Investments in the space sector, the Anushandhan National Research Foundation Bill and much more
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(Podcast) Computation and AI: Next-Gen Materials Discovery
Deep science funding updates
- Astrogate Labs, a manufacturer of optical communication systems for space applications, has raised an undisclosed amount of funding as part of a strategic investment from Satsure.
- Satsure, a company offering satellite earth observation data and analytics, has raised $15 million in its series A funding round led by Baring Private Equity Partners and Promus Ventures along with Omdiyar Network India and xto10X. Existing investors such as Force Ventures, Luckbox Ventures and IndigoEdge Advisors also participated in the round.
Deep Science Ecosystem Updates
- The Anushandhan National Research Foundation bill was passed by the parliament which aims to provide state universities equitable access to research funds from philanthropists, industries and private donors. A total of 50,000 crores have been allocated to this program over 5 years (2023-28). Around 80% of this is expected to come from non-government sources such as industry and philanthropists.
- Voxelgrids Innovations has developed the first indigenous MRI scanner in the country and it will be launched at the Sathya Sai Institute of Higher Medical Sciences, Bengaluru in October.
- The Chandrayaan-3 mission successfully made a soft landing near the south pole of the moon using the Vikram lander.
- BITS Pilani has launched a new PhD program called PhD-DRIVE to promote researchers to pursue entrepreneurship and develop deep tech products.
- Rajasthan-based Sahasra Semiconductor will start the commercial production of first made-in-India memory chips from September or early October. This will make them the first company in India to do so.
- MeitY has transferred cost-effective lithium-ion battery recycling technology to nine recycling companies and nine more received letters of intent at Niti Aayog. The technology was developed in partnership with the Government of Telengana and Greenko Energies
News from the research community
- A group of researchers from Banaras Hindu University have synthesised cathode materials, capable of providing high capacity and prolonged battery life, enabling longer-lasting and more powerful sodium ion batteries.
- Researchers at the Extended Crystalline Organic Materials (ECOM) Laboratory at S. N. Bose National Centre for Basic Sciences, Kolkata have synthesized a crystalline, chemically stable material, belonging to the class of crystalline porous organic polymers with permanent porosity and highly ordered structures. This could enhance the energy density of the cathode for Li-S batteries and make them more efficient.
Deep Science Thoughts
AI-powered materials discovery: A new age
The rapid rise of artificial intelligence (AI) has promised to upend, at a fundamental level, the way we go about our tasks. GPT, to name a prominent example, has changed the way some of us go about our day-to-day activities. The impact of advanced computation and AI is felt across sectors, though, and materials science is one such sector where we see it having a paradigm-shifting impact.
Scientific method moving to a computational paradigm
Materials science, just like other fields of science, has rapidly entered the third and fourth paradigms where it’s incorporated advanced computation and big data approaches respectively. This development, over the past three decades, has allayed fears of a stagnation in materials science. The biggest impact has been in the process of materials discovery; a process that used to be guided earlier by heuristics and rules of thumb is now accelerated and focused by computational tools.
Just this year, Citrine Informatics, a platform for computational materials discovery, raised $16M in its Series C fundraise. There have also been a number of important research discoveries, for example AWS’ project on scaling up computational chemistry with the aim of supporting a circular economy and a new MIT project for material development that improves upon current deep learning methods.
A computation-based materials discovery process is not just an improvement over previous approaches, but marks an “inversion” of the problem. Instead of synthesizing and only then testing materials for certain desired properties, candidate materials can be computationally screened to have a high likelihood of those desired properties.
The need for new materials and accelerated discovery
The computational revolution in materials discovery comes at an opportune time. Our global climate change mitigation effort consists of a number of novel technologies to be deployed, each of which requires specialized materials to be developed, ranging from advanced battery electrodes and membrane-based electrolyzers for hydrogen production to coatings for solar panels.
Although it now seems like a no-brainer to adopt a computational approach, it is only recently that efforts in this direction obtained a degree of maturity. Taking a cue from the drug discovery space, the Materials Genome Initiative (MGI) began in 2011 as a large academic collaboration to build important datasets predicting the physical properties of various classes of materials. The MGI can already count a number of academic discoveries as resounding successes, e.g. polar metals, self-assembling polymers, and OLEDs.
AI-powered materials discovery has now started to move to the commercial stage. It is a nontrivial task though where making a meaningful change requires deep knowledge of two disparate fields. Because of this, only recently has there been a number of startups in this space that have spun out of prominent research groups around the world.
Opportunities and startups in the space
These startups have built AI-powered platforms to accelerate materials discovery, of course with different strengths and specialties. These platforms are used both by academic labs and industrial corporations. Citrine Informatics (founded 2013), Mat3ra (founded 2015), and Kebotix (founded 2017) work on this model and have successfully partnered with large industrial and chemical players across the world such as BP, Bayer and Mitsubishi Chemical.
In India, the computational drugs and materials space is a few years behind larger global players. We have seen a number of startups addressing the field of computational biologicals discovery, such as Quantumzyme and Kcat Enzymes. On the material discovery side, there has been relatively less activity, although that is rising as we speak. Prescience Insilico and SciDentAi are two Bangalore-based startups which are developing state-of-the-art computational materials discovery platforms.
The business execution of such a model remains to be proven, and in particular the ability of these startups to unlock higher revenues by co-owning the IP of the materials they develop for their customers. Partnership with industry is also important, where these startups must remain cognizant of what their customers demand, which in some cases may begin with the relatively easier process optimization process and will only then graduate to new materials discovery.
There is no lack of problem statements though; we need more efficient perovskite-based solar cells, better steels, construction materials with higher embodied carbon, cost-competitive bioplastics, just to name a few. Thus, we see this as a sunrise industry at a stage where real value can be created by combining deep expertise in two fields, and we see Indian companies being able to compete in the global space.
