In material science, the time-domain Brillouin scattering (TDBS) technique, initially known as the picosecond acoustic interferometry technique [1], allows imaging either of a continuous change of (or of inhomogeneities occurring due to a mismatch in) acoustical, optical, and/or photo-elastic parameters in transparent materials [2]. In this technique, acoustic waves are generated by an ultrashort optical (pump) pulse absorbed by the tested material or by an optoacoustic transducer in contact with it. In the most general case, up to three waves could be generated and propagate in the sample: one longitudinal (or quasi-longitudinal) and two shear (or quasi-shear) waves. Propagation of these waves is monitored by a second time-delayed ultrashort optical (probe) pulse with the wavelength in the transparency region of the tested material. In that case, a part of the probe beam is reflected at by stationary surfaces/interfaces and another part is reflected at by the propagating acoustic pulses. These reflected parts interfere on the photodetector and give rise to an oscillatory signal having the same frequencies as the Brillouin oscillations. In the most general case, several frequencies could be present in the signal, the values of which being defined by the combinations of the acoustic sound velocity, refractive index? and probe light wavelength. In a polycrystalline material, tracking of the changes of those frequencies with lateral position and with delay time should allow a precise 3D? imaging of the crystallites (or of crystallites groups having the same preferential orientation) and of the boundaries between them. Yet, contrast in the TDBS imaging, such as in the evaluation of texture [3], of position of grain boundaries [4], and of elastic moduli [5] in polycrystalline materials, comes usually from the value of the Brillouin frequency associated to the longitudinal acoustic pulses only. However, a parallel monitoring of both longitudinal and transverse acoustic pulses has recently demonstrated an enhanced ability in determining grains orientation near the surface of a polycrystalline ceria (CeO2) sample [6]. We propose here to extend the technique to three dimensions by making use of the three acoustic pulses, if available, and/or by taking benefit from the fact that Brillouin frequencies depend on the local refractive index and the local sound velocities. Indeed, accurate and simultaneous estimates of the variations of the three Brillouin frequencies with respect to time in collected TDBS signals gives access to the variations of the material parameters as a function of the sample depth. Combining the latter with a 2D lateral scanning over the sample leads to a three dimensional imaging. Some applications of the TDBS technique for 3D imaging of polycrystalline materials, both at atmospheric and at high pressures, will be presented, together with the signal processing procedure/software developed for this purpose. The experimental results have been collected with an ASOPS-based picosecond acoustic microscope (JAX-M1, NETA, France), which allows a fast image acquisition. The fFigure 1 presents examples of the images for ??? obtained with the Brillouin frequencies associated with (a) longitudinal, (b) fast and (c) slow quasi-shear acoustic pulses, demonstrating their complementarity in determining the grain boundary positions in the vicinity of the sample surface. The nanoscale imaging ability of TDBS is improved by the use of shear acoustic waves, which is expected to be even more evident by the gain in contrast obtained on the imaging of buried grain boundaries. Fig. 1. Examples of the images obtained with the Brillouin frequencies associated with (a) quasi-longitudinal, (b) fast and (c) slow quasi-shear acoustic pulses. Acknowledgements This research is supported by the project , the Acoustic Hub® program and the LMAc project NANOSHEAR. References 1.C. Thomsen, H.T. Graham, H.J. Maris, J. Tauc, Optics Communications 60, 55 (1986); doi:10.1016/0030-4018(86)90116-1 2.V. E. Gusev, and P. Ruello, Applied Physics Reviews 5, 031101 (2018); doi:10.1063/1.5017241 3.S. M. Nikitin, N. Chigarev, V. Tournat, A. Bulou, D. Gasteau, B. Castagnede, A. Zerr, V. E. Gusev, Scientific Reports 5, 9352 (2015); doi:10.1038/srep09352 4.M. Khafizov, J. Pakarinen, L. He, H. Henderson, M. Manuel, A. Nelson, B. Jaques, D. Butt, D. Hurley, Acta Materialia 112, 209–215 (2016); doi: 10.1016/j.actamat.2016.04.003 5.M. Kuriakose, S. Raetz, Q. M. Hu, S. M. Nikitin, N. Chigarev, V. Tournat, A. Bulou, A. Lomonosov, P. Djemia, V. E. Gusev, A. Zerr, Physical Review B 96, 134122 (2017); doi:10.1103/PhysRevB.96.134122 6.Y. Wang, D. H. Hurley, Z. Hua, G. Sha, S. Raetz, V. E. Gusev, M. Khafizov, Scripta Materialia 166, 34– 38 (2019); doi: 10.1016/j.scriptamat.2019.02.037