01 Early Research
Data-Driven Grid Intelligence
Real-time AI optimization of energy distribution networks. Predictive load balancing and autonomous routing reduce transmission losses by up to 40%.
DAKE works at the intersection of physics, data science, and materials research — exploring unconventional approaches to energy generation and transmission.
DAKE is a research company working at the intersection of physics, artificial intelligence, and engineering. The focus is on four research vectors: AI-driven optimisation of energy grids, quantum systems for next-generation energy conversion, AI & machine learning for self-organising distributed infrastructure, and gravitational potential as a source of continuous, predictable power.
The work is exploratory by nature. Some approaches will yield incremental improvements; others may point in entirely new directions. The common thread is rigorous, physics-first investigation.
Our research spans the full spectrum of energy science, from conventional optimization to entirely new physical paradigms.
Real-time AI optimization of energy distribution networks. Predictive load balancing and autonomous routing reduce transmission losses by up to 40%.
Exploiting quantum tunneling, multi-exciton generation, and coherent energy transfer to design next-generation conversion systems — from photovoltaics to quantum thermodynamic engines operating beyond classical efficiency limits.
Self-organizing distributed infrastructure where autonomous nodes negotiate and optimize energy flows in real time — no central point of failure.
Converting gravitational potential energy from mass differentials, tidal cycles, and structural loading into continuous, predictable electrical output.
Four active research programs, one per technology vector.
Developing foundation models for real-time energy demand prediction trained on large-scale grid telemetry data — enabling predictive load balancing without explicit supervision.
Mapping the theoretical upper limits of energy conversion in quantum systems — from multi-exciton generation in photovoltaics to coherent transport phenomena in thermodynamic engines.
Designing decentralised communication and negotiation protocols for energy networks where nodes independently optimise local and global flows without central orchestration.
Designing infrastructure-scale mechanical systems that exploit gravitational differentials — tidal cycles, structural loading, and mass displacement — as sources of long-duration, dispatchable power.
"Most of the energy physics we rely on was formalised decades ago. The assumption that all practically useful phenomena have already been found is probably wrong."— DAKE Research Notes
DAKE is open to collaboration with research institutions, universities, and organisations working on complementary problems.