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- Simulation of Ion Beam Etching of Patterned Nanometer-scale Magnetic Structures for High-Density Storage Applications

that some secondary flux particles may not contribute to redeposited layer formation even if they reach its surface Automatic extraction of 2D cut planes for direct comparison with SEM pictures Extraction of key geometrical parameters from simulated structures layer thickness angles etc Capability to setup designs of experiment with variation of process conditions material parameters as well as geometrical parameters of initial structure and masks Typical Example Densely Packed Magnetic Bits Structures with densely packed features are most challenging for Ion Milling simulation At the same time the large matrix of small magnetic islands as shown in Figure 2 is the ultimate goal of this technology To demonstrate that Victory Process can handle such dense structures we performed an ion milling simulation within a simulation domain indicated by the yellow box in the mask layout shown in Figure 3 The area outside the yellow box demonstrates 8 reflective symmetric domains which are taken into account only for redeposition This means that the local etch rates in these domains are the same as in the main simulation domain but some portion of sputtered particles may reach the main domain and participate in redeposition Figure 2 Top down image of dense pack of ion milled magnetic islands arranged in hexagonal formation The pitch or distance between centers of the islands was 20 nm This is a fragment of the SEM picture from 2 reprinted with permission from the author Dan Kercher HGST Figure 3 Mask layout with 10 nm islands and 15nm pitch The following settings were used for all simulations in this paper The ion milling was performed with 250 eV Ar and a current density of 1 5 pA μm2 The constantly rotated ion beam was tilted by 5 from surface normal and had flux divergence of 5 The etched structure consisted of two layers Chromium substrate material and the 20 nm hard Carbon mask The etch rate versus angle function for this simulation was obtain by the semi empirical Yamanura model 3 using above ion beam settings and default values for these materials Also all parameters of alloy were the same as for Chromium except the density which was set to 80 of Chromium density The milling rates as a function of incidence angle for all three materials are shown in Figure 4 Figure 4 Ion etch rate dependence on incident ion angle for three materials used in structures simulated in this paper The result of ion milling simulation for the densely packed magnetic islands is shown in Figure 5 This picture confirms that the simulator can capture main characteristics of the ion milling process in 3D faceting of hard mask alloy thickness variation due to different proximity of neighboring island and shallower etch depth in directions toward closest neighbors 0 60 120 degrees Figure 5 The final structure after 5 minutes ion milling Yellow is chromium blue regions are hard masks and red layers are redeposited alloy Calibration of Ion Milling Simulation and Process Optimization The example in

Original URL path: http://www.silvaco.fr/tech_lib_TCAD/simulationstandard/2013/apr_may_jun/a1/simulation_of_ion_beam_etching_of_patterned_nanometer-scale_magnetic_structures_for_high-Density_storage_applications_a1.html (2016-05-03)

Open archived version from archive - Plasmonic Light Trapping Transforming Thin-Film Photovoltaics

to fabrication and allows them to examine the optimum design architecture Finite Difference Time Domain FDTD method in the Atlas Luminous framework was used to examine the plasmonic effects on the performance of PV devices The plasmonic nanomaterial due to their optical properties also acts as a broadband anti reflection coating to increase light coupling to PV cells Figure 1 shows a graphical representation of the plasmonic effect of the metal nanoparticles in the PV device under illumination Such nanoparticles can be easily integrated in the PV device architecture during the fabrication process 3 Light interaction with the plasmonic structures induces plasmons i e collective surface oscillations of conduction electrons in the metal nanoparticles which traps light by either exciting localised surface plasmon resonance LSPR Figure 1a or light scattering Figure 1b Figure 1 a Light concentration by the excitation of localised surface plasmons resonance around metal nanoparticles embedded in the semiconductor of PV device b Light scattering by the metal nanoparticles at the surface of the PV device The position of the P N junction is indicated by the solid black line in the active layer of the PV device Coupled opto electronic simulations were performed on thin film amorphous silicon PV devices with gold metal nanoparticles of 30 nm radii used to demonstrate the plasmonic effects in different positions in the device structure Figure 2 More detailed information on the simulation and parameters used can be found in the published article 4 Incident light AM1 5G solar spectrum was used to perform opto electronic simulations and to calculate current density voltage J V curves photogeneration and recombination rates as well as providing spectral response data such as surface reflection absorption and transmission The syntax used for the definition of the incoming beam is defined as Beam num 1 x o 0 0 y o 25 0 angle 90 0 AM1 5 wavel start 0 295 wavel end 0 805 wavel num 51 FDTD fd auto td srate 5 prop leng 150 0 s top big index te cos phase 0 0 td errmax 0 01 dt 5 0E 18 td end periodic verbose Whereas the syntax used to define the phase matched layers is described as pml top degree 1 width 25 0 r90 0 01 pml bottom degree 1 width 25 0 r90 0 01 The material parameters of the amorphous silicon are defined as follows material material silicon mun 1 mup 0 05 nc300 2 0e21 nv300 1 0e22 eg300 1 75 affinity 4 0 taun0 1 0E 6 taup0 1 0E 6 The defects states in the bandgap of amorphous silicon are defined as follows defects nta 1 e21 ntd 1 e21 wta 0 033 wtd 0 049 nga 1 5e15 ngd 1 5e15 ega 0 62 egd 0 78 wga 0 15 wgd 0 15 sigtae 1 e 17 sigtah 1 e 15 sigtde 1 e 15 sigtdh 1 e 17 siggae 2 e 16 siggah 2 e 15 siggde 2 e 15 siggdh

Original URL path: http://www.silvaco.fr/tech_lib_TCAD/simulationstandard/2015/jan_feb_mar/a2/a2.html (2016-05-03)

Open archived version from archive - Leakage Current TCAD Calibration in a-Si TFTs

including density of states DOS and band to band tunneling What attendees will learn Basic concepts of a Si TFT TCAD simulation Basic equations Physical parameters Density of states model TCAD calibration procedure example Process and Device simulations for IV curve generation Understanding and use of density of states models Understanding and use of probability of occupation function Correlation between density of states and current density Presenter Nam Kyun Tak

Original URL path: http://www.silvaco.fr/webinar/leakage_currents_tcad_calibration_in_a-si_tfts.html (2016-05-03)

Open archived version from archive - Modeling the Optical Response of Phonon-dressed Excitons in OLED Simulations

the vibrational mode The term proportional to g 2 1 aligns the LUMO level and the band gap to the user specified value The band gap E 0 plays no essential role in determining the eigenvalues and eigenstates of the system except for shifting the resulting spectrum by the band gap energy Note that the above form of the Hamiltonian does not make reference to the detailed spatial structure of the exciton and nuclear wavefunction That information has been absorbed into the parameters described above Following Hoffman et al 3 we compute the energy spectrum of this Hamiltonian in the basis represented as where represents exciton at site n and represents a phonon cloud with specifying the phonon occupation in the oscillator at site m The oscillator at the exciton site is shifted by amount g Figure 1 as dictated by 1 and we represent its occupation number by a different symbol Thus by virtue of the dependence of phonon occupation on the location of exciton the state of the molecular distortion is coupled fully to the exciton The resulting Hamiltonian can be diagonalized using the Lang Firsov transformation 3 in which the system is described by exciton polaron whose hopping energy is given by where where are called Frank Condon factors and they are equal to the overlap of the phonon clouds at the initial and final site in a hopping event The main benefit of using harmonic oscillator to model the vibrational modes is that Frank Condon factors can be computed analytically from the inner product of shifted oscillator wavefunctions Thus the two parameters J and g fully determine the effective mass of the polaron The same Frank Condon factors also determine the amplitudes and selection rules of optical transitions A fully cohrent exciton polaron in a lattice carries a definite momentum and the energymomentum relationship yields a set of exciton bands as a function of the momentum k Since the photon momentum is negligible compared to that of an exciton optically driven transitions occur only at k 0 We therefore compute only k 0 states and exploit the fact that large inhomogeneous broadening rather than band dispersion dominates density of states at k 0 This formulation of the DOS is also consistent with assumptions underlying the hopping model of exciton dynamics simulated in Atlas C Radiative Emission and Energy transfer Following the standard treatment of dipole coupling between light and matter the Hamiltonian for the interaction of an exciton polaron with a plane wave electric field is where the sum includes both positive and negative frequencies and is the position operator A standard approach to compute absorption and emission spectra is in terms of the matrix elements of taken between the exact eigenstates of exciton polarons This is an extremely expensive calculation since a very large number of phonon cloud states exist for a given modest size and phonon occupancy In addition since most of the states are optically forbidden their inclusion in the spectrum serves only as an additional broadening mechanism In our methodology we use a much faster Green function based method to compute the absorptive and emissive contributions optical susceptibility χ ab ω χ em ω respectively In this method only the optically accessible states are referenced explicitly by the calculation while the presence of the remaining states appears as an additional broadening mechanism as is expected physically The technique is mathematically equivalent to exact diagonalization and becomes useful in the presence of sufficient broadening as is the case for organic materials 28 With homogeneous broadening specified by η the susceptibility can be written as 2 3 where is the density of molecules and N α is the number of phonons in the exciton polaron state Ψ α and Z is the partition function normalizing the Boltzmann factors Computation of χ ab ω χ em ω by 2 and 3 is done by solving a series of linear systems By organizing the basis states according to whether they are dipole allowed or not we minimize the number of systems that must be solved The spectra are subjected to energy dependent inhomogeneous broadening in the end The power radiated per unit volume in energy interval E E Δ E by spontaneous emission is given by the imaginary component of χ em 4 where f orient accounts for averaging over the random orientations of the exciton dipoles in amorphous materials Thus the radiative rate normalized to 1 exciton per unit cell volume is 5 In the case of doped materials the Förster transfer rate of a singlet from donor site D to acceptor A is 6 From this formula we also compute the F orster radius which is inter molecular distance at which the non radiative transfer equals the radiative decay of excitons Note that conventional formulas for Forster transfer use slightly different definitions for the spectra used in the overlap integral 6 See Appendix A for equivalence of k dd to conventional formula We now turn to results of our simulations with this model III Results and Discussion A Spectrum of Alq 3 Alq 3 is one of the most important host materials used in OLEDs It is known to emit green light at wavelengths of approximately 530 nm In addition it is also one of the simplest applications of the model described above Frenkel excitons in Alq 3 couple to the bending modes of the molecule where the exciton resides However the inter molecular hopping is weak and thus the vibrational modes of Alq 3 are expected to create small phonon clouds only The large inhomogeneous broadening generally render the vibrational modes unobservable in the emission and absorption spectra of Alq 3 3 However in their experiments Brinkman et al were able to obtain this for crystalline Alq 3 4 2 K 23 From their observations the authors concluded that the Huang Rhys factor g E vib 2 2 6 0 4 and E vib 0 065 22 23 Using the value g 1

Original URL path: http://www.silvaco.fr/tech_lib_TCAD/simulationstandard/2014/jan_feb_mar/a1/a1.html (2016-05-03)

Open archived version from archive - Variation Manager

Variation Manager is a new generation of tool providing efficient and reliable solutions to analog mixed signal and RF designers It provides a comprehensive suite of analysis tools that allow the designer to accurately address statistical design and to make the right design decision upfront Fast Monte Carlo Analysis Up to 30x The innovative approach of Variation Manager to Monte Carlo analysis has been designed to provide equivalent results as a classical Monte Carlo Analysis but with up to 30x time speed up High Sigma Performance Limits Highly accurate and efficient High Sigma extractor given the required sigma yield this analysis will find the design performance limits that correspond to this yield The analysis is very economic in simulations and robust to multi failure zones High Sigma Yield Estimation Robust fast high sigma yield estimator given design performance limit this analysis will quickly verify and estimate the yield to 4 6 sigma with a very limited number of simulations Variability eXplorer Analysis Exploring design performance critical zones based on a user controlled simulation budget Variability eXplorer will identify marginalities from 3 sigma to high sigma Highly cost effective providing variability induced marginal corners and most influential parameters VX is the designer best companion during development stages True Corners Extraction The Variation Manager True Corners Extraction investigates the PVT parameters that lead to the performance most likely statistical corners to achieve a given yield Features and Benefits Breakthrough analysis techniques Impressive Simulation time speed up Unique engine for local variability analysis Complete control of results accuracy Reliable and mature technology Variation Manager has been tested and validated by major companies on most aggressive technologies Smart simulation manager High simulation throughput through LSF SGE cluster Simulation result management to keep the most representative waveforms while avoiding disks saturation Simulator and environment independent

Original URL path: http://www.silvaco.fr/products/variation_analysis/iclys.html (2016-05-03)

Open archived version from archive - Library Variation Manager

and reliable solutions for standard cells statistical functional verification while preserving brute force quality Features and Benefits Breakthrough analysis techniques Impressive Simulation time speed up Unique engine for standard cells statistical verification Reliable and mature technology Tested and validated by major players on most advanced technology nodes Non intrusive tool Designed to be simply integrated into golden characterization flow without any modification Smart simulation manager Simulation results management High simulation

Original URL path: http://www.silvaco.fr/products/variation_analysis/calys.html (2016-05-03)

Open archived version from archive - SILVACO - Interconnect Application Notes

Using CLEVER 3 001 Predicting Capacitance Coupling of IPS Mode TFT LCD Using CLEVER CORPORATE About Us News Management Partners Careers Conferences Goverment Programs Locations Contact Us Solutions Overview Display Power Reliability Optical Advanced Process Development Analog HSIO Design Library

Original URL path: http://www.silvaco.fr/tech_lib_EDA/appNotes/parasiticExtraction.html (2016-05-03)

Open archived version from archive - SILVACO Presentation Materials - Cell-Level Parasitic Extraction

Extraction RC Extractor for Realistic 3D Structures Clever Competitive Analysis Physics Based Parasitic Extraction Users Guide 3D Interconnect Modeling for 90nm and Below RC Extractor for 3D Structures Physics Based Parasitic Extraction Application Examples CORPORATE About Us News Management Partners Careers Conferences Goverment Programs Locations Contact Us Solutions Overview Display Power Reliability Optical Advanced Process Development Analog HSIO Design Library Memory Design Technical Library Publications Webinars University Program Overview Partners

Original URL path: http://www.silvaco.fr/tech_lib_EDA/kbase/parasiticExtraction/cellLevelExtraction.html (2016-05-03)

Open archived version from archive