Q&A Information Session

Dane MorganUniversity of Wisconsin, Madison

ddmorgan@wisc.edu, W: 608-265-5879, C: 608-234-2906UW Madison

September 6, 2016 1

To Join: Send me email at ddmorgan@wisc.edu with your name, email, major (intended if not set), and any relevant facts/interests (e.g., have project already, strong machine learning skills, know python, want only solar energy, …)

What is the Informatics Skunkworks?

The “Informatics Skunkworks” is a group dedicated to realizing the potential of

informatics for science and engineering.

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Vision: Transform science and engineering with informatics

Why Form the Informations Skunkworks?

Incredible opportunity for young creative researchers

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Massive Data New FieldsTransformative Tools

How the Informatics Skunkworks Works – Big Picture

• You talk to me if you are interested.

• We find you a project with a mentor (me, another faculty, industry representative) – you can bring a project.

• You work on the project for either credit (most common) or pay (if available) and get cool results.

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How the Informatics Skunkworks Works – Details

• Typical commitment is ~10h/wk during the year (3 credits), possibly full time over summer if adequate funds and interest.

• Participants should plan to spend 2-3h/wk in lab at designated “gathering” times.

• Participants should plan to meet and present progress to a mentor at least every 2 weeks.

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Why Join the Skunkworks vs. Just Work Separately?

• Community building: You can find a like-minded community of colleagues from which to learn and form a network for a lifetime.

• Technical resources: Have people to ask questions and have access to our computational (codes and computers) resources.

• Presentation opportunities: Utilize frequent opportunities to present work on web page, as posters and/or talks, potentially publish papers.

• Learn teamwork: We tend to work in teams to help build critical teamwork skills for future employment.

• Snack food: Our lab is well stocked

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Some Stuff the Skunkworks Has/Does

• Large lab with lot’s of snacks (thanks to Profs Rebecca Willet and Robert Nowak) – EH 3546

• Excellent web page to highlight our accomplishments (skunkworks.wisc.edu)– Always looking for people to help develop

this• Experienced members who know

powerful informatics tools (python, matlab, SciKitLearn, tensorflow, etc.)

• Neat data sets you can explore (mostly in materials)

• Many opportunities for posters, talks, papers, etc.

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An Example of Skunkworks Results

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Predicting Impurity Diffusion in FCC Alloys

Wu, et al, Scientific Data ‘16

Calculated activation energies with ab initio methods

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Example: Predicting Impurity Diffusion in FCC Alloys

• 15 FCC hosts x 100 impurities = 1500 systems, ~15m core-hours (~$500k to produce, ~2 years).

• We have computed values for ~10%

• How can we quickly (and cheaply) get to ~100% coverage?

Materials Informatics Approach – Regression and Prediction

• Assume Activation energy = F(elemental properties)• Elemental properties = melting temperature, bulk modulus,

electronegativity, …• F is determined using a one of many possible methods: linear

regression, neural network, decision tree, kernel ridge regression, …

• Fit F with calculated data, test it with cross-validation, then predict new data.

Train F(properties)

Y. Zeng and K. Bai, Journal of Alloys and Compounds 624, p. 201-209 (2015).11

Model Predictive Ability

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DataX

Model Predictive Ability

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DataX

Model Predictive Ability

• Leave one out cross validation

• Predictive RMS = 0.14 eV – predicts diffusion of new impurity within <10x at 1000K. Could save ~$500k!

• Soon to be an online tool and journal paper

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DataX

Conclusions

Informatics is a transformative technology for nearly everything – come join us!

Some experienced skunkworkers to talk to

15Henry Wu Aren Lorenson

Some Data Sets We Can Use

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DataX