Semiconductors
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Data-centers: the economics?
The capex costs of data-centers are typically $10M/MW, with opex costs dominated by maintenance (c40%), electricity (c15-25%), labor, water, G&A and other. A 30MW data-center must generate $100M of revenues for a 10% IRR, while an AI data-center in 2025+ may need to charge $10/EFLOP of compute.
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Data center energy: caps lock?
Everybody knows “AI data centers use round-the-clock power”. Yet one of the biggest power challenges for AI data data centers is precisely that they do not use round-the-clock power. They incur large load transients that cannot be handled by batteries, power grids or most generation. This 15-page report explores data center load profiles, which may…
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Capacitor market: leading companies?
This data-file profiles a dozen leading companies in capacitors, which control two-thirds of the $30bn pa global market. Many companies also produce other passive electronic components, sensors and MOSFETs. Hence will the rise of AI, especially transient-heavy data-centers, pull on demand?
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Groq: AI inference breakthrough?
Groq has developed LPUs for AI inference, which are up to 10x faster and 80-90% more energy efficient than today’s GPUs. This 8-page Groq technology review assesses its patent moat, LPU costs, implications for our AI energy models, and whether Groq could ever dethrone NVIDIA’s GPUs?
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Ideal Power: Bi-Directional Bipolar Junction Transistors?
Bi-Directional Bipolar Junction Transistors are an emerging category of semiconductor-based switching device, that can achieve lower on-state voltage drops than MOSFETs and softer, faster switching than IGBTs, to improve efficiency and lower component count in bi-directional power converters. This data-file screens B-TRAN patents from Ideal Power.
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Energy intensity of AI: chomping at the bit?
Rising energy demands of AI are now the biggest uncertainty in all of global energy. To understand why, this 17-page note is an overview of AI computing from first principles, across transistors, DRAM, GPUs and deep learning. GPU efficiency will inevitably increase, but compute increases faster. AI most likely uses 300-2,500 TWH in 2030, with…
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Bill of materials: electronic devices and data-centers?
Electronic devices are changing the world, from portable electronics to AI data centers. Hence what materials are used in electronic devices, as percentage of mass, and in kg/kW terms? This data-file tabualates the bill of materials, for different devices, across different studies.
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Energy and AI: the power and the glory?
The power demands of AI will contribute to the largest growth of new generation capacity in history. This 18-page note evaluates the power implications of AI data-centers. Reliability is crucial. Gas demand grows. Annual sales of CCGTs and back-up gensets in the US both rise by 2.5x? This is our most detailed AI report to…
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Vapor deposition: leading companies?
This data-file is a screen of leading companies in vapor deposition, manufacturing the key equipment for making PV silicon, solar, AI chips and LED lighting solutions. The market for vapor deposition equipment is worth $50bn pa and growing at 8% per year. Who stands out?
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Seebeck Effect: are thermoelectrics the next solar?
Solar semiconductors have changed the world, converting light into clean electricity. Hence can thermoelectric semiconductors follow the same path, converting heat into electricity with no moving parts? This 14-page report reviews the opportunity, challenges, efficiency, costs and companies.
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