Hands-on Introduction to Mat3ra.com

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Summary

Detailed Content

Presenter(s)

10:00

Workshop introduction

Introduction of the workshop schedule, goals, agenda.

KM, JD

10:10

Platform introduction

Mat3ra.com capabilities: (1) company background, its vision, mission, and the present state; (2) the platform capabilities, and case studies overview.

TB

10:45

Platform UI overview

Hands-on session exploring the main aspects of the platform UI, including the following:

Preliminary

• Registration (each participant will receive an account)

• Joining the Webinar/Seminar collaborative account

UI overview

• accounts and teams

• supported entities: jobs, materials, workflows

• data convention

  • files / data on disk

  • structured data in the database and the data standards

  • search - basic, advanced, pro

  • data sharing: entity bank and access levels

• other:

  • supported modeling engines (applications)

  • access through command-line terminal

TB

11:30

Materials

basic actions

• upload from files

• import from online database(s)

• import from bank

• import from standata

data infrastructure

• example JSON representation:

  • ontologies, categorization, schemas

• identifying uniqueness

• metadata

• search / advanced search / pro search

• bank collection / data visibility

atomic design capabilities

• create/delete atoms

• edit crystal lattice and basis parameters

• supercells, combinatorial sets, surfaces

• advanced options - mat3ra-made notebooks:

  • The approach to the Python-based open-source stack

  • api-examples

  • mat3ra-made

Properties

categorization:

• descriptive

• characteristic

• precision

data infrastructure:

• association with materials, workflows, jobs

• refinement:

  • raw, refined, best

other property categories:

• metaProperties

• protoProperties (workflow datasets, pseudopotentials

 TB

12:00 

Lunch + Focus discussion(s) in the semi-private space.

13:00

Welcome back and the Remaining Workshop Overview (10 mins)

JD, KM

13:10-14:00

Workflows

data infrastructure

• example JSON representation

• bank collection and sharing

• default workflows:

  • default supported applications

  • default subworkflows and their LEGO-like representation

• identifying uniqueness

workflow datasets

• Density Functional Theory pseudopotentials

• pseudopotential filters

basic actions

• create / update / clone / search

• copy from shared bank / use inside a job

• add/remove (sub)workflow units

• unit templates and rendering

  • UI render

  • runtime render

convergence and relaxation examples

14:00 ～ 15:00

Jobs.

data infrastructure

• organizing jobs inside a project

• example JSON representation

• compute parameters

basic actions

• create / create a jobs set / clone / search

• add / remove materials

• select workflow / adjust during job creation

• adjust workflow dataset (pseudopotentials)

• set compute parameters

compute infrastructure overview

• clusters / cloud providers

• benchmarks

• security policies

• monitoring

• job results / materials properties

command-line jobs:

• examples folder

• example CLI job calculation from a terminal

jobs:

1. Upload a set of materials

2. Import additional set from online database

3. Copy workflow(s) from the shared workflows bank

15:00 ～ 16:00

Hands-on real-world example calculations

Specific advanced examples:

• Using DeepMD with ab-initio data from QE

• Using LAMMPS with M3GNET

  By KM

16:00 ~ 17:00

Using REST-API

1. RESTful API basics:

   1. https://docs.mat3ra.com/rest-api/overview/

   2. https://api-explorer.mat3ra.com/#!/API/post_login

   3. https://github.com/Exabyte-io/api-client

2. Accessing API-Examples:

   1. https://github.com/Exabyte-io/api-examples

   2. via the web platform

3. Authentication:

   1. Via the web platform in JupyterLite session

   2. Via standalone Python environment

4. Querying the data:

   1. Via the web platform or in a JupyterLite session

   2. Via standalone Python/JupyterLab environment

5. Creating the Entities:

   1. Materials

   2. Workflow(s)

   3. Job(s)

6. Additional Items:

   1. High-throughput calculations

   2. Creating ML models

Other items:

• https://docs.mat3ra.com/tutorials/other/jupyter/)

TB

17:00 ～ 17:30

Q&A

17:30 ~ 18:30

Happy Hour