How Constructor Research supports advanced materials scientists
29 November, 2024
AI has been a trusted tool in research for years. In the era of big data, and particularly through LLMs, it offers a powerful solution across all research stages.
Constructor Research was designed to address significant computational challenges, especially for larger systems, providing scientists with next-gen tools for faster, more efficient research, and scalable results.
One such example is ‘Hamiltonian Magic’, a project led by Prof Dr Stephan Roche and his team at ICN2, which presents new approaches in how researchers deal with materials science challenges using AI and machine learning.
About ICN2:
The Catalan Institute of Nanosciences and Nanotechnology (ICN2) is a reference center for national and international-level research in nanoscience and nanotechnology. Professor Roche leads the Theoretical and Computational Nanoscience group.
Project objectives
Manual tasks automation
The ICN2 team needed a custom solution to automate manual tasks and simplify a complex workflow.
Constructor Research not only accelerated their research project by 5x but also enabled collaboration and experiment reproducibility for further project development.
Workflow and testing improvement
Prof Roche’s team used Constructor Research as the primary computational environment, leveraging its GPU resources and integrated Visual Studio interface to improve the workflow and testing.
Challenges
Tool selection and integration
Computational restrictions
Experiment testing
Outcomes
The ICN2 team successfully tested and reproduced their experiments all in one place, without 3rd party tools. Tasks that usually required extensive computational time were completed in days.
1 solution
3 people
5x accelerated overall research process
Using Constructor Research significantly accelerated development for Prof Roche and his team with:
High-performance computing
Seamless remote access
Efficiency for time-consuming tasks
Here’s how the ICN2 team uses Constructor
Conclusion
With Constructor Research, Prof Roche’s team from ICN2 successfully developed a scalable machine learning model to extract Hamiltonians from atomic structures, much faster and easier.
To hear more about how AI can be used to accelerate scientific research, watch the recording of our webinar “From Manual to Machine: AI impact in modern research”, where Prof Dr Stephan Roche and his team presented their experience and opinion on how AI can support the design of innovative advanced materials, with a live demo in Constructor.
