Postdoc, Nantes Institute of Materials, France
Rafael Herschberg is a highly skilled research engineer with six years of experience in the metallurgical industry. He specializes in advanced simulations and modeling techniques, particularly in atomistic approaches such as Atomistic Kinetic Monte Carlo and Phase Field Crystal methods. Rafael is also proficient in data science and machine learning, which he integrates into his work in alloy design and material engineering. His career spans research roles in prestigious institutions like the Institut des Matériaux de Nantes and CEA Saclay, and he has presented groundbreaking research internationally. Passionate about collaboration, Rafael works effectively with multidisciplinary teams to address complex modeling challenges and innovate in alloy design. 🌍💡🔬
Profile
Google Scholar
Education
Rafael holds a Ph.D. in Physics from Université de Paris-Saclay (2018), where he specialized in materials science. He also completed a Magister in Materials Science and Technology at the Instituto Sabato (UNSAM – CNEA) in Buenos Aires (2015). His academic journey began with a Bachelor’s degree in Physics, with a minor in Mathematics and Economics, from the Rochester Institute of Technology (2012). His robust educational foundation provided him with a deep understanding of physics, material science, and computational modeling, shaping his career as a researcher and engineer. 🎓📚🧑🎓
Experience
Rafael’s professional career includes roles as a Research Engineer at various prestigious institutions. At the Institut des Matériaux de Nantes (2023–present), he engineered Ni-based alloys through computational thermodynamics, machine learning, and optimization algorithms. At Université de Rouen-Normandie (2021–2022), he modeled Cottrell atmospheres in steels using advanced parallel algorithms and high-performance computing (HPC). He also worked as a Data Analysis Consultant in real estate (2020) and a Research Engineer at CEA Saclay (2015–2018), where he developed numerical algorithms for analyzing thermo-kinetics phenomena in steels. His diverse experience reflects a commitment to scientific advancement and innovation. 💼🔧💻
Research Focus
Rafael’s research focuses on atomistic modeling, material science, and advanced simulation techniques. He specializes in alloy design, particularly the diffusion of carbon in FeCr alloys and the development of novel alloy strategies using machine learning. His work also includes modeling Cottrell atmospheres in steels and exploring thermo-kinetics phenomena in austenitic steels. Rafael aims to integrate computational thermodynamics and optimization algorithms into the alloy design process to drive innovation in material properties and applications. His research enhances both theoretical and practical advancements in the field of materials science. ⚙️🔬🧪
Publication Top Notes
- Atomistic Modelling of the Diffusion of C in FeCr Alloys
- From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy
- Modeling the Diffusion of Interstitial Impurities and their Impact on the Ageing of Ferritic Steels
- Interacción entre Precipitados y la Transformación Martensítica en Monocristales de CuAlNi con Memoria de Forma