Five researchers from academia, translational institutes, and industry confronted the most uncomfortable fact in Indian applied science: brilliant materials regularly die between the laboratory and the factory.
Prof. Chandra Shekhar Sharma, who moderated Panel Discussion 1 — titled ‘Translating Carbon Fundamental Research into Scalable Sustainable Technologies’ — opened proceedings with a provocation dressed as a question: why do so many research breakthroughs fail to become products? The panelists — drawn from ARCI, IIT Hyderabad, NIT Warangal, and Brahmaion Private Limited — spent sixty minutes furnishing answers that were, variously, technical, systemic, institutional, and philosophical.
The Problem of Consistency
The first and most technically specific barrier identified was repeatability. A material synthesised at milligram scale in a laboratory possesses precisely the properties that earned it attention: a particular surface area, a defined pore volume, a measured electrochemical response. Scale it to kilograms, let alone tonnes, and these properties shift — sometimes subtly, sometimes catastrophically. ‘Batch-to-batch consistency,’ one panelist noted, ‘is the unglamorous problem nobody wants to write a paper about, but it is the problem that kills technologies.’ The audience laughed, uncomfortably.
“The computational chemist, the ML scientist, and the experimentalist live in silos. They work in silos. They never talk to each other. That is the problem.”
The consistency problem is compounded by how research is incentivised. Academic laboratories are rewarded for peak performance — the best result from the best batch, reported in a paper — not for the mean performance across fifty batches under varying conditions. Techno-Economic Analysis (TEA), which requires researchers to assess lifecycle costs, energy inputs, supply chain vulnerabilities, and production economics alongside electrochemical metrics, remains marginal in Indian academic culture. The panel was unsparing: if a material cannot be produced consistently at cost, no amount of scientific elegance saves it.
The Consortium Model
The panelists converged on a structural solution: the consortium model, integrating academic laboratories (fundamental science and material discovery), translational research institutes such as ARCI (scaling to TRL 5/6), and industry or startups (market alignment, manufacturing, user-centric design). No single institution can do all three; the tragedy of Indian materials research, one panelist argued, is that the three communities have historically operated in silos — each optimising for its own metrics, speaking its own language, and rarely finishing each other’s sentences.
The session’s sharpest exchange emerged from a question posed by a startup founder in the audience, who challenged the panel on the specific problem of manufacturing equipment: materials research may advance to TRL 3 in a university lab, but scaling beyond that requires a 20-kilogram milling unit, a continuous pusher-type furnace, or a cell fabrication line — equipment that is almost entirely imported. Dr. Tata Narasinga Rao’s response extended his biryani metaphor: ARCI had begun fabricating some of its own equipment precisely to break this dependence, including components for its supercapacitor fabrication line. ‘Unless manufacturing research is done,’ he said, ‘this gap will continue.’
The AI/Computational Divide
A particularly illuminating exchange arose when a computational materials chemist in the audience asked how machine learning and atomistic modelling could accelerate materials discovery for the panel’s experimental researchers. The response from Dr. Narasinga Rao was disarmingly direct: ‘The computational chemist, the ML scientist, and the experimentalist live in silos. We know each other for a long time and I have never tested the outcome of your computational work. It never happened.’ He urged precisely the kind of embedded collaboration — where an ML scientist works alongside an experimentalist, screening material combinations in silico before synthesis — that, he noted, is standard practice in advanced research systems abroad and conspicuously absent in India. The path forward, several panelists agreed, begins with a simple institutional commitment: start talking to each other from day one of a research project, not at the paper-writing stage.
The panel’s collective resolution was summarised by Prof. Sharma: the Carbon Lab’s second fifteen years must be animated by a question that its first fifteen years rarely asked explicitly — ‘Can we design research with translation in mind from the beginning?’ The valley of death, the discussion made clear, is not a geological feature. It is a design flaw.Raja Aditya
