heads, some discrepancy in the range of ± 1 cm between literature, CFD and physical model tests was identified with a discussion regarding differences included in the manuscript. For downstream energy dissipation, variable tailwater depths were considered to analyze the formation and sweep-out of a hydraulic jump. It was found that even for high discharges, relatively low downstream Froude numbers were obtained due to high energy dissipation involved by the three-dimensional flow between the sidewalls. The effects of some additional energy dissipation devices, e.g. baffle blocks or end sills, were also analyzed. End sills were found to be non-effective. However, baffle blocks with different locations may improve energy dissipation downstream of labyrinth weirs.
Non-intrusive measuring techniques have attained a lot of interest in relation to both hydraulic modeling and prototype applications. Complimenting acoustic techniques, significant progress has been made for the development of new optical methods. Computer vision techniques can help to extract new information, e. g. high-resolution velocity and depth data, from videos captured with relatively inexpensive, consumer-grade cameras. Depth cameras are sensors providing information on the distance between the camera and observed features. Currently, sensors with different working principles are available. Stereoscopic systems reference physical image features (passive system) from two perspectives; in order to enhance the number of features and improve the results, a sensor may also estimate the disparity from a detected light to its original projection (active stereo system). In the current study, the RGB-D camera Intel RealSense D435, working on such stereo vision principle, is used in different, typical hydraulic modeling applications. All tests have been conducted at the Utah Water Research Laboratory. This paper will demonstrate the performance and limitations of the RGB-D sensor, installed as a single camera and as camera arrays, applied to 1) detect the free surface for highly turbulent, aerated hydraulic jumps, for free-falling jets and for an energy dissipation basin downstream of a labyrinth weir and 2) to monitor local scours upstream and downstream of a Piano Key Weir. It is intended to share the authors’ experiences with respect to camera settings, calibration, lightning conditions and other requirements in order to promote this useful, easily accessible device. Results will be compared to data from classical instrumentation and the literature. It will be shown that even in difficult application, e. g. the detection of a highly turbulent, fluctuating free-surface, the RGB-D sensor may yield similar accuracy as classical, intrusive probes.
Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables.
The development and operation of hybrid or purely electrically powered aircraft in regional air mobility is a significant challenge for the entire aviation sector. This technology is expected to lead to substantial advances in flight performance, energy efficiency, reliability, safety, noise reduction, and exhaust emissions. Nevertheless, any consumed energy results in heat or carbon dioxide emissions and limited electric energy storage capabilities suppress commercial use. Therefore, the significant challenges to achieving eco-efficient aviation are increased aircraft efficiency, the development of new energy storage technologies, and the optimization of flight operations. Two major approaches for higher eco-efficiency are identified: The first one, is to take horizontal and vertical atmospheric motion phenomena into account. Where, in particular, atmospheric waves hold exciting potential. The second one is the use of the regeneration ability of electric aircraft. The fusion of both strategies is expected to improve efficiency. The objective is to reduce energy consumption during flight while not neglecting commercial usability and convenient flight characteristics. Therefore, an optimized control problem based on a general aviation class aircraft has to be developed and validated by flight experiments. The formulated approach enables a development of detailed knowledge of the potential and limitations of optimizing flight missions, considering the capability of regeneration and atmospheric influences to increase efficiency and range.