biostudies-literatureUnknown13(12)Piasecki RThe main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic clusters that serve as surrogate inclusions. The clusters have the same individual areas and interfacMaterials (Basel, Switzerland)E2748https://www.ebi.ac.uk/biostudies/studies/S-EPMC7345931biostudies-literatureA Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions.PMC7345931Bartecka AFraczek DPiasecki ROlchawa WfalseA Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions.The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic clusters that serve as surrogate inclusions. The clusters have the same individual areas and interfac2020-01-01T00:00:00Z2020 Jun2026-07-15T23:34:39.756Z2025-04-19T18:01:32.351ZS-EPMC73459313256040410.3390/ma13122748