  We investigate the relationship between the thermal properties of a micro
pulsating heat pipe (MPHP) and the internal flow characteristics. The MPHP
consists of an eleven-turn closed-loop of a meandering square microchannel with
a hydraulic diameter of $350\ {}{\mu}{\rm m}$ engraved on a silicon substrate.
The MPHP charged with Fluorinert FC-72 tends to exhibit higher effective
thermal conductivities for the coolant temperature of $T_{\rm c} = 40\
{}^\circ\mathrm{C}$ compared to $T_{\rm c} = 20\ {}^\circ\mathrm{C}$, and
provides the highest effective thermal conductivity of about $700\ {}{\rm
W/(m{\cdot}K)}$ for $T_{\rm c} = 40\ {}^\circ\mathrm{C}$ and a filling ratio of
48%. Interestingly, we observe two different self-oscillation modes having
different thermal conductivities, even for identical heat input rates. This
tendency indicates a hysteresis of the effective thermal conductivity, which
originates from the difference in the heat input rates at which the MPHP falls
into and recovers from dryout. Subsequently, semantic segmentation-based image
recognition is applied to the recorded flow images to identify the flow
characteristics, successfully extracting four different flow patterns involving
liquid slugs, liquid films, dry walls, and rapid-boiling regions. The image
recognition results indicate that high effective thermal conductivities of the
MPHP relate to stable self-oscillations with large amplitudes and high
frequencies, along with long and thin liquid films beneficial for latent heat
transfer. Finally, we perform numerical simulations of latent/sensible heat
transfer via vapor plugs and of sensible heat transfer via liquid slugs using
the extracted flow patterns as inputs. We find that latent heat transfer via
liquid films accounts for a considerable portion of the overall heat transfer,
while the sensible heat transfer via liquid slugs is much less significant.
