Key Findings and Scaling Laws

This record presents a concise mathematical framework and scaling laws for an event-driven energy conversion paradigm operating in high-impedance electrostatic environments. The work formalizes threshold-triggered energy release events and establishes invariant relations governing per-event energy, event rate, and average power output. The formulation reframes electrostatic potential as a stored state that produces usable power only through discrete, non-steady-state transitions. The results are intended as a foundational reference (prior art) for non-equilibrium, event-based energy systems and do not disclose device-specific implementations.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-03
DOI
https://doi.org/10.5281/zenodo.18136664
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Key Findings and Scaling Laws

adam akeely
Zenodo (CERN European Organization for Nuclear Research)
Advanced Memory and Neural Computing
article

Key Findings and Scaling Laws

adam akeely
article en

Abstract

This record presents a concise mathematical framework and scaling laws for an event-driven energy conversion paradigm operating in high-impedance electrostatic environments. The work formalizes threshold-triggered energy release events and establishes invariant relations governing per-event energy, event rate, and average power output. The formulation reframes electrostatic potential as a stored state that produces usable power only through discrete, non-steady-state transitions. The results are intended as a foundational reference (prior art) for non-equilibrium, event-based energy systems and do not disclose device-specific implementations.

Zenodo (CERN European Organization for Nuclear Research)
Affordable and clean energy
Openalex Percentile: Top 98%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Key Findings and Scaling Laws — adam akeely · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS