Gan-Q (ガン Q キュー, Gan Kyū)[1][2] is an unorthodox Kaiju that first appeared in Ultraman Gaia. The very first Gan-Q in that series initially appeared as an eyeball-themed monster with an unknown origin.

The name Gan-Q was given by a newspaper company in the Ultraman Gaia series. Attacks are made with electromagnetic waves, or by using special powers to throw rocks. It can also absorb missiles and fire it back.

Mar 21, 2025 · Dr. Gan Qu is a dedicated materials scientist specializing in energy storage and catalysis. He earned his Ph.D. in Materials Physics & Chemistry from Wuhan University and is currently a faculty member at Zhengzhou University.

Mar 19, 2021 · As low-cost electrocatalysts for oxygen reduction reaction applied to fuel cells and metal-air batteries, atomic-dispersed transition metal-nitrogen-carbon materials are emerging, but the genuine mechanism thereof is still arguable.

May 29, 2017 · Here, a rapid, facile, and scalable strategy to efficiently fabricate MBOs and MTOs with various morphologies and crystal structures is reported. Only 1 min is required for the whole process and the yield is above 90%. This strategy is the simplest and the fastest method reported and exhibits large potential for application.

Gan Qu's 18 research works with 797 citations and 3,148 reads, including: Cs‐Induced Phase‐Transformation of Vanadium Oxide for High Performance Zinc‐Ion Batteries

‪Tsinghua University‬ - ‪‪Cited by 10,204‬‬ - ‪LLM Alignment‬

May 27, 2020 · Herein, we propose a bifunctional quinone-type salt to anchor polysulfides and suppress their dissolution for use in high-performance Li-S batteries. We find that the tetrahydroxy-1,4-benzoquinone disodium salt dimer (TBS-dimer) does not dissolve in organic electrolytes and can be generated at 400 °C.

[1] Gan Qu, Rui Pang, Kai Guo et al., Universal triquinoxalinylene (3Q) molecule electrodes for ultrafast and ultrastable Li + storage, Energy Storage Mater. 2022, 46, 322-328.

Oct 18, 2020 · Aiming at the acceleration of use cases for practical quantum computers, we propose QuGAN, a quantum GAN architecture that provides stable convergence, quantum-state based gradients and significantly reduced parameter sets.