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Zinc (Zn) is viewed as a promising anode material for large-scale secondary batteries. However, due to parasitic reactions and uneven Zn distribution during repeated stripping/plating cycles, Zn anodes show inferior performance and stability. To overcome such drawbacks, carboxymethyl cellulose (CMC) as an artificial solid electrolyte interphase (ASEI) is fabricated on a Zn sheet and Zn-graphite composite anode. The roles of CMC-ASEI are examined using X-ray tomography, X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS). Results show that the carboxyl group in CMC can regulate the flux and local concentration of Zn ions at the surface, allowing uniform Zn dissolution/deposition, and can suppress corrosion by reducing water activities on the anode's surface. At 5 mA cm−², the Zn-iodine battery having CMC-ASEI can cycle up to 2,000 cycles. This work provides a simple and scalable solution for advanced Zn anodes for Zn-based batteries. CA extern

Epilepsy is a widely known neurological disease, causing atypical brain activity such as seizures. Apparently, it is critical to analyse possible triggers as well as establish appropriate medical treatment based on the seizure type. In general, diagnosis of epilepsy is usually conducted by applying various state-of-the-art algorithms to extract useful information from electroencephalography (EEG) signals. For effective real-time epilepsy diagnosis, the biomedical device integrated with the best performing machine learning algorithm is needed. Multilayer Perceptron (feed-forward) Artificial Neural Network (MLP-ANN) has proven to be a much better choice over traditional supervised machine learning algorithms in achieving high accuracy diagnosis. Challenges exist in handling extremely long data processing time in the case of many features in EEG signals plus complex MLP-ANN structure and computations. This research proposes the 5-12-3 MLP-ANN configuration to classify different types of epileptic seizures using Field Programmable Gate Array (FPGA) as a real-time embedded system.

Deficit irrigation approaches have been applied in mitigation of pressure on global freshwater availability. Data from growth of plants under different water stress conditions allows the development of growth models taking into account irrigation scheduling. In this work, a model predictive control approach combined with a modified trellis decoding algorithm is applied to control growth of maize plants under deficit irrigation conditions by specifying the irrigation schedule required to achieve specific total leaf length at the end of a specified growth period. The brute force-based algorithm allows the control of growth to within 8.5 % of the desired final total leaf length over a growth period of seven days. The designed control algorithm is an adaptable solution that can be applied to different optimization goals related to plant growth and water consumption, and allows the user to evaluate best-case and worst-case scenarios in advance, which supports decision making with regard to irrigation decisions.

Machine Learning algorithms based on kernel density estimation (KDE) are said to be well suited for anomaly detection. However, existing approaches mainly cover point anomaly detection. Many industrial applications also require detecting drifts, contextual and collective anomalies. Due to the demand for small latencies, edge computing gains significance and hybrid models are no adequate solution. The main contribution is the EEM-KDE algorithm, which includes extensions of the KDE for detecting all aforementioned types of anomalies in streaming data in the edge. Finally, the proposed algorithm is evaluated showing the capability to detect different types of anomalies using an industrial control unit. CA extern

In this study, the temperature and volume fraction distributions of liquid silicon nanoparticles in the aerosol flow in gas-phase synthesis were retrieved using tomographic reconstruction of emission and extinction spectra in the 230–700 nm range. Measurements were done in an optically accessible microwave-plasma flow reactor fed with a SiH4/H2/Ar gas mixture. Optical emission and extinction spectra in the visible spectral range were captured along a line perpendicular to the flow direction covering the entire cross-section of the Si particle stream. Particle temperature and volume fraction distributions were determined and the preferred location of the silicon particles in a 1-mm thick zone at the circumference of the cylindric flow was revealed. The combined recording of line-resolved emission/extinction spectra is a promising method for spatially-resolved detection of nanoparticles in combustion or gas-phase synthesis.

The laser powder bed fusion of metals (PBF-LB/M) is one of the most promising techniques to realize lightweight optimized parts and structures. Possible design elements are internal cooling channels or topology optimized geometries. However, not only does the process suffer of instabilities causing pores and lack-of-fusion defects but also a low surface quality. A further knowledge about these defects and their influence on the mechanical behavior are needed to use additively manufactured parts in structural relevant applications. In this work, the austenitic stainless steel 316LVM (X2CrNiMo18-15-3) has been processed by PBF-LB/M. In total, four different batches were manufactured with either no intended porosity or specific cubic defects ranging between 0.3 and 1.5 mm edge length. The fatigue behavior was evaluated at stress ratio R = -1 up to 1E7 cycles. The fracture surface was analyzed by scanning electron microscopy and the relationship between artificial defect size and fatigue strength was investigated by Kitagawa-Takahashi (KT) diagram and its modification by El Haddad's intrinsic crack length. The results show that the KT-diagram underestimates the fatigue strength of the investigated steel indicating a high defect tolerance and possible hardening mechanisms during cyclic loading such as possible nano-twinning. An influence of the entrapped process gas could also play a role. As long as this is unclear, the models can only be used conservatively as the full potential of the PBF-LB/M steel cannot be fully exploited. CA extern

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Comprehensive characterization of crumpled graphene materials is required to understand their morphologically dependent properties. This study connects the optical properties of crumpled few-layer graphene (FLG) aerosols and colloidal suspensions with particle morphology. The mass absorption cross-section (MAC) of crumpled FLG was measured in the aerosol phase and it is shown that such aerosols absorb visible light more efficiently than soot aerosols. The UV–Vis spectra of FLG suspensions in ethanol were correlated with the mean nanoparticle layer number and the lateral size. The measured optical properties were also simulated using discrete dipole approximation (DDA) applied to volume-reconstructed particles with refractive indices of graphene and graphite from literature. The measurements were more closely reproduced using the refractive index of graphite pellets rather than flat graphene on a substrate. Moreover, we show that a simpler Rayleigh–Debye–Gans (RDG) model can predict the wavelength dependence of the crumpled FLG absorption cross-section.

Multi-regime effects occur due to the interaction of combustion phenomena such as partial premixing of reactants or product-recirculation and lead to the invalidity of idealization of local reaction zones by purely premixed or purely non-premixed flame structures. The recently proposed multi-regime burner (MRB) at the Hochschule Darmstadt and the TU Darmstadt is investigated using highly-resolved Large-Eddy Simulation (LES) regarding the present combustion modes – with focus on MILD combustion – and overall flame characteristics. Thermochemical experimental data and highly resolved LES are compared for two selected operating conditions MRB18b and MRB26b. The experimental investigation focuses on the overall flame structure by examining radial profiles of temperature and mixture fraction, as well as scatter plots of temperature and CH₄ versus mixture fraction. The objective of this analysis is to provide insights into the reaction zone structure which are difficult to extract by experimental means, by using highly-resolved Large-Eddy Simulations under flow conditions representative of MRB18b and MRB26b. The generated database was used to allow for a separate analysis of the inner and outer flame branches. SO₂ measurements were analyzed together with the simulated temperature fields to further assess the flame stabilization mechanism in this configuration. The importance of different flame zones and burning modes was analyzed using the flame index and temperature locus diagrams. The effects of the flame zones are found to evolve with the downstream distance and show distinct differences between the two operating conditions. The applied diagnostics reveal the spatial and thermodynamical state of the different regimes.

Gas-phase iron compounds strongly affect the flame structure already at very low concentrations, which implies the control of combustion efficiency, pollution formation, and materials synthesis in flames. The impact of iron pentacarbonyl on low-pressure premixed flames was investigated experimentally and numerically for a broad range of equivalence ratios. The burner was operated in top-to-bottom orientation, causing a strong effect of buoyancy on the flow field, a configuration, also known as buoyancy-opposed flame. The application of ultra-sensitive broadband intracavity laser absorption diagnostics enabled path-integrated measurements of gas-phase FeO in the particle-laden flow. Spatially-resolved temperature distributions were measured via OH laser-induced fluorescence. The measurements were complemented by detailed simulations of the down-firing flame to determine the (one-dimensional) flow field on the centerline of the burner. The experimental findings were the basis for extension of existing reaction schemes for iron-doped flames and a new skeletal scheme was proposed. Measured temperatures and normalized FeO concentrations were used to validate both the detailed and the skeletal scheme. The results of the optimization and reduction procedure helped to improve the understanding of the structure of the iron-doped flame and the role of iron-cluster formation in the interaction mechanisms which cause the flame inhibition or promotion by iron-compounds.

Late-evaporating liquid fuel wall-films are considered a major source of soot in spark-ignition direct-injection (SIDI) engines. In this study, a direct-injection model experiment was developed to visualize soot formation in the vicinity of evaporating fuel films. Isooctane is injected by a multi-hole injector into the optically accessible part of a constant-flow facility at atmospheric pressure. Some of the liquid fuel impinges on the quartz-glass windows and forms fuel films. After spark ignition, a turbulent flame front propagates through the chamber, and subsequently sooting combustion is detected near the fuel films. Overlapping laser light sheets at 532 and 1064 nm excite laser-induced fluorescence (LIF) of polycyclic aromatic hydrocarbons (PAH) -potential soot precursors- and laser-induced incandescence (LII) of soot, respectively. The 532 nm light sheet has low fluence to avoid the excitation of LII. The LII and LIF signals are detected simultaneously and spectrally separated on two cameras. In complementary line-of-sight imaging, the fuel spray, chemiluminescence, and soot incandescence are captured with a high-speed color camera. In separate experiments, toluene is added to the isooctane as a fluorescent tracer and excited by pulsed 266 nm flood illumination. From images of the LIF signal, the fuel-films’ thickness and mass evolutions are evaluated. The films survive the entire combustion event. PAH LIF is found in close vicinity of the evaporating fuel films. Soot is found spatially separated from, but adjacent to the PAH, both with high spatial intermittency. Average images additionally indicate that soot is formed with a much higher spatial intermittency than PAH. Images from the color camera show soot incandescence earlier and in a similar region compared to soot LII. Chemiluminescence downstream of the soot-forming region is thought to indicate the subsequent oxidation of fuel, soot, and PAH.

We report state-resolved absorption cross-section measurement and oscillator-strength evaluation of the gas-phase iron oxide (FeO) orange system near 611 nm. Intracavity absorption spectroscopy (ICAS) with a homemade broadband dye laser was applied for time-resolved measurements of absorption spectra of shock-activated mixtures of iron pentacarbonyl and carbon dioxide (diluted in argon), generating gas-phase FeO. The measurements were performed with a time resolution of 170 µs in the spectral range of 16,316–16,353 cm−1 that includes a large number of FeO absorption lines. Across the 8-cm diameter of the shock tube, ICAS leads to an effective absorption path length of 260 m. Absorption cross-section values of 0.5 × 10–18–4 × 10–18 cm2 were determined for temperatures around 2200 K and pressures of ∼1.3 bar. Pressure- and temperature-independent oscillator strengths for individual ro-vibronic transitions within the 611-nm band of FeO orange system are reported for the first time. These data are generally applicable for quantitative absorption measurements of flame studies of iron chemistry, where FeO plays a key role as intermediate species.

Ethanol is known to be prone to pre-ignition in internal combustion engines under high-load conditions and its ignition shows large deviations from ideal, spatially, and temporally-homogeneous ignition in shock tubes at moderate temperatures (800–950 K). In this context, the ignition of stoichiometric ethanol/O2 mixtures with various levels of inert gas dilution was investigated in a high-pressure shock tube at ≅20 bar between 800 and 1250 K. Ignition delay times were determined from spatially integral detection of chemiluminescence emission. Additionally, high-repetition-rate color imaging enabled the differentiation of the luminescence in time, space, and spectral range between various ignition modes. In the low-temperature range (800–860 K), different inhomogeneous ignition modes were identified. The addition of small amounts of helium into the undiluted fuel/air mixture was found to be efficient to mitigate pre-ignition, attributed to a variation in heat transfer and thus suppression of the build-up of local temperature inhomogeneities. The experiments in case of spatially homogeneous ignition show very good agreement with the predictions based on three detailed kinetics mechanisms (Zhang et al., CNF 190 (2018) 74, Frassoldati et al., CNF 159 (2012) 2295, and Zhou et al. CNF 197 (2018) 423), inhomogeneities, however, resulted in a shortening of the ignition delay times up to a factor of 2.6.

Tetramethylsilane is a precursor often used for the production of flame-synthesized silica nanoparticles or coatings. This study investigates the chemical reaction mechanism of tetramethylsilane in a series of H2/O2/Ar low-pressure (p = 30 mbar) flames from fuel-lean to slightly fuel-rich flame conditions (φ=0.8, 1.0 and 1.2). Mole fraction profiles are obtained by molecular-beam mass spectrometry. The experimental data are compared to simulations using a recently published reaction mechanism. The present study reveals the influence of the flame composition on the depletion of the precursor TMS, the formation of its main carbon-containing products (e.g. CO2 and CO) and the main silicon-containing intermediates (e.g. Si(CH3)3(CH2)OO), Si(OH)4, SiO2, Si4O10H4) appearing along the routes of particle formation. TEM images of synthesized particles reveal that the nanoparticles obtained from the gas-phase synthesis are spheres with a low degree of agglomeration. The particle size distribution appears to be dependent on the equivalence ratio of the synthesis flames and the changes can tentatively be traced to different particle formation pathways. The data set provided in this work can serve a basis for improvements to the reaction mechanisms of the Si/C/H/O system that are urgently needed to improve particle synthesis processes.

Shock-tube and flow-reactor experiments were used to study the thermal decomposition of diethyl carbonate (C2H5OC(O)OC2H5; DEC). The formation of CO2, C2H4, and C2H5OH was measured with gas chromatography/mass spectrometry (GC/MS) and high-repetition-rate time-of-flight mass spectrometry (HRR-TOF-MS) behind reflected shock waves. The same products were also detected by GC/MS in flow reactor experiments. All experiments combined span a temperature range of 663–1203 K at pressures between 1.0 and 2.0 bar. Time-resolved species concentration profiles from HRR-TOF-MS and product compositions from GC/MS measurements were simulated applying a detailed reaction mechanism for DEC combustion. A master-equation analysis was conducted based on computed energies from G4 calculations. Quantum chemical calculations confirm that DEC primarily decomposes by six-center elimination, C2H5OC(O)OC2H5 → C2H4 + C2H5OC(O)OH (1a) , followed by rapid decomposition of the alkoxy acid, C2H5OC(O)OH → C2H5OH + CO2 (1b) . Measured DEC decomposition rate constants k(T) at p ≈ 1.5 bar can be represented by the Arrhenius equation k(T) = 1013.64±0.12 exp(−204.24±1.95 kJ/mol/RT) s − 1. Theoretical predictions for k1a were in good agreement with experimentally derived values. The theoretical analysis also included dipropyl carbonate (C3H7OC(O)OC3H7; DPC) decomposition and the reactivities of DEC and DPC are compared and discussed in the context of reactivity of dialkyl carbonates under pyrolytic conditions.

Understanding the combustion of methyl esters is crucial to elucidate kinetic pathways and predict combustion parameters, soot yields, and fuel performance of biodiesel, however most kinetic studies of methyl esters have focused on smaller, surrogate model esters. Methyl hexanoate is a larger methyl ester approaching the chain length of methyl esters found in biodiesel and has not received as much research attention as other smaller esters. The purpose of this work is to present the first atmospheric pressure combustion data of methyl hexanoate, CH3CH2CH2CH2CH2COOCH3. Mixtures of 2% methyl hexanoate in O2 and N2 are studied using a plug flow reactor at atmospheric pressure, wall temperatures from 573 to 973 K, residence times from roughly 1-2 s., and fuel equivalence ratios of 1, 1.5, and 2. Exhaust gases are analyzed by a gas chromatograph-mass spectrometer system and species mole fractions are presented. The literature model shows satisfactory agreement with the experimental species profiles and improvements for future mechanistic studies are suggested. In particular, this work proposes new unimolecular decomposition pathways of methyl hexanoate to form methanol or methyl acetate. Furthermore, the experiment detected three unsaturated esters that are direct products of the low temperature oxidation chemistry and it provides more insight into branching ratios for the formation of methyl hexanoate radicals and for the decomposition of hydroperoxyalkyl radicals.

Piston engines can be operated with very fuel-rich fuel/air mixtures to simultaneously produce syngas, power, and heat – so-called “polygeneration”. In this context, the effects of methoxymethane (dimethyl ether, DME), ethoxyethane (diethyl ether, DEE), and n-heptane as additives in compression-ignition of fuel-rich methane/air mixtures were investigated in experiment and simulation. The experiments were performed in a single-cylinder octane-number test engine at a compression ratio of 10. Engine operating stability, auto-ignition behavior, and syngas production were examined. The simulations used a single zone model with detailed chemical kinetics. The method for pressure trace analysis was adapted to the very fuel-rich conditions examined in this study. The choice of additive does not significantly influence syngas production, but a distinct influence on auto-ignition was found. The most effective additive in terms of mass fraction was DEE which produced stable operation at around 20% by weight. While the use of DME and n-heptane resulted in similar heat release traces, DEE yielded more early heat release and less of a negative temperature coefficient (NTC) behavior. The widest stable operating range in terms of additive fraction was found for DME. A reaction path analysis showed that the effect on ignition is similar for all three additives: they react early in the compression stroke and lead to H-abstraction from CH₄. Comparing heat release rates and calculated cylinder temperatures indicated that not only the additive's reactivity but also its heat capacity contributes to auto-ignition behavior. CA Kaiser

Laser powder bed fusion (PBF-LB/M) of bulk metallic glasses (BMGs) has experienced growing scientific and industrial interest in the last years, with a special focus on application relevant systems based on zirconium. The high cooling rates and the layer-wise build-up process allow overcoming size and geometry limitations typical for conventional casting routes. Yet, the novel production approach requires different alloy characteristics than casting processes. The present work reports for the first time on the PBF-LB/M-processing of three CuTi-based bulk metallic glass formers in the Vit101 system, allowing to exceed the mechanical performance of most additively formed Zr-based BMGs. Furthermore, the influence of alloy properties like thermal stability and toughness on the PBF-LB/M applicability are systematically studied. Thermal stability plays a minor role to produce amorphous specimen, while notch toughness is found to be a more crucial aspect to achieve parts with low defect density and resulting high mechanical performance. The results suggest fundamentally different alloy development strategies adapted to the needs of the PBF-LB/M-process, leaving classical casting-based optimization of glass forming ability behind and evolving towards a rather toughness-oriented optimization.

The stability of graphene structure in sulfur-doped graphene catalyst is demonstrated to be a key aspect during the ozonation process. Enhancing the stability of the sulfur-doped graphene structure is therefore important to improve its catalytic activity during the ozonation process. However, this has remained a challenge so far. Therefore, we adopted a low-energy microwave plasma technique to synthesize a high purity sulfur-doped graphene (S ⎯ Gr) catalyst for the ozonation process. The effect of S ⎯ Gr in the ozonation process was tested using carbamazepine (CBZ; 0.05 mM) as a probe compound. A complete CBZ removal was obtained at an ozone concentration of 0.08 mM while in comparison with single O

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This paper is a continuation of our work done in Part I, in which the a priori and budget analyses were conducted, Wen et al. (2019). In this work, we focus on addressing specific and recurring issues in flamelet modeling for pulverized coal combustion, including strong heat losses, multi-mode combustion and reaction progress variable definition. First, extended flamelet formulations are developed that can take into account strong heat loss effects in pulverized coal combustion systems. Then, to characterize multi-mode combustion in pulverized coal flames, a coupled premixed and non-premixed flamelet model is developed using the combustion mode index. Finally, the effects of reaction progress variable definition on the flamelet predictions are quantified. A state-of-the-art direct numerical simulation database is employed to challenge the newly developed flamelet models. The tabulated thermo-chemical quantities are compared with the reference direct numerical simulation results through a priori analyses. Comparisons show that the newly developed flamelet models which take into account strong heat loss effects can predict the gas temperature and species mass fractions correctly. The adiabatic flamelet models over-predict the corresponding thermo-chemical quantities in regions where the interphase heat transfer is significant. Coupled with a linear extrapolation method, the prediction of the gas temperature with the adiabatic flamelet models can be improved. The performance of the multi-mode flamelet model depends on whether the local combustion mode can be correctly identified. The conventional combustion mode index based on the gradients of fuel and oxidizer species mass fractions cannot correctly identify the combustion mode in the entire combustion field.

Model-free adaptive control has been used to design feedback in cases when accurate mathematical modeling of the system can not be realized. By using only input-output information, the control approach is attractive with respect to minimal design efforts. In this contribution an improved model-free control program is proposed and applied to flexible systems. The main control idea is based on the compact-form dynamic linearization technique. A linearized controller structure which contains a matrix of unknown time-varying parameters namely pseudo-partial derivative can be designed. First, an equivalent linearized data-based model of the original system is established and corrected locally by using the recursive least-squares estimation algorithm. Then a modified objective function with respect to the controller parameter matrix considering minimization of the current tracking errors and its variations is proposed for control performance improvement. Finally, the required control inputs are calculated to fulfill control requirements. For illustration and as example, the newly introduced method is applied to reduce vibrations of an elastic crane representing a multivariable system. The control effectiveness is verified nummerically and compared with conventional model-free and PI controllers.

In this paper chattering mitigated sliding mode control of uncertain nonlinear systems is considered. Concrete knowledge about the system parameters or uncertainty bounds is assumed to be unavailable. A combined sliding mode and data-driven model-free predictive control strategy is proposed. Calculation of the predictive control input is based on a linearized system description. The parameters of the linearized model are estimated online using a Kalman filter and input-output data. The sliding mode controller guarantees boundedness of the tracking error. The switching gain adapts online which avoids the uncertainty bounds of the system to be known. Overestimation of the bounds is avoided by the use of the predictive controller, leading to mitigation of the chattering effect. The effectiveness of the proposed strategy is confirmed by a simulation example.

In this paper output constrained sliding mode control of nonlinear relative degree two systems is considered. The constraints are formulated with respect to the first derivative of the control variable. The system may be effected by matched disturbances. Only the uncertainty bounds are required to be known. A multi-controller approach with variable gains is proposed. The controller guarantees that the constraints can at most be violated for a finite-time, which can be shortened by tuning the controller parameters. Despite the action of the multiple controllers the tracking error of the approach is guaranteed to be bounded.

In wind energy operation and maintenance costs significantly contribute to the overall cost. This paper proposes a novel adaptive lifetime control approach for wind turbines to reduce operation and maintenance costs. The approach is based on a cascade structure with the outer loop utilizing structural health monitoring and prognosis techniques to determine suitable controller parameters and reference values of the inner loop. The trade-off between power production and load reduction is balanced to achieve predefined service lifetime using the knowledge of current system state-of-health and predicted future damage accumulation behavior. Unscheduled downtime is avoided by guaranteeing the predefined lifetime, hence reducing the maintenance cost. Simulation results using a reference wind turbine model show that the proposed control strategy can regulate the lifetime or the accumulated damage to the desired value with a reasonable sacrifice in harvested power.

Digitization is changing our world and industry. One of the flagships of the current industrial revolution, the so-called Industry 4.0, is the digital twin. The term digital twin is being widely discussed, but it is often unclear to the operators and contractors what added value can be generated from the digital twin and how business models can be shaped in the digital world due to unclear creation and updating procedures and costs. The deterrent factors are the large-scale effort of building the digital twin and synchronizing it with the real object. The partial models as well as the planning, live and historical data have to be integrated into a single framework. The goal of this paper is to analyze different applications and the possible design methods of the digital twin. Another aim is to present the advantages and disadvantages of the respective methods and to suggest suitable design methods for the selected applications. CA Adamenko

This work develops flamelet tabulation methods for solid fuel combustion with and without fuel-bound nitrogen based on computations in particle-laden counterflow flames. The proposed flamelet tabulation methods for NO prediction are evaluated for two different coal types. The results show that extracting the NO mass fraction from the flamelet library directly results in significant discrepancies in the studied fuel nitrogen-free flame, while reasonable predictions can be obtained by using the same method in the fuel-bound nitrogen flames for both coal types. In contrast, solving a transport equation for the NO mass fraction tends to improve the NO prediction. The NO concentration is well predicted by splitting the NO source term into a formation part and a rescaled consumption part. The best NO prediction is obtained by extracting the formation part and the rescaled consumption part with a modified reaction progress variable.