esa-sceva/satcom-chunk-collection huggingface dataset:
# Trajectory Planning and Optimization for a Par4 Parallel Robot Based on Energy Consumption
###### Abstract  
A study on trajectory planning and optimization for a Par4 parallel robot was carried out, based on energy consumption in high-speed picking and placing. In the end-effector operating space of the Par4 parallel robot, the rectangular transition of the pick-and-place trajectory was rounded by a Lame curve. A piecewise design method was adopted to accomplish trajectory shape planning for displacement, velocity and acceleration. To make the Par4 robot's end run more smoothly and to reduce residual vibration, asymmetric fifth-order and sixth-order polynomial motion laws were employed. With the aim of reaching the minimum mechanical energy consumption for the Par4 parallel robot, the recently proposed Grey Wolf Optimizer (GWO) algorithm was adopted to optimize the planning trajectory. The validity of the design method was verified by experiments, and it was found that the minimum mechanical energy consumption of the optimal trajectory planned under the law of fifth-order polynomial motion is lower than that of sixth-order polynomial motion. In addition, the experiments also revealed the optimal values of Parameters \(e\) and \(f\), which were the parameters of the Lame curve function. Parameter \(e\) can be calculated as half the pick-up span for the minimum mechanical energy consumption, unlike parameter \(f\), whose optimal value depends on specific circumstances such as the pick-and-place coordinates and the pick-up height.  
parallel robot; trajectory planning; mechanical energy consumption; Grey Wolf Optimizer; polynomial motion +
Footnote †: journal: Applied Sciences  
Article
###### Abstract  
Accurate estimation of the rotor flux angle remains a significant challenge when conventional direct or indirect field-oriented control (FOC) strategies are applied to induction motor drives. This paper proposes a novel method for determining the rotor flux angle under steady-state conditions using only stator voltage and current measurements. An adjustable steady-state detection mechanism is introduced and integrated into a phase-locked loop (PLL)-based indirect field-oriented framework to enable a smooth injection of the actual rotor flux angle into the control system. Both simulation and experimental results validate the effectiveness of the proposed method, demonstrating a significant reduction in stator current compared to conventional FOC approaches under identical load torque conditions.  
field-oriented control (FOC); induction motors; rotor flux angle estimation; stator current control; phase-locked loop (PLL) 2020 IEEEexample:BSTcontrol
## 2 Materials and Methods
### Analysis Methods  
To determine the waste chemical composition, X-ray fluorescence (XRF) was used. The concentrations of carbon and sulfur present in the waste were measured using energy-dispersive X-ray spectroscopy (EDX). Whereas, to measure the concentration of toxic elements, such as Pb, Cd, Zn, Cr, and As, inductively coupled plasma atomic emission spectroscopy (ICP-AES) was used  
Inductively Coupled Plasma (ICP) is an analytical technique used for determining metal concentrations. ICP is a type of emission spectroscopy that uses double-induction plasma (argon, in our case) to produce excited atoms and ions that emit electromagnetic radiation at characteristic wavelengths of a particular element. The intensity of this emission indicates the concentration of the element within the sample.  
The working principle of XRF is based on the excitation of the sample atoms by high-energy X-rays, followed by the emission of characteristic photons with a certain energy, well correlated to the atomic number Z of each element. The determination of the energy (or wavelength) of the emitted photon allows for qualitative analysis and the determination of the number of emitted characteristic photons allows for quantitative analysis. To perform XRF, a spectrometer is required that consists of an excitation source, sample and a detection system, which can be either wavelength-dispersive or energy-dispersive.  
Energy Dispersive X-ray Analysis (EDX), referred to as EDS or EDAX, is an X-ray technique used to identify the elemental composition of materials. EDS makes use of the X-ray spectrum emitted by a solid sample bombarded with a focused beam of electrons to obtain a localized chemical analysis. Qualitative analysis involves the identification of the lines in the spectrum and is straightforward owing to the simplicity of X-ray spectra. Quantitative analysis entails measuring line intensities for each element in the sample and comparing this data to the known composition of these same elements.
## 3 Methods
### Calculation of the Performance Ratio  
The monitoring standard IEC61724-1:2017 [48] was applied to calculate the PR. PR is defined by Equation (9) for the array-level DC performance ratio, PR\({}_{\rm A}\), and Equation (10) for the system level, PR. In this work, we use PR as one of the performance matrices to be evaluated.  
\[\mathrm{PR_{A}}=\frac{\mathrm{Y_{A}}}{\mathrm{Y_{r}}} \tag{9}\]  
\[\mathrm{PR}=\frac{\mathrm{Y_{f}}}{\mathrm{Y_{r}}} \tag{10}\]  
where the array yield in kWh/kWp, Y\({}_{A}\), is the amount of energy produced by the array, E\({}_{\rm dc}\), from each installed rated power, P\({}_{0}\), over the analysis period. Y\({}_{A}\) is equivalent to the number of hours over which the PV array produces its rated power and is defined by Equation (11).  
Figure 3: The period of data availability for each PV system; green: data is available, red: data is not available.  
\[\mathrm{Y_{A}}=\frac{\mathrm{E_{dc}}}{\mathrm{P_{0}}} \tag{11}\]  
where the reference yield in kWh/kWp, Y\({}_{\mathrm{r}}\), is the total amount of available in-plane solar irradiance in kWh/m\({}^{2}\), H\({}_{\mathrm{i}}\), divided by the reference irradiance, G\({}_{\mathrm{ref}}\), of 1000 W/m\({}^{2}\) (Equation (12).  
\[\mathrm{Y_{r}}=\frac{\mathrm{H_{i}}}{\mathrm{G_{ref}}} \tag{12}\]  
where the final yield in kWh/kWp, Y\({}_{\mathrm{f}}\), is the annual, monthly, or daily net AC energy output in kWh, E\({}_{\mathrm{ac}}\), of the PV system per installed rated power, P\({}_{0}\), given by Equation (13).  
\[\mathrm{Y_{f}}=\frac{\mathrm{E_{ac}}}{\mathrm{P_{0}}} \tag{13}\]  
Three types of PR were calculated: PR, STC temperature-corrected PR, PR\({}_{\mathrm{stc.}}\), and annual-averaged temperature-corrected PR, PR\({}_{\mathrm{ann.}}\). For the calculation of PR\({}_{\mathrm{stc.}}\) and PR\({}_{\mathrm{ann.}}\), the temperature coefficient of maximum power (Y\({}_{\mathrm{Pmp}}\)) is a critical component.
## 4 Experiments and Results
### Implementation Settings  
In the feature extraction stage, we use 128 mel filters to convert the raw audio data into a log-mel spectrogram, with a window size of 1024 and a hop size of 512. After extraction, the feature tensor enters the network encoder and decoder, whose parameters are shown in Table 1. The implementation software is PyTorch 2.7.1. We use the Adam [37] optimizer to train the model for 300 epochs, with a batch size of 16 and a learning rate of 0.002. The entire training process is completed on an NVIDIA RTX 3090 GPU (Nvidia, Santa Clara, CA, USA). With this batch and device settings, the total VRAM cost is about 4000 MB and total training time is 10 h.  
Figure 6: SS-ALIM652M1-002 voice algorithm motherboard [36].
# Steering the Clinical Translation of Delivery Systems for Drugs and Health Products
## 3 Poster Presentations
### Efficient siRNA Delivery Using Carbosilane Dendrimers for Overcoming Cancer Drug Resistance  
[PERSON] 1,*, [PERSON] 1, [PERSON] 2, [PERSON] 2, [PERSON] 3, [PERSON] 4, [PERSON] 4 and [PERSON] 1  
1 Department of Drug Science and Technology, University of Turin, Via Giuria 9, 10125 Torino, Italy  
2 Department of Pharmacy, University of Groningen, [PERSON], 1.9713 AV Groningen, The Netherlands  
3 Department of Clinical and Biological Sciences, University of Turin, c.so Raffaello 30, 10125 Torino, Italy  
4 Department of Organic Chemistry and Inorganic Chemistry, University of Alcala, Campus Universitario Alcala de Henares, 28805 Madrid, Spain  
* Correspondence: [EMAIL_ADDRESS]  
The transcription factor Nrf2 (NF-E2-related factor 2) is the master regulator of antioxidant and cytoprotective systems. Nrf2 activation appears beneficial for carcinogen detoxification in normal cells; however, its activation is critical for resistance to drugs in various tumors, including bladder cancers. For this reason, it has been postulated that Nrf2 could represent an interesting target to combat chemoresistance. Since a small number of Nrf2 inhibitors have been identified so far, the use of a specific small interfering RNA (siRNA) against this gene is an attractive possibility [21]. However, siRNAs are unstable in blood and have very poor ability to cross the lipophilic cell membranes. Considering these limitations, the use of nanocarriers have been studied to protect siRNA from degradation during systemic circulation, and transport siRNA to target cells avoiding nonspecific delivery [22]. Dendrimers are repeatedly hyperbranched polymer molecules. The well-defined size and structure, branching architecture, and high density of tailorable surface functional groups can provide significant advantages. In this context, several types of cationic dendrimers have been explored for gene therapy, being able to form electrostatic complexes with nucleic acids. In particular, carbosilane dendrimers are emerging as attractive non-viral vectors to deliver siRNA both in vitro and in vivo [23]. The aim of this work was the design, development and the characterization of carbosilane dendrimer (CDD) nanoformulations for the delivery of siRNA against Nrf2. The biological activity of siRNA loaded carbosilane dendrimers in reducing drug resistance and tumor growth in bladder cancer cell lines with a high level of Nrf2 was also evaluated.  
Stable nanosuspensions of CDD with sizes of about 300 nm were obtained. CDD were able to load siRNA and to protect it from degradation. siNrf2-CDD down-regulated the target gene in T24 cells and sensitized cisplatin-resistant cell lines to CDDP treatment. In conclusion, siNrf2-CDDs might represent a promising tool to overcome chemoresistance in bladder cancer.
## 4 SDOF Systems with Nonlinear Eddy Current Dampers
### Response to Seismic Excitations
#### 4.3.2 Displacement and Acceleration Responses to Real Earthqu
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Seismic Wave**} & \multirow{2}{*}{**Without** **Damper (m/s\({}^{2}\))**} & \multicolumn{2}{c}{**SDOF-FVD**} & \multicolumn{2}{c}{**SDOF-FCD**} \\ \cline{3-6}  & & \(\alpha\) & **PAR (m/s\({}^{2}\))** & \(\rho\) & **PAR (m/s\({}^{2}\))** & \(\rho\) \\ \hline \multirow{4}{*}{Electroro} & & 0.2 & 2.57 & 13.60\% & 2.55 & 14.43\% \\  & & 0.4 & 2.69 & 9.58\% & 2.59 & 13.09\% \\  & & 0.6 & 2.72 & 8.68\% & 2.75 & 7.54\% \\  & & 0.8 & 2.88 & 3.13\% & 2.81 & 5.54\% \\  & & 1 & 2.93 & 1.59\% & 2.86 & 3.99\% \\ \hline \multirow{4}{*}{Irpinia} & & 0.2 & 2.96 & 3.92\% & 3.05 & 0.89\% \\  & & 0.4 & 2.84 & 7.80\% & 2.84 & 7.77\% \\  & & 0.6 & 2.98 & 3.29\% & 2.92 & 5.16\% \\  & & 0.8 & 2.98 & 3.12\% & 2.94 & 4.40\% \\  & & 1 & 3.01 & 2.20\% & 2.97 & 3.39\% \\ \hline \multirow{4}{*}{ChiChi} & & 0.2 & 2.57 & 21.14\% & 2.56 & 21.54\% \\  & & 0.4 & 2.78 & 14.67\% & 2.74 & 15.78\% \\  & & 0.6 & 2.91 & 10.83\% & 2.85 & 12.70\% \\  & & 0.8 & 2.97 & 8.72\% & 2.92 & 10.51\% \\  & & 1 & 3.05 & 6.49\% & 2.95 & 9.47\% \\ \hline \multirow{4}{*}{Kobe} & & 0.2 & 2.54 & 18.77\% & 2.54 & 18.71\% \\  & & 0.4 & 2.81 & 10.21\% & 2.78 & 11.26\% \\  & & 0.6 & 3.02 & 3.48\% & 2.92 & 6.75\% \\  & & 0.8 & 3.11 & 0.71\% & 3.02 & 3.45\% \\  & & 1 & 3.12 & 0.42\% & 3.08 & 1.70\% \\ \hline \multirow{4}{*}{Northridge} & & 0.2 & 2.55 & 14.65\% & 2.51 & 15.96\% \\  & & 0.4 & 2.71 & 9.43\% & 2.66 & 11.00\% \\  & & 0.6 & 2.85 & 4.72\% & 2.75 & 7.91\% \\  & & 0.8 & 2.92 & 2.14\% & 2.87 & 4.07\% \\  & & 1 & 2.98 & 0.26\% & 2.90 & 2.88\% \\ \hline \multirow{4}{*}{Nigat} & & 0.2 & 2.79 & 10.10\% & 2.78 & 10.52\% \\  & & 0.4 & 2.94 & 5.22\% & 2.88 & 6.99\% \\  & & 0.6 & 2.96 & 4.48\% & 2.94 & 5.16\% \\  & & 0.8 & 3.01 & 3.03\% & 2.97 & 4.17\% \\  & & 1 & 3.01 & 2.85\% & 2.99 & 3.45\% \\ \hline \multirow{4}{*}{Loma Prieta} & & 0.2 & 3.14 & \(-\)1.16\% & 2.96 & 4.63\% \\  & & 0.4 & 3.06 & 1.49\% & 3.03 & 2.35\% \\  & & 0.6 & 2.97 & 4.51\% & 3.03 & 2.46\% \\  & & 0.8 & 2.96 & 4.77\% & 2.97 & 4.34\% \\  & & 1 & 3.02 & 2.80\% & 2.94 & 5.34\% \\ \hline \multirow{4}{*}{Iwate} & & 0.2 & 2.61 & 17.77\% & 2.82 & 11.19\% \\  & & 0.4 & 2.98 & 6.15\% & 2.96 & 6.75\% \\ \cline{1-1}  & & 0.6 & 3.03 & 4.49\% & 3.03 & 4.62\% \\ \cline{1-1}  & & 0.8 & 3.12 & 1.88\% & 3.07 & 3.47\% \\ \cline{1-1}  & & 1 & 3.09 & 2.73\% & 3.09 & 2.58\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Peak acceleration responses (PARs) of SDOF-ECDs and SDOF-FVDs.
## 4 Performance Analysis  
In this section, we derive the analytical expression for the ABER associated with the cooperative TU-FSO system described here. Considering the CDF shown in (9), a new highly accurate closed-form expression can be obtained for the ABER of an AF-based dual-hop TU-FSO system under all regimes of turbulence strength when employing any generalized coding technique. We will distinguish two scenarios: first, one where we can deduce an analytical closed-form expression for its associated conditional BER (CBER) of a particular signaling technique; in this case, we have provided the case of a classic uncoded OOK format that additionally can be used as a reference. Moreover, as a second scenario, we consider any generic coding scheme for which its closed-form analytical expression for CBER is unknown and, thus, closed-form expressions for the ABER cannot be easily derived. For this latter case, a curve-fitting method based on a hyper-exponential fitting technique introduced in [43] has been applied to derive a highly accurate mathematically tractable expression for CBER, which can then be applied to the procedure here described to obtain a closed-form expression for ABER.
## 5 Model-Based Simulation and Results  
Based on the results of COMSOL simulations, a reduced-order model (ROM) of the pump was generated in the form of a look-up table. This model output time-dependent net flow and electrical current from excitation voltage and frequency inputs. Figure 8 shows an overview of the closed-loop control simulations in MATLAB/Simulink, where the pump supplied insulin to [PERSON], Bergman, and Sorensen glucose-insulin models with T1 DM parameters. The R2019b version of MATLAB was used, and the solver settings were configured as \(6\times 10^{-7}\) minutes minimum step size, auto solver selection, \(1\times 10^{-4}\) relative tolerance, adaptive zero-crossing, 1440 min. (i.e., one day) stop time.  
The glucose intake model supplied glucose input to the glucose-insulin models. On top of the 100 mg/dL basal glucose, a 150 mg/dL increase lasted for 18 min after each meal. This increase was supplied via a 1/(2s + 1) delay transfer function. Voltage and frequency of the pump excitation signal were constant, and the controllers switched the pump on/off based on the difference between the reference and measured glucose. Pump displacement and the electrical current were monitored as well as the inlet and outlet flow rates. The amount of delivered insulin was calculated from the net flow rate and the volume integral of the outlet.  
As explained in Section 1.4, the simpler models, Ackerman and Bergman, are used for controller design, whereas the comprehensive Sorensen model is used for validation. Figure 9 shows the results of model-based simulations with three meal disturbances at 400, 750, and 1150 minutes. The PID controller successfully maintained the blood glucose level of the Sorensen model at around 90 mg/dL (Figure 9) and kept the insulin level at 18 mU/dL (Figure 10a). On the other hand, the \(\delta\) value of the optimal controller had a negligible effect on the insulin level. This was shown with the Bergman model,  
Figure 8: Overview of the closed-loop control simulations.  
as seen in Figure 10b, where the insulin level decreased minimally with increasing \(\delta\). The corresponding difference between the glucose levels was smaller than 0.05 mg/dL.
## 2 Materials and Methods
### Synthesis of Substrates  
2-Chloro-4-methyl-9-oxabicyclo[4.3.0]nonan-8-one (2)  
Chloro-4-methyl-9-oxabicyclo[4.3.0]nonan-8-one (2)  
Chloro-lactonization of acid **1** (1.71 g, 0.011 mol), according to the known procedure [22] gave chloroolactone **2** (1.23 g, 0.0065 mol) in 59% yield. The physical and spectral data of this product are as follows: n\({}_{\rm D}\) = 1.4900, \({}^{1}\)H NMR (600 MHz, CDCl\({}_{3}\)): 0.93 (d, \(J\) = 6.5 Hz, 3H, CH\({}_{3}\)-9), 1.61 (ddd, \(J\) = 14.8, 11.8 and 3.2 Hz, 2H, CH\({}_{2}\)-5), 1.71-1.79 (m, 1H, one of CH\({}_{2}\)-3), 1.88-1.94 (m, 1H, one of CH\({}_{2}\)-3), 1.98-2.04 (m, 1H, H-4), 2.23 (d, \(J\) = 16.4 Hz, 1H, one of CH\({}_{2}\)-7), 2.68 (dd, J=16.4 and 6.2 Hz, 1H, one of CH\({}_{2}\)-7), 2.69-2.75 (m, 1H, H-6), 4.47-4.49 (m, 1H, H-2), 4.55 (dd, \(J\) = 5.5 and 2.7 Hz, 1H, H-1), \({}^{13}\)C NMR (151 MHz, CDCl\({}_{3}\)): 21.5 (C-9), 23.2 (C-4), 32.1 (C-6), 35.6 (C-3), 35.8 (C-5), 38.1 (C-7), 55.2 (C-1), 79.8 (C-2), 175.9 (C-8), IR (KBr, cm\({}^{-1}\)): 2954, 1787, 1457, 1161, 1019, 976, _ESIHRMS_: calcd for C\({}_{9}\)H\({}_{13}\)ClO\({}_{2}\)Na, _m/z_ 211.0502 (M + H)\({}^{+}\), found 211.0508. (SI, Figures S9-S14)  
2-Bromo-4-methyl-9-oxabicyclo[4.3.0]nonan-8-one (3)  
Bromolactonization of acid **1** (1.71 g, 0.011 mol), according to the known method [23] gave bromolactone **3** (2.1 g, 0.0090 mol) in 82% yield. The physical and spectral data of this product are as follows: n\({}_{\rm D}\) = 1.5150, \({}^{1}\)H NMR (600 MHz, CDCl\({}_{3}\)): 0.93 (d, \(J\) = 6.3 Hz, 3H, CH\({}_{3}\)-9), 1.66 (ddd, \(J\) = 15.0, 11.9 and 3.3 Hz, 2H, CH\({}_{2}\)-5), 1.69-1.79 (m, 1H, one of CH\({}_{2}\)-3), 1.93-2.00 (m, 1H, one of CH\({}_{2}\)-3), 2.01-2.03 (m, 1H, H-4), 2.23 (d, \(J\) = 16.4 Hz, 1H, one of CH\({}_{2}\)-7), 2.68 (dd, \(J\) = 16.4 and 6.3 Hz, 1H, one of CH\({}_{2}\)-7), 2.74-2.84 (m, 1H, H-6), 4.58-4.60 (m, 1H, H-2), 4.65 (dd, \(J\) = 5.3 and 2.6 Hz, 1 H, H-1), \({}^{13}\)C NMR (151 MHz, CDCl\({}_{3}\)): 21.4 (C-9), 24.3 (C-4), 32.1 (C-6), 35.7 (C-3), 36.0 (C-5), 38.4 (C-7), 47.6 (C-1), 80.1 (C-2), 176.1 (C-8), IR (KBr, cm\({}^{-1}\)): 2957, 1799, 1457, 1158, 1016, 973, _ESIHRMS_: calcd for C\({}_{9}\)H\({}_{13}\)BrO\({}_{2}\)Na, _m/z_ 254.9997 and 256.9977 (M + H)+, found 254.9986 and 256.9917. (SI, Figures S15-S20)  
2-Iodo-4-methyl-9-oxabicyclo[4.3.0]nonan-8-one (4)  
Iodolactonization of acid **1** (1.36 g, 0.0088 mol) according to the known procedure [24] gave iodolactone **4** (2.1 g, 0.0075 mol) in 83% yield. The physical and spectral data of this product are as follows: \({}^{1}\)H NMR (300 MHz, CDCl\({}_{3}\)): 0.80-0.88 (m, 1H one of CH\({}_{2}\)-5), 0.94 (d, \(J\) = 6.5 Hz, 3H, CH\({}_{3}\)-9), 1.44-1.54 (m, 1H one of CH\({}_{2}\)-5), 1.69-1.74 (m, 1H, one of CH\({}_{2}\)-3), 1.90 (d, \(J\) = 16.3 Hz, 1H, one of CH\({}_{2}\)-3), 1.98-2.00 (m, 1H, H-4), 2.21 (d, \(J\) = 16.7 Hz, 1H, one of CH\({}_{2}\)-7), 2.66 (dd, \(J\) = 16.7 and 6.4 Hz, 1H, one of CH\({}_{2}\)-7), 2.80-2.90 (m, 1H, H-6), 4.66 (m, 1H, H-2), 4.80 (m, 1H, H-1), IR (film, cm\({}^{-1}\)): 2972, 1792, 1164, 960.
# A 2.4 GHz 20 W 8-Channel RF Source Module with Improved Channel Output Balance
## 4 Conclusions  
A 2.4 GHz 20 W 8-channel RF source module with improved channel output balance for plasma generator applications is proposed. To equalize the variability between channels when the impedance of the output terminal changes due to plasma generation, a method of distributing eight channels from the high-power amplifier was applied. The channel spacing was also reduced to less than 4 cm to further improve uniformity, and the overall module size was reduced by 58.4% by simplifying the circuit configuration compared to that of the previous module. In addition, a Wilkinson divider was designed to reduce the phase and magnitude difference between channels, and the results are presented. Through the brazing process, water jacket implementation was optimized, and the module was further reduced in size and weight. The RF measurement shows that the output power was 20 W for each channel, and the drain efficiency was greater than 50%. This paper demonstrates that the use of a multi-channel RF source can be a promising design method to improve the channel output balance for plasma generator applications.  
Conceptualization, formal analysis, investigation, and resources, H.N. and J.K.; methodology, software, validation, data curation, writing--original draft preparation, writing --review and editing, and visualization, H.N., T.K., T.S. and S.B.; supervision, project administration, and funding acquisition, J.K. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the fourth BK21 Program through the National Research Foundation of Korea within the Ministry of Education, and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science).  
Not applicable.  
The authors declare no conflict of interest.
###### Abstract  
We present a self-organized method based on defocused ion beam sputtering for nanostructuring glass substrates which feature antireflective and light trapping effects. By irradiating the substrate, capped with a thin gold (Au) film, a self-organized Au nanowire stencil mask is firstly created. The morphology of the mask is then transferred to the glass surface by further irradiating the substrate, finally producing high aspect ratio, uniaxial ripple-like nanostructures whose morphological parameters can be tailored by varying the ion fluence. The effect of a Ti adhesion layer, interposed between glass and Au with the role of inhibiting nanowire dewetting, has also been investigated in order to achieve an improved morphological tunability of the templates. Morphological and optical characterization have been carried out, revealing remarkable light trapping performance for the largest ion fluences. The photon harvesting capability of the nanostructured glass has been tested for different preparation conditions by fabricating thin film amorphous Si solar cells. The comparison of devices grown on textured and flat substrates reveals a relative increase of the short circuit current up to 25%. However, a detrimental impact on the electrical performance is observed with the rougher morphologies endowed with steep v-shaped grooves. We finally demonstrate that post-growth ion beam restructuring of the glass template represents a viable approach toward improved electrical performance.  
light trapping; nanopatterning; self-organization; thin film silicon solar cells; photon harvesting; photovoltaic; nanophotonics; ion beam sputtering +
Footnote †: journal: Applied Physics Letters B