Alex Bien

Work Experience

• Research Assistant, Laboratory for Physical Sciences • LPS Qubit Collaboratory (November 2020 - July 2022)

  · Leveraged Python, LabVIEW, and Origin Pro to analyze the charge-to-mass ratio of Au, SiC, and C (graphene) nanoparticles levitated in a quadrupole ion trap and to monitor sample density metrics
  
  · Used COMSOL Multiphysics to model AC and electrostatic potentials of the experiment, and to trace nanoparticle paths in launch simulations
  
  · Used SOLIDWORKS to create engineering drawings of the experimental setup to be fabricated in the machine shop
  
  · Gained hands-on experience with high-vacuum systems, gas plumbing, electrical circuitry, and overall experimental design
  
  Bruce Kane - Principal Investigator
  Joyce Coppock - Postdoctoral Researcher

  Location

  College Park, MD, USA

• SULI Researcher, SLAC National Accelerator Laboratory • Stanford University (June 2021 - August 2021)

  Energy Spread Optimization for the LCLS-II Photoinjector
  
  At SLAC, energy is imparted on a beam of electrons by pushing them to near light speeds, and the accrued kinetic energy is released via synchrotron radiation in the form of high intensity x-rays upon rapid deceleration of said electrons. There are several elements to this high intensity beam generation that we must consider. Given that several experimental hutches are located at the end of the 2.5 mile long beam, it is imperative that the beam shape holds its integrity from one end of the vacuum chamber to the other so that coherence is optimized, and the highest quality beam is achieved. Theoretically we would be able to focus the beam to an infinitesimally small spot, but this is inhibited by several factors. One factor is the energy spread of the electron beam; that is the distribution of energy in one of its constituent electron bunches. In my research, I sweep across RF field phase shift angles in the eighth cavity of the first cryomodule, produce phase space plots for each shift, and fit first, second, and third degree polynomials to analyze uniformity in the energy spread. This is done by first manufacturing a distribution in distgen, running simulations through OPAL at each different phase, and then postprocessing the data in Python.
  
  Technical talk given on 8/4/2021 to fellow SULI Researchers

  Location

  Menlo Park, CA, USA

• PREP Researcher, National Institute of Standards and Technology (NIST) (March 2019 - August 2020)

  Finite Element Analysis (FEA) and X-ray Diffraction Analysis of Steel Microstructures
  
  The goal of this project is to test if finite element analysis (FEA) performed on a steel microstructure can explain non-linear x-ray diffraction behavior.
  
  For deformations more complicated than uniaxial tension, where the stress is simply load divided by area, measuring the stresses in the material becomes a challenge. One technique is to use x-ray diffraction to measure the changes in the inter-atomic distances, and correlate this to a stress in the solid. For most materials this is fairly straightforward, and a linear equation can be found relating the inter-atomic distance and the angle (commonly called ψ) between the diffraction vector and applied stress. When ferritic steels are deformed, particularly in biaxial tension, the correlation between inter-atomic distances and ψ becomes non-linear (see Figure 1 of Barral et al, Metallurgical Transactions A (1987) p 1229 – 1237) and much harder to accurately fit. This behavior is well known and the dominant mechanisms, namely the elastic anisotropy and crystallographic texture, are also known. What is not known is how these factors cause the non-linear behavior.
  
  Recent experiments have led us to believe that the spatial arrangement of the grains in the material, and the specific crystal orientations that are formed during biaxial tension are the significant factors. We have performed these calculations on single crystals and are now interested in using FEA to model the behavior of a collection of grains and analyze what stresses result from their interaction.
  
  We gained insight into the non-linear x-ray diffraction behavior and developed a new method for the calculation of diffraction elastic constants, finding that the non-linear behavior is due to the orientations of two main grain clusters under biaxial tension.
  
  Technical talk given at NIST on 8/19/2019 to the Mechanical Performance Group at the Materials Measurements Lab

  Location

  Gaithersburg, MD, USA

• SPD Researcher, University of Maryland - First Year Innovation and Research Experience (FIRE) (August 2019 - December 2019)

  Randomly Killed Layers in HGCAL
  
  Simulated performance loss in the Central Muon Solenoid's High Granularity Calorimeter (CMS HGCAL) located at the Large Hadron Collider (LHC) due to damaged detector cells using data from UMD's Tier-3 computing cluster. This research expands upon the earlier work of Dr. Sarah Eno et al., by using newer HGCAL code in GEANT4 simulations, as well as measuring percentage losses in photon total energy.
  
  Poster presentation given 4/22/2019 at UMD's Undergraduate Research Day
  
  Müge Karagöz - Supervising Professor

  Location

  College Park, MD, USA