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X-WR-CALNAME:Stanford Energy Student Lectures - Magnesium Crystal Defects a
 nd Battery State Estimation
X-WR-TIMEZONE:Pacific Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260817T015718Z
UID:tag:localist.com\,2008:EventInstance_53615565554593
DTSTART:20260811T220000Z
DTEND:20260811T230000Z
DESCRIPTION:Join us as grad student/postdoc speakers from various technical
  areas deliver short and accessible presentations about their innovative c
 lean energy research. Learn more about cutting-edge science and the most r
 ecent breakthroughs in areas such as renewables\, energy conversion materi
 als and devices\, catalysis\, and decarbonization from the researchers the
 mselves!\n\nRefreshments will be provided starting at 2:45pm. Share your f
 eedback on the speakers for a chance to win a Coupa gift card!\n\nSpeaker 
 Topics:\n\nEdem Honu - High-temperature defect and microstructural evoluti
 on in single-crystal Mg\n\nAbstract:\n\nWeight reduction in structural app
 lications is among the most direct routes to reducing fuel consumption and
  CO₂ emissions in transport. Magnesium (Mg)\, the lightest available str
 uctural metal (ρ =1.74 g/cm³)\, is 30% less than aluminium alloys with a
  high specific strength and is therefore a critical candidate of next-gene
 ration lightweight structures in automotive and aerospace applications. Re
 alizing this potential requires well-controlled thermal processing cycles 
 to restore workability and tailor microstructure\; yet the intrinsic\, the
 rmally-driven dislocation behaviour of Mg\, by grain-boundary effects or a
 pplied stress\, is poorly understood.\n\nHere\, we present the first in-si
 tu three-dimensional dark-field X-ray microscopy (DFXM) study of defect ev
 olution in a single-crystal Mg during a high-temperature annealing cycle u
 nder no applied stress\, resolving a bulk volume of 255 × 92 × 40 µm³ 
 at sub-micrometre resolution. A pre-existing {11-22} compression twin diss
 olves by ~202°C\, triggering thermally activated dislocation climb across
  multiple prismatic and pyramidal slip variants. Continued heating drives 
 near-complete static recovery by 318°C\, after which the crystal stabiliz
 es as a hierarchical sub-grain boundary network.\n\nStatistical analysis o
 f centre-of-mass rocking-curve maps confirms a significant reduction in la
 ttice orientation spread\, confirming the progressive release of stored el
 astic energy. These critical temperature windows inform optimized annealin
 g regimes directly applicable to the industrial processing of Mg component
 s\, with implications for reducing fuel consumption through wider deployme
 nt of lightweight Mg structures. The results simultaneously provide the ex
 perimental benchmark required to validate emerging thermal field dislocati
 on mechanics (T-FDM) and phase-field dislocation dynamics (PFDD) models in
  low-symmetry crystal structures.\n\nSpeaker bio:\n\nMy background is in a
 erospace engineering\, but currently\, I am a structural and materials ent
 husiast with strong research interests in metal powder-based AM technology
 \, hydrogen embrittlement\, and machine learning. I work in the Dresselhau
 s-Marais group at the Geballe Laboratory for Advanced Materials at Stanfor
 d University and SLAC National Accelerator Laboratory\, where I study hydr
 ogen-induced mesoscale defects using advanced characterization techniques 
 and imaging.\n\n \n\nJoseph Lucero - Seeing Inside Batteries from the Outs
 ide: State Estimation for Reliable Energy Storage\n\nAbstract:\n\nLithium-
 ion batteries are central to electrified transportation and grid energy st
 orage\, yet many internal states needed for effective operation cannot be 
 measured directly. Battery management systems must therefore infer quantit
 ies such as state of charge from external measurements\, typically current
  and voltage. This talk focuses on how physics-based models can support mo
 re trustworthy state estimation from these limited signals. In particular\
 , I will discuss why high-resolution battery models that accurately predic
 t voltage are not necessarily the best models for estimating internal stat
 es\, and how observability-aware modeling can help identify model structur
 es better suited for inference. Improved state estimation can clarify how 
 battery systems interpret operating conditions\, quantify uncertainty\, an
 d support more informed control decisions. Ultimately\, current and voltag
 e measurements contain valuable information about battery behavior\, but e
 xtracting that information requires models designed not only to simulate b
 attery dynamics\, but also to infer the hidden states that inform battery 
 operation.\n\nSpeaker bio:\n\nJoseph N. E. Lucero is a final-year Ph.D. ca
 ndidate in Chemistry at Stanford University\, where he develops electroche
 mical battery models and estimation algorithms for next-generation battery
  management systems. His research spans lithium-ion battery modeling acros
 s multiple scales\, from electrochemical model development and state estim
 ation to vehicle energy analysis and grid-scale energy optimization. He ha
 s held research internships at Google and Oak Ridge National Laboratory\, 
 and his publications span battery systems\, stochastic thermodynamics\, bi
 ophysics\, and medical physics. Joseph earned his M.Sc. in Physics and B.S
 c. with Distinction in Biological Physics from Simon Fraser University.
GEO:37.42816;-122.175935
LOCATION:Y2E2 Building\, 299
SUMMARY:Stanford Energy Student Lectures - Magnesium Crystal Defects and Ba
 ttery State Estimation
URL;VALUE=URI:https://events.stanford.edu/event/stanford-energy-student-lec
 tures-magnesium-crystal-defects-and-battery-state-estimation
CATEGORIES:Lecture/Presentation/Talk
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