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Science-based simulation tools such as Finite Element (FE) models are routinely used in scientific and engineering applications. While their success is strongly dependent on our understanding of underlying governing physical laws, they…
Applications of the M\"ossbauer spectroscopy (MS) in the investigation of Fe-Cr alloys are reviewed. A high sensitivity of the hyperfine magnetic field to the presence of Cr atoms in the vicinity of the probe Fe atoms permits quantitative…
This work presents a three-dimensional constitutive model for shape memory alloys considering the TRansformation-Induced Plasticity (TRIP) as well as the Two-Way Shape Memory Effect (TWSME) through a large deformation framework. The…
Direct experimental characterization of indentation-induced martensitic microstructures in pseudoelastic shape memory alloys (SMAs) is not possible, and thus there is a lack of evidence and understanding regarding the microstructure pattern…
The work presents a thermomechanical model for polycrystalline NiTi-based shape memory alloys developed within the framework of generalized standard solids, which is able to cover loading-mode dependent localization of the martensitic…
Research over the years has shown that the formation of the Fe$_3$Si phase in FINEMET (Fe-Si-Nb-B-Cu) alloys leads to superior soft magnetic properties. In this work, we use a CALPHAD approach to derive Fe-Si phase diagrams to identify the…
Fully harnessing the vast design space enabled by metamaterials to control electromagnetic (EM) fields remains an open problem for researchers. Inverse-design techniques have shown to best exploit the degrees of freedom available in design,…
A fundamental question in the study of ferromagnetic shap ememory alloys is the nature of magnetoelastic coupling and the extent it drives the structural transformation. This question also holds the key to developing new and optimized…
We investigate the basic thermal, mechanical and structural properties of body centred cubic iron ($\alpha$-Fe) at several temperatures and positive loading by means of Molecular Dynamics simulations in conjunction with the embedded-atom…
Powder bed fusion is a widely used additive manufacturing (AM) process for producing complex, small-batch parts that are impractical to manufacture using conventional methods. However, its broader adoption is hindered by process-induced…
Gold-Silver (Au-Ag) core-shell nanostructures are gaining importance in stretchable electronics where high tensile and fatigue resistance is of paramount importance. This work proposes the parameterization of a modified embedded atomic…
In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration. This work is built on top of a recent algorithm SAM, which is capable of computing dense anatomical/semantic correspondences between two…
Differential scanning calorimetry (DSC) and magnetic measurements were performed to study the influence of ferromagnetic 3-d transition elements Fe and Co on structural and magnetic properties of ferromagnetic shape memory alloys Ni2MnGa.…
Control of individual spins at the atomic level holds great promise for miniaturized spintronics, quantum sensing, and quantum information processing. Both single atomic and molecular spin centers are prime candidates for these applications…
We introduce an interpretable deep learning framework that predicts the cohesive energy of transition-metal alloys (TMAs) by embedding cohesion theory within graph neural networks (GNNs). Beyond accurate prediction of cohesive energy, a key…
The ability to accurately quantify the performance an additively manufactured (AM) product is important for a widespread industry adoption of AM as the design is required to: (1) satisfy geometrical constraints, (2) satisfy structural…
Predicting mechanical properties in metal additive manufacturing (MAM) is essential for ensuring the performance and reliability of printed parts, as well as their suitability for specific applications. However, conducting experiments to…
Spin-based electronics or spintronics is an emerging field, in which we try to utilize spin degrees of freedom as well as charge transport in materials and devices. While metal-based spin-devices, such as magnetic-field sensors and…
Adult spine deformity (ASD) is prevalent and leads to a sagittal misalignment in the vertebral column. Computational methods, including Finite Element (FE) Models, have emerged as valuable tools for investigating the causes and treatment of…
Statistical shape modeling (SSM) is an enabling quantitative tool to study anatomical shapes in various medical applications. However, directly using 3D images in these applications still has a long way to go. Recent deep learning methods…