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Titze, Michael

Publications and source records attributed to Titze, Michael.

46 records · Page 3

Single Photon Emitters Coupled to Photonic Wire bonds

This project will test the coupling of light emitted from silicon vacancy and nitrogen vacancy defects in diamond into additively manufactured photonic wire bonds toward integration into an "on-chip quantum photonics platform". These defects offer a room-temperature solid state solution for quantum information technologies but suffer from issues such as low activation rate and variable local environments. Photonic wire bonding will allow entanglement of pre-selected solid-state defects alleviating some of these issues and enable simplified integration with other photonic devices. These developments could prove to be key technologies to realize quantum secured networks for national security applications.

42 ENGINEERING↗

Quantum Sensed Electron Spin Resonance Discovery Platform (Final Report)

The properties of materials can change dramatically at the nanoscale new and useful properties can emerge. An example is found in the paramagnetism in iron oxide magnetic nanoparticles. Using magnetically sensitive nitrogen-vacancy centers in diamond, we developed a platform to study electron spin resonance of nanoscale materials. To implement the platform, diamond substrates were prepared with nitrogen vacancy centers near the surface. Nanoparticles were placed on the surface using a drop casting technique. Using optical and microwave pulsing techniques, we demonstrated T1 relaxometry and double electron-electron resonance techniques for measuring the local electron spin resonance. The diamond NV platform developed in this project provides a combination of good magnetic field sensitivity and high spatial resolution and will be used for future investigations of nanomaterials and quantum materials.

36 MATERIALS SCIENCE↗

Evaluation of the accuracy of stopping and range of ions in matter simulations through secondary ion mass spectrometry and Rutherford backscattering spectrometry for low energy heavy ion implantation

The freely available “Stopping and Range of Ions in Matter” (SRIM) code is used for evaluating ion beam ranges and depth profiles. We present secondary ion mass spectrometry and Rutherford backscattering experimental results of Si samples implanted with low energy Sb ions to evaluate the accuracy of SRIM simulations. We show that the SRIM simulation systematically overestimates the range by 2–6 nm and this overestimation increases for larger ion implantation energy. For the lowest energy implantation investigated, here we find up to a 25% error between the SRIM simulation and the measured range. Finally, the ion straggle shows excellent agreement between simulation and experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lithium source for focused ion beam implantation and analysis

In this work, we present a new Li source for focused ion beam applications. Based on an AuSi eutectic alloy, Li is added as an impurity to minimize effects from degradation when exposed to air. We show the source is stable over the course of an hour and spot sizes ≲10 nm can be achieved. The Li beam can achieve hundreds of nanometer ranges in semiconductors with minimal damage being generated along the path length. The source performance is evaluated through a high-resolution ion beam induced charge collection experiment on an Si-based detector. Further application of the source for ion beam analysis is numerically explored; the example investigated is based on probing a semiconductor heterostructure through a Rutherford backscattering experiment, where the Li beam can reveal information that is inaccessible with either low energy or high energy He projectiles used as probes.

36 MATERIALS SCIENCE↗

Machine learning enabled lineshape analysis in optical two-dimensional coherent spectroscopy

Optical two-dimensional (2D) coherent spectroscopy excels in studying coupling and dynamics in complex systems. The dynamical information can be learned from lineshape analysis to extract the corresponding linewidth. However, it is usually challenging to fit a 2D spectrum, especially when the homogeneous and inhomogeneous linewidths are comparable. We implemented a machine learning algorithm to analyze 2D spectra to retrieve homogeneous and inhomogeneous linewidths. The algorithm was trained using simulated 2D spectra with known linewidth values. The trained algorithm can analyze both simulated (not used in training) and experimental spectra to extract the homogeneous and inhomogeneous linewidths. Finally, this approach can be potentially applied to 2D spectra with more sophisticated spectral features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗