From 7d851eb8c73291892508083a7f2cbf002878882a Mon Sep 17 00:00:00 2001 From: Cooper Date: Sat, 4 Jan 2025 09:16:40 -0700 Subject: [PATCH] Updated BayesOpt section of Research page --- biography.html | 7 +++++++ images/EC_white.png | Bin 0 -> 77390 bytes images/PF6_white.png | Bin 0 -> 2678 bytes images/bayesopt.png | Bin 0 -> 162790 bytes images/bayesoptsmalltrans.png | Bin 0 -> 189321 bytes images/mean-acqf-EC-PF6.png | Bin 0 -> 73027 bytes images/molsets_diagram.png | Bin 0 -> 246518 bytes index.html | 26 +++++++++++--------------- research.html | 20 +++++++++++++++++--- source/biography.html | 7 +++++++ source/index.html | 26 +++++++++++--------------- source/research.html | 20 +++++++++++++++++--- 12 files changed, 70 insertions(+), 36 deletions(-) create mode 100644 images/EC_white.png create mode 100644 images/PF6_white.png create mode 100644 images/bayesopt.png create mode 100644 images/bayesoptsmalltrans.png create mode 100644 images/mean-acqf-EC-PF6.png create mode 100644 images/molsets_diagram.png diff --git a/biography.html b/biography.html index 134a519..ecc75a6 100644 --- a/biography.html +++ b/biography.html @@ -62,4 +62,11 @@ }); }); + +
+

Biography

+

This is my biography

+
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    +
    Main Image @@ -56,7 +56,7 @@
    -
    +
    Main Image @@ -64,39 +64,35 @@
    -
    +
    -
    +

    Cooper Tezak

    -
    -
    +
    -
    -

    PhD Student, CU Boulder

    +

    PhD Candidate, CU Boulder

    Atomic Broker

    -
    -
    +
    +
    Battery Electrolyte Composition Optimization
    I have recently begun working with Chunmei Ban - on optimizing experimental electrolyte composition for Na-ion batteries. I lead the effort to develop a Bayesian optimization framework - that uses a gaussian process to estimate the charge capacity at a given cycle based on the mass weights of electrolyte components. + on optimizing experimental electrolyte composition for Na-ion batteries. I have succesfully implemented + information theoretic and simple expected improvement acquisiton functions on top of a gaussian process + surrogate model to efficiently explore compositions experimentally. However, the design space for electrolyte compositions + is huge and experiments are expensive. I am currently working on incorporating molecular features into the model using + graph neural networks to featurize molecular structures and attention mechanisms to create mixture level representations + from the constituent molecular features. + [7] + The architecture of the model is summarized as

    + Molsets Architecture

    @@ -139,6 +146,13 @@ to have less occupied d-orbitals that were capable of strongly reducing the \( N_2 \) triple bond. However, all materials were inevitably limited by the desorption of \( NH_3* \) from the surface.

    + Bayesian Optimization +

    + Bayesian Optimization model for battery electrolyte compositions. X and Y axes are fractions of chemicals + EC and NaPF6. The left panel shows the mean of the model and the right shows the + acquisiton function value, which is the + log expected improvement + .

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