- Troubleshot the display product delivery technical blocking issue’s root cause with quantitative failure analysis using modeling and simulation with experimental measurement on the vendor’s display module sample. Closely working with vendors and internal cross-function team for product delivery.

Digital system - Modeling & simulation: OLED display Pixel FoS (Front of the Screen) issue modeling & simulation and propose solutions.

• Built display OLED pixel model with input of EE/TFT/OLED parameters. Built temperature luminescence sensitivity and temperature color sensitivity FoS issue model.
• Achieved high correlation between the model and experimental results and provided FoS issue mitigation plan.
• Submitted an innovation pattern disclosure for novel FoS mitigation methods.

Physcial system - Experiment metrology and failure analysis for display module low-light transient measurement for FoS issue study.

• Introduced a novel display FoS metrology setup using a colorimeter, luminance meter, and single photon counting module for single-pixel optical transient measurement, and provided technical manuals for the new metrology setup.
• Tuned the display driving setting with FPGA tuning, and programmable voltage source tuning, and used oscilloscope for timing verification.
• Delivered robust/complex optical, software control, and electronics test setup in the laboratory.

- Designed and prototyped an electro-optical system, named “Quantum System on Chip” (QSoC), for scalable quantum computing architecture that hybrid integrated over ten thousand advanced qubits (cleanroom fabricated diamond color center as single photon source) on the CMOS backplane with free-space optical control and readout. Designed the QSoC backplane and got it fabricated with foundry tape out followed by in-house cleanroom post-processing and packaging. Built the automated testing setup and algorithm with programmable electrical-optical hardware for QSoC inhomogenous registration and uniformity compensation and built a digital twin model that connects the physical and the digital worlds for root cause identification and optimization implementation. Proposed a protocol of “entanglement multiplexing” for large-scale quantum computing resource state generation fully utilizing the capability of the QSoC. Implemented a "Transformer-on-QuPairs" architecture that uses machine learning technology to outperform the rule-based approach for the “entanglement multiplexing” operation for the dynamic inhomogeneous quantum resource scheduling.

EE - Circuit design: System-on-Chip with digital, analog, radio-frequency circuit

• CMOS Chip design: CMOS backend chip for panel control (180nm High Voltage) designed with cadence including a digital series interface for channel selection, high voltage (HV) maintainer. RF switch for the transmission line.
• Digital circuit design: Serial shift register, data selector, communication with Serial Peripheral Interface (SPI) interface.
• Analog circuit design: High Voltage sample and hold in an array with an external high voltage source.
• Radio Frequency (RF) circuit design: RF switch, RF Driver with external arbitrary waveform generator (AWG) signal.

EE - Optical design: ray tracing and wave optics simulation

• Photonic integrated circuit (PIC) design: visible PIC platform including waveguide, taper, edge coupler, ring resonator, antenna, and grating coupler, designed with Lumerical Interconnect.
• Nanoscale optics design: Lumerical FDTD simulation of the nanophotonics antenna emission far-field optimization.
• Microscale optics design: Zemax Opticstudio simulation of the free space optics of lens system optimization for fiber coupling efficiency including lens, polarization beam splitter, beam splitter, quarter waveplate, half waveplate, etc.
• Optical hardware model 3D rendering visualization: 3D Optix/Blender ray tracing rendering.

EE - Customized metrology setup design: customized automated electrical-optical metrology for failure analysis

• Auto EE-Optics metrology: programmed the setup with code (Matlab/Python/C/C++) for auto-acquiring data, synchronized source control signal and detector measured signal from various setups.
• Optical measurement: Camera widefield high-throughput characterization, MEMS mirror scan, microscope video measurement, spectrometer, and spatial light modulator for programmable routing.
• Digital/Analog signal measurement: used field-programmable gate array (FPGA) to generate the test vector for chip testing. Tuned the quantum emitter wavelength with electronics voltage sweep in 4K cryogenic temperature.
• High-speed RF measurement: used a 10 GHz bandwidth arbitrary waveform generator (AWG) to drive an Electro-Optics Modulator (EOM) for a 1 ns pulsing for visible red laser optical control. Verified with a 10 GHz bandwidth oscilloscope.

EE - Customized experimental manufacturing: customized hardware fabrication

• Heterogenous integration: Transfer print with Polydimethylsiloxane (PDMS), pick-and-place (with tungsten probe). Heterogenous integration structure design and material selection.
• Optics/Chips packaging integration: Fiber array alignment and gluing, 3D printing/machine fab of mechanical components. Printed circuit board (PCB) design using Altium and using CAD to design custom cavity PCB.
• Foundry tape out design: CMOS chip tape out in TSMC, Photonics integrated circuit tape out in Sandia National Lab, PCB tape out with vendor in China, wire bonding, and RF packaging. Layout design and visualization with Gdspy, KLayout, Solidworks, AutoCAD, Latex, and Blender.
• Nanofabrication: Thin-film physical/chemical deposition; lithography (photo and ebeam) and etching(wet and dry), characterization (spectrum, optical/electron microscopy, etc), implantation and annealing etc.

CS - Architecture and Modeling: understand the whole system from high-level architecture and device operation detail for system optimization

• System architecture protocol modeling: Proposed entanglement multiplexing architecture for large-scale quantum computing resource state generation, built the digital twin modeling for the whole system.
• Novel hardware architecture modeling: Built the model for QSoC function (math, physics) and control (electrical, optical, electrical-optical interface). The architecture with QSoC extended the two-dimensional planar computing chip with a third dimension (free-space optics), which introduced the advanced functionality benefit leveraging the modern semiconductor mass production capability.
• Hardware compensation function modeling: Built the behavior model for inhomogenous compensation of the qubit tuning. Designed the compensation pipeline from high-throughput data collection (auto measurement for inhomogenous registration), and a software look-up table for voltage-induced qubit frequency compensation. Built the device modeling with COMSOL multi-physics for modeling the physical tuning behavior for the compensation.
• Optoelectronics sensor modeling: Camera/photodetector pixel modeling for signal-to-noise prediction in application-specific scenes including scientific complementary metal-oxide-semiconductor (sCMOS) camera, electron-multiplying charge-coupled devices (EMCCD), and avalanche photodiode (APD). Based on the possible variation during the semiconductor fabrication process, estimate the performance variation of the optical device.

CS - Simulation: computation speed up with cloud computing resources and algorithm optimization

• Optimization with parallel and distributed computing: Used MPI communication for the distributed computation of various nodes in the cluster. Used OpenMP to speed up the simulation with multi-thread parallel computing within a server node. Generated the whole simulation file with script and wrote a custom gradient descent algorithm to efficiently optimize the geometry parameters.
• Bayesian optimization with physical model: Using a physical model to emulate the numerical simulation result from commercial software. Based on the physical model, to calculate the highest probability of the next group of parameters for the commercial software. Using the physical model’s pre-knowledge for next step prediction, optimization can converge must faster than the random trial.
• Coding language: Matlab, Python, C, C++, CUDA.
• Operation system experience: Linux, MacOS, Windows.

AI - Statistical quantitative analysis: extract the value from the available multimodal dataset

• Time series data analysis: modeled quantum state transfer with Bayesian probabilistic model.
• Statistical analysis: applied linear regression of the correlated qubit signal with the control signal. Analyzed the qubit feature signal distribution with hypothesis testing and found a good qubit candidate.
• Machine learning: classified the high-quality qubit with supervised learning.
• Camera video data signal processing: recognized the qubit signal pattern with computer vision algorithm.

AI - Machine Learning Engineering: strategy optimization with AI

• Formulated the scientific problem and simulated it within a digitized environment, allowing the exploration and development of agent-based optimization strategies.
• Proposed a "Transformer-on-QuPairs" architecture for dynamic quantum inhomogenous resource scheduling tasks.
• Implemented various machine learning technologies like reinforcement learning, fully connected network, and transformer architecture for various machine learning technologies comparisons for the same problem.
• Outperformed the quantum system performance over 3x using the machine learning-based agents compared with the rule-based agent.

- Designed a two-dimensional (2D) tunnel heterojunction with an H-shaped energy barrier, which serves as ultrathin memory selectors with good symmetry, non-linearity, and high endurance. Explored the design space for H-shaped memory using physical modeling and first-principle density functional theory (DFT) quantum transport simulations. Evaluated the H-shaped selector in the one-selector-one-resistor (1S1R) configuration and provided design guidelines for the heterojunction (metal/nL hBN/nL 2D material/nL hBN/metal) design to match the 1R characteristics.

Physical system to digital system: explored the design space with digitized modeling instead of physical experiment to speed up design optimization

• Atom scale (Å ~ nm): DFT calculation in VASP (Vienna Ab initio Simulation Package) using supercomputer cluster.
• Atom scale (Å ~ nm): Quantum transport calculation (Current-voltage relation in atom scale device) in QuantumATK with non-equilibrium green's functions formalism (NEGF) using supercomputer cluster.

- Proposed the physical model to bridge the gap between unexpected observed physical phenomena with theoretical understanding.

Physical system to digital system: root-cause discovery for semiconductor device experiment by Modeling & simulation

• Micro-scale modeling (μm ~ mm): Semiconductor device model in Matlab and Mathematica
• Nano-scale modeling (nm ~ μm): Device electric field and strain simulation in COMSOL Multiphysics
• Atomic-scale modeling (Å ~ nm): Atomic-scale semiconductor material investigation using VASP and Material Studio for first-principal calculation using a supercomputer cluster
• Electron band diagram and projected density of states calculation in different atomic structure supercells
• Defect optical spectrum prediction
• Electron and hole effective mass changed in the conduction band and valance band
• Electron density 3D/2D diagram in the atomic structure with atomic defect model
• Lowest energy atomic structure configurations optimization for material heterojunction or defect
• Spin-orbit coupling calculation for MAE
• Pattern written: Wrote a pattern with a novel device structure using graphene nanoribbon for terahertz emission.

Reference:

1. Linsen Li, et al. "Heterogeneous integration of spin-photon interfaces with a CMOS platform." Nature. (2024)
2. Linsen Li, et al. "Dynamic inhomogeneous quantum resource scheduling with reinforcement learning." Arxiv:2405.16380. (2024)
3. Linsen Li, et al. "Field-based design of a resonant dielectric antenna for coherent spin-photon interfaces." Optics Express, 29, 16469-16476. (2021)
4. Linsen Li, et al. “First principles study of memory selectors using heterojunctions of 2D layered materials.” International Electron Devices Meeting (IEDM), 24.3.1-24.3.4. (2018)
5. Linsen Li, et al. "Influence of point defects on optical properties of GaN-based materials by first principle study." Computational Materials Science 129: 49-54. (2017)
6. Linsen Li, Zhibiao Hao. "Graphene terahertz emitter and its manufacturing method." Patent Application Number CN201510767570. Filed on Nov. 11, 2015. Granted on Nov. 26, 2018, Assignee: Tsinghua University.