Non-destructive extraction of junction depths of active doping profiles from photomodulated optical reflectance offset curves

The ITRS Roadmap highlights the electrical characterization of the source and drain extension regions as a key challenge for future complimentary-metal-oxide-semiconductor technology. Presently, an accurate determination of the depth of ultrashallow junctions can routinely only be performed by time-consuming and destructive techniques such as secondary ion mass spectrometry (SIMS). In this work, the authors propose to use the fast and nondestructive photomodulated optical reflectance (PMOR) technique , as implemented in the Therma-Probe\textregistered (TP) dopant metrology system, for these purposes. PMOR is a pump-probe technique based on the measurement of the pump-induced modulated change in probe reflectance, i.e., the so-called (photo) modulated reflectance. In this article, the authors demonstrate that the absolute junction depths of boxlike active dopant structures can be extracted in a very simple and straightforward way from the TP offset curves, which represent the behavior of the modulated reflectance as a function of the pump-probe beam spacing. Although the procedure is based on the insights into the physical behavior of the offset curves, no modeling is involved in the actual extraction process itself. The extracted junction depths are in good correlation with the corresponding junction depths as measured by means of SIMS. The technique has a subnanometer depth sensitivity for depths ranging from 10 to 35 nm with the present Therma-Probe\textregistered 630XP system. The extension of the proposed procedure to the general ultrashallow profiles is also explored and discusse

Оценка ультразвукового исследования в диагностике патологии эндометрия в постменопаузе

ЭНДОМЕТРИЙПАТОЛОГИЯПОСТМЕНОПАУЗАУЛЬТРАСОНОГРАФИ

High quality optical microring resonators in Si3N 4/SiO2

We have experimentally demonstrated high Q-factors strip waveguide resonators using the Si3N4/SiO2 material platform at the wavelength of 1.31μm. The analyzed filters demonstrate high quality factors reaching 133,000. The dependence on resonator radii and coupling gap is also discussed

Light coupling and distribution for Si3N4/SiO2 integrated multichannel single-mode sensing system

We present an efficient and highly alignment-tolerant light coupling and distribution system for a multichannel Si3 N4 /Si O 2 single-mode photonics sensing chip. The design of the input and output couplers and the distribution splitters is discussed. Examples of multichannel data obtained with the system are given

Ultrahigh Sensitivity Slot-Waveguide Biosensor on a Highly Integrated Chip for Simultaneous Diagnosis of Multiple

SABIO is a multidisciplinary project involving the emerging fields of micro-nanotechnology, photonics, fluidics and bio-chemistry, targeting a contribution to the development of intelligent diagnostic equipment through the demonstration of a compact polymer based and silicon-based CMOS-compatible micro-nano system. It integrates optical biosensors for label-free biomolecular recognition based on a novel photonic structure named slot-waveguide with immobilized bimolecular receptors on its surface. The slot-waveguides provide high optical intensity in a sub wavelength-size low refractive index region (slot-region) sandwiched between two high refractive index strips (rails) [1] leading to an enhanced interaction between the optical probe and biomolecular complexes (antibody-antigen). As such a biosensor is predicted to exhibit a surface concentration detection-limit lower than 1 pg/mm2, state-of-the-art in label free integrated optical biosensors, as well as the possibility of multiplexed assay, which, together with reduced reaction volumes, leads to the ability to perform rapid multi-analytesensing and comprehensive tests. This offers the further advantageous possibility of assaying several parameters simultaneously and consequently, statistical analysis of these results can potentially increase the reliability and reduce the measurement uncertainty of a diagnostic over single-parameter assays. In addition, the SABIO micro-nano system device applied to its novel protein-based diagnostic technology has the potential to be fast and easy to use, making routine screening or monitoring of diseases more cost-effective

Dye-Based Photonic Sensing Systems

[EN] We report on dye-based photonic sensing systems which are fabricated and packaged at wafer scale. For the first time luminescent organic nanocomposite thin-films deposited by plasma technology are integrated in photonic sensing systems as active sensing elements. The realized dye-based photonic sensors include an environmental NO2 sensor and a sunlight ultraviolet light (UV) A + B sensor. The luminescent signal from the nanocomposite thin-films responds to changes in the environment and is selectively filtered by a photonic structure consisting of a Fabry Perot cavity. The sensors are fabricated and packaged at wafer-scale, which makes the technology viable for volume manufacturing. Prototype photonic sensor systems have been tested in real-world scenarios.The authors thank the EU (Phodye Strep Project 033793 and ERC Starting Grant M&M's 277879), and the Spanish Ministry of Economy and Competitiveness (MAT-2010-21228) and Junta de Andalucia (P09-TEP-5283) for financial support.Aparicio, F.; Alcaire, M.; González-Elipe, A.; Barranco, A.; Holgado, M.; Casquel, R.; Sanza, F.... (2016). Dye-Based Photonic Sensing Systems. Sensors and Actuators B Chemical. 228:649-657. https://doi.org/10.1016/j.snb.2016.01.092S64965722

Development of Photonic Multi-Sensing Systems Based on Molecular Gates Biorecognition and Plasmonic Sensors: The PHOTONGATE Project

[EN] This paper presents the concept of a novel adaptable sensing solution currently being developed under the EU Commission-founded PHOTONGATE project. This concept will allow for the quantification of multiple analytes of the same or different nature (chemicals, metals, bacteria, etc.) in a single test with levels of sensitivity and selectivity at/or over those offered by current solutions. PHOTONGATE relies on two core technologies: a biochemical technology (molecular gates), which will confer the specificity and, therefore, the capability to be adaptable to the analyte of interest, and which, combined with porous substrates, will increase the sensitivity, and a photonic technology based on localized surface plasmonic resonance (LSPR) structures that serve as transducers for light interaction. Both technologies are in the micron range, facilitating the integration of multiple sensors within a small area (mm2). The concept will be developed for its application in health diagnosis and food safety sectors. It is thought of as an easy-to-use modular concept, which will consist of the sensing module, mainly of a microfluidics cartridge that will house the photonic sensor, and a platform for fluidic handling, optical interrogation, and signal processing. The platform will include a new optical concept, which is fully European Union Made, avoiding optical fibers and expensive optical components.The micro-nanofabrication capabilities required in the PHOTONGATE project- 101093042 are funded by the Pluri-Regional FEDER funding Plan 2014-2020 European Commission. This research project has received funding from the European Union¿s HORIZON-CL4-2022 research and innovation programme under grant agreement ID 101093042, PHOTONGATE projectNieves-Paniagua, Ó.; Ortiz De Zárate-Díaz, D.; Aznar, E.; Caballos-Gómez, MI.; Garrido-García, EM.; Martínez-Máñez, R.; Dortu, F.... (2023). Development of Photonic Multi-Sensing Systems Based on Molecular Gates Biorecognition and Plasmonic Sensors: The PHOTONGATE Project. Sensors. 23(20):1-13. https://doi.org/10.3390/s23208548113232

Low Frequency Modulated Optical Reflectance for the One-Dimensional Characterization of Ultra Shallow Junctions (Lage frequentie gemoduleerde optische reflectie voor de eendimensionale karakterisatie van ultra dunne juncties)

The scaling down of the metal oxide semiconductor field-effect transisto r (MOSFET) has fostered the development of new characterization techniqu es that must be able to probe features of ever smaller dimensions. One o f the key elements is the control of the properties of the ultra-shallow junctions (USJs) encountered in the source and drain extension regions of a MOSFE T. In this thesis, we have developed the theory of photo modulated optical reflectance (PMOR) for the characterization of USJs in silicon. We have assessed the theory by comparing it with experimental measurements on Bo ron doped chemical vapour deposition box-like profiles acquired with the Carrier Illumination (CI) metrology tool. CI allows to measure the prob e laser differential reflectance as a function of the power of the pump laser, also known as a power curve. The possibilities and lim itations of PMOR and especially of PMOR on CI have been deeply assessed. The work has been divided into two main tasks, namely the direct and the inverse problem. The direct problem, i.e. the simulation of a power cur ve from a known active doping profile, has been addressed through the de velopment of a finite element code for the simulation of a semiconductor under optical injection, of suitable approximations and of compact expr essions for speed optimization as needed for solving the inverse problem . The inverse problem, i.e. the reconstruction of the active doping profile from a given power curve, has been addressed using different methods of increasing complexi ties, including direct nonlinear optimization based on iterations on the direct problem. We have shown that CI was able to reconstruct box-like doping profiles w ith junction depths in the range 15-70 nm and with active doping concent rations of up to 1e20 /cm3. The accuracy of the technique is however str ongly affected by surface recombinations, which limits its practical use in the present implementation. We believe, however, that this limitatio n could be eliminated by using an ultrafast (sub-picosecond) pumping mec hanism, and we have proposed a reconstruction method that would be suite d for the reconstruction of arbitrary monotonic non-retrograde doping pr ofiles.1 Introduction 1.1 Motivation 1.2 Overview of USJ characterization 1.2.1 Secondary Ion Mass Spectroscopy (1D) 1.2.2 Spreading Resistance Probe (1D) 1.2.3 Micro Four Point Probe (0D/1D) 1.2.4 Scanning Spreading Resistance Microscopy (2D) 1.2.5 Electron holography (1D) 1.2.6 Junction Photo Voltage (0D) 1.2.7 Others 1.3 Optical probes for USJ characterization 1.3.1 Reflectometry and Ellipsometry 1.3.2 Photo Modulated Optical Reflectance 1.3.2.1 Generalities 1.3.2.2 CI State of the art and objective 1.4 Content 2 Experimental setup 2.1 Hardware setup 2.2 Measurement conditions 3 Optical modeling 3.1 Fourier Components (signals) 3.2 Reflectance 3.2.1 First order reflection 3.2.2 First order Maxwell wave equation 3.2.3 Transfert matrix formulation 3.2.4 Comparison 3.2.5 Lateral integration 3.3 Refractive index 3.3.1 The thermo-optic model (Jellison) 3.3.2 The electro-optic free carrier absorption model (Drude) 3.3.3 The electro-optic free carrier absorption model (Schumann) 3.3.4 The band-to-band absorption model (Smith) 3.4 Summary 4 Material modeling 4.1 Plasma 4.1.1 The drift-di�ffusion equations 4.1.2 The ambipolar diff�usion equation 4.1.3 The steady-periodic ambipolar diff�usion equations 4.1.4 Absorption and optical generation models 4.1.5 Bulk Recombination models 4.1.6 Surface Recombination models 4.1.6.1 Single trapping center 4.1.6.2 Pb center 4.1.7 Band Gap Narrowing models 4.1.8 Mobility and Diff�usivity models 4.2 Temperature 4.2.1 The heat equation 4.2.2 Heat generation model 4.2.3 Analytical solution 4.3 General solution of the Helmholtz equation 4.4 Finite element formulation 4.4.1 The Gummel map for the DD equations in Slotboom's variables 4.4.2 Resolution flow chart 5 Experiment vs. Theory 5.1 Surface charging 5.1.1 The capacitor model 5.1.2 Removal of the charging contribution 5.2 Uniform doping 5.2.1 Experimental data 5.2.2 General information about the simulation 5.2.3 MEDICI vs. FSEM 5.2.4 Analysis of the models 5.2.4.1 Bulk recombinations 5.2.4.2 Surface recombinations 5.2.4.3 Mobilities 5.2.4.4 Injection dependent BGN 5.2.4.5 High illumination power (GW/cm2) 5.2.4.6 Frequency eff�ects 5.3 Nonuniform doping 5.3.1 Experimental data 5.3.2 Preliminary analysis of the experimental data 5.3.2.1 Temperature dependence on the layer thickness 5.3.2.2 Impact of the lateral pro�le on the signal 5.3.3 General information about the simulations 5.3.4 MEDICI vs. FSEM solutions 5.3.5 General behavior of the solution 5.3.6 Analysis of the models 5.3.6.1 Injection dependent BGN 5.3.6.2 Surface Recombinations 5.3.6.3 Layer mobility 5.4 Conclusion 6 Approximated Solutions 6.1 Nonlinear currentless approximation 6.2 Flat Quasi Fermi Level (FQL) and Doping Layer Invariant Bulk Level (LIBL) approximations 6.2.1 Excess carrier concentration in the layer 6.2.2 Lateral decay length in the layer 6.2.3 Junction potential 6.2.4 Extension to arbitrary pro�files 6.2.5 LIBL approximation validity 6.2.6 FQL approximation validity 6.3 Conclusion 7 Inverse Problem 7.1 The inflection point method 7.2 The high vs low power derivative method 7.2.1 Error estimation by Monte-Carlo approach 7.3 Direct optimization 7.4 Backward deconvolution by staircase doping pro�file approximation 7.5 Conclusion 8 Conclusions A APPENDIX A.1 BX10 data A.1.1 BX10 output �file description A.1.2 Normalized R1 legacy calculation A.1.3 Laser power uncertainty A.2 Reference phase calculation A.3 n,k, K1; K2 A.4 Fundamental relations at interface A.5 First order surface di�fferential reflectance A.6 Maxwell wave equation A.6.1 Calculation of Aspnes semi-infi�nite integral A.6.2 Calculation of Aspnes reflectance from the phase derivative A.7 Reflectance functional derivative A.7.1 First order reflection A.7.2 First order Maxwell wave equation A.8 Use of maxima for interference calculation A.9 Nonlinear steady periodic approximation A.9.0.1 The harmonic recombination terms A.9.0.2 Jacobian A.10 The drift-diff�usion (DD) equations A.10.1 Expression of the currents in Slotboom's variables A.10.2 Expression of the currents in Slotboom's variables (relative to intrinsic level) A.10.3 Expression of the currents in drift-diffusion form A.10.4 Fermi-Dirac statistics A.10.5 Einstein relation in Fermi-Dirac statistics A.10.6 The Drift-Diff�usion equation in Slotboom variables A.10.7 The Gummel map for the drift-diff�usion equations A.10.8 Equilibrium A.11 Matrix expressions for the Helmoltz equation A.12 Interface traps A.13 Solution of 1d Poisson equation with surface charges A.14 Fitting of substrate excess carrier concentration and excess temperature as a function of pump power A.15 Silicon optical functions A.16 CVD samples descriptionstatus: publishe