I did my PhD in (Physical) Chemistry at the University of Amsterdam. My PhD research was experimental in nature: “far-infrared” (now Terahertz) spectroscopy. During my PhD I spent 5 months during the summer of 1975 at CECAM in Orsay (France) where I familiarised myself with Molecular Dynamics and Monte Carlo simulations, a field that was then just taking off in Europe. Subsequently, I was a Postdoc at UCLA and Research Scientist at Shell, before moving to back Academia in 1981.

Among the topics that I studied were: simulations of “Entropic” Phase transitions in liquid crystals, (crystal) nucleation, Complex self-assembly, and super-selective targeting of cells. For my work I developed novel algorithms, including Free-energy methods, Configurational Bias Monte Carlo for (chain molecules), and techniques to “count” uncountably large numbers of distinct (granular) packings, and the modelling of DNA-mediated self-assembly.

With my former student Berend Smit, I wrote a book about computer simulation techniques (Understanding Molecular Simulations – 3rd edition, 2023). The book is widely used.

I like to share my fascination with the giants of thermodynamics and statistical physics of the 19th century (Carnot, Gibbs, Maxwell, Boltzmann). But my interest in history goes beyond that.

Rather than just giving a list of topics that I found (and still find) interesting, let me give two examples from my time in Cambridge.
The first is a technique to count the number of distinct packings of, say, chocolate eggs in a jar. If the number of particles exceeds 10-15, the number of packing becomes super-astronomically large and cannot be counted. By exploiting my expertise with free-energy calculations, I could translate the counting problem into a sampling problem. It then became feasible to “count” numbers of packings exceeding 10^200, or (much) larger.

A more recent example is the work that we did on super-selective targeting. The idea is that many diseased cells over-express certain peptide fragments on their surface. But often, healthy cells express the same fragments, just fewer. In such cases “monovalent” molecules target healthy cells as well as diseased cells: less strongly, but there are many more healthy cells. Super selective targeting uses particles that carry several ligands. These particles bind selectively to surfaces that express the target peptide receptors above a certain threshold concentration. The road from idea to application is long, but I am happy to see that it is now progressing well.