  We present a novel methodology to search for intranuclear neutron-antineutron
transition ($n\rightarrow\bar{n}$) followed by $\bar{n}$-nucleon annihilation
within an $^{40}$Ar nucleus, using the MicroBooNE liquid argon time projection
chamber (LArTPC) detector. A discovery of $n\rightarrow\bar{n}$ transition or a
new best limit on the lifetime of this process would either constitute physics
beyond the Standard Model or greatly constrain theories of baryogenesis,
respectively. The approach presented in this paper makes use of deep learning
methods to select $n\rightarrow\bar{n}$ events based on their unique features
and differentiate them from cosmogenic backgrounds. The achieved signal and
background efficiencies are (70.22$\pm$6.04)\% and (0.0020$\pm$0.0003)\%,
respectively. A demonstration of a search is performed with a data set
corresponding to an exposure of $3.32 \times10^{26}\,$neutron-years, and where
the background rate is constrained through direct measurement, assuming the
presence of a negligible signal. With this approach, no excess of events over
the background prediction is observed, setting a demonstrative lower bound on
the $n\rightarrow\bar{n}$ lifetime in $^{40}$Ar of $\tau_{\textrm{m}} \gtrsim
1.1\times10^{26}\,$years, and on the free $n\rightarrow\bar{n}$ transition time
of $\tau_{\textrm{\nnbar}} \gtrsim 2.6\times10^{5}\,$s, each at the $90\%$
confidence level. This analysis represents a first-ever proof-of-principle
demonstration of the ability to search for this rare process in LArTPCs with
high efficiency and low background.
