Influence of point defects on thermal conductivity in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>TiFe</mml:mi> <mml:mi>x</mml:mi> </mml:msub> <mml:msub> <mml:mi>Ni</mml:mi> <mml:mrow> <mml:mn>1</mml:mn> <m

Point defects and impurities are highly effective mechanisms for manipulating thermal conductivity, primarily because they significantly enhance phonon scattering. However, accurately computing thermal conductivities in defect-laden systems using density functional theory is computationally expensive, leading to a scarcity of theoretical simulations. Here we tackle the case of the widely studied double half-Heusler compound <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mrow> <a:msub> <a:mi>TiFe</a:mi> <a:mi>x</a:mi> </a:msub> <a:msub> <a:mi>Ni</a:mi> <a:mrow> <a:mn>1</a:mn> <a:mo>−</a:mo> <a:mi>x</a:mi> </a:mrow> </a:msub> <a:mi>Sb</a:mi> </a:mrow> </a:math> , using first principles and Green's function methods to calculate the phonon-defect scattering rates. Existing predictions for the lattice thermal conductivity of pristine <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:mrow> <b:msub> <b:mi>TiFe</b:mi> <b:mrow> <b:mn>0.5</b:mn> </b:mrow> </b:msub> <b:msub> <b:mi>Ni</b:mi> <b:mrow> <b:mn>0.5</b:mn> </b:mrow> </b:msub> <b:mi>Sb</b:mi> </b:mrow> </b:math> are significantly higher than measurements in actual samples. In contrast, we achieve excellent agreement with experimental points for Fe-rich systems with 1.16% <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:msub> <c:mi>Fe</c:mi> <c:mi>Ni</c:mi> </c:msub> </c:math> substitutions and Ni-rich systems with 0.87% <d:math xmlns:d="http://www.w3.org/1998/Math/MathML"> <d:msub> <d:mi>Ni</d:mi> <d:mi>int</d:mi> </d:msub> </d:math> interstitial defects. We provide detailed results for three types of defects and assess their contributions to the behavior of specific compositions. The data suggests that Hall concentrations can significantly overestimate defect concentrations. These results highlight the predictive capabilities of phonon transport modeling and its importance in understanding and quantifying defects in semiconductors.