Virtual Reality (VR) for scientific visualization has been researched from the 90s, but there has been little research into the fundamental aspects of VR for scientific visualisation. Questions like "Is VR ready for adoption?", "How does VR design differ from design for monocular systems?" are two examples of fundamental questions yet to addressed. In this paper a scientific visualiser based on the game engine Unreal Engine 4 (UE4) was developed and tested by educators and researchers. A full ray marcher was successfully implemented and a near zero-cost cutting tool was developed. VR is found to have a lot of potential for improving visualisation of data sets with structural "interleaved complexity". VR has also been deemed ready for limited mass adoption. Through field testing visualisations of volumetric and geometric models, three major issues are identified: Current VR hardware lacks adequate input options. Menu and interaction design must be reinvented. Furthermore, 90 FPS is required for comfortable and extended VR use, which makes most current algorithms and data sets incompatible with VR. The conclusion reached through analysis of and feedback regarding the computational cost and design challenges of VR is that VR is best utilised as a tool in already existing monocular visualisation tool kits. By using a monocular system to perform most of the encoding and filtering and then use VR for inspecting the pre-processed model, it is possible to obtain the best of both worlds.