Maxwell Fulford

Maxwell Fulford is a researcher specializing in computational studies of ice crystal growth mechanisms and molecular dynamics. His work integrates advanced simulation techniques with machine learning approaches to analyze ice surfaces and phase transitions. Supervised by Prof. Molteni and Prof. Lorenz, he completed his Doctor of Philosophy in 2017 with a thesis on hexagonal ice growth computational modeling. His research focuses on surface science, quasi-liquid layers, and neural network applications in chemical systems.

• Education: PhD in Computational Chemistry (2017)

Research interests include understanding ice crystal kinetics, molecular mechanisms of surface growth, and developing AI tools for material analysis. His recent work explores face-dependent ice growth dynamics using molecular dynamics simulations and deep learning frameworks. Collaborative efforts focus on atmospheric and cryobiological applications of ice surface properties.

Publications highlight interdisciplinary approaches combining physics-based modeling with data-driven methods. No awards were explicitly mentioned, but his work has garnered significant citations in materials science and computational chemistry domains.