A computational approach to the reconstruction of surface geometry from early temple superstructures

Recovering the control or implicit geometry underlying temple architecture requires bringing together fragments of evidence from field measurements, relating these to mathematical and geometric descriptions in canonical texts and proposing "best-fit" constructive models. While scholars in the field have traditionally used manual methods, the innovative application of niche computational techniques can help extend the study of artefact geometry. This paper demonstrates the application of a hybrid computational approach to the problem of recovering the surface geometry of early temple superstructures. The approach combines field measurements of temples, close-range architectural photogrammetry, rule-based generation and parametric modelling. The computing of surface geometry comprises a rule-based global model governing the overall form of the superstructure, several local models for individual motifs using photogrammetry and an intermediate geometry model that combines the two. To explain the technique and the different models, the paper examines an illustrative example of surface geometry reconstruction based on studies undertaken on a tenth century stone superstructure from western India. The example demonstrates that a combination of computational methods yields sophisticated models of the constructive geometry underlying temple form and that these digital artefacts can form the basis for in depth comparative analysis of temples, arising out of similar techniques, spread over geography, culture and time.

On recovering the surface geometry of temple superstructures

The application of computational techniques to the analysis of heritage artifacts enables scholars to bring together diverse fragments of surviving evidence, construe "best-fit" strategies and unearth implicit or hidden relationships. This paper reports a hybrid approach for recovering the surface geometry of temples. The approach combines physical measurements, architectural photogrammetry and generative rules to create a parametric model of the surface. The computing of surface geometry is broken into three parts, a global model governing the overall form of the superstructure, local models governing the geometry of individual motifs and finally the global and local models are combined into a single geometry. In this paper, the technique for recovering surface geometry is applied to a tenth century stone superstructure: the temple of Ranakdevi at Wadhwan in Western India. The global model of the superstructure and the local model of one individual motif are presented.

Facet selectivity in gold binding peptides: exploiting interfacial water structure

Peptide sequences that can discriminate between gold facets under aqueous conditions offer a promising route to control the growth and organisation of biomimetically-synthesised gold nanoparticles. Knowledge of the interplay between sequence, conformations and interfacial properties is essential for predictable manipulation of these biointerfaces, but the structural connections between a given peptide sequence and its binding affinity remain unclear, impeding practical advances in the field. These structural insights, at atomic-scale resolution, are not easily accessed with experimental approaches, but can be delivered via molecular simulation. A current unmet challenge lies in forging links between predicted adsorption free energies derived from enhanced sampling simulations with the conformational ensemble of the peptide and the water structure at the surface. To meet this challenge, here we use an in situ combination of Replica Exchange with Solute Tempering with Metadynamics simulations to predict the adsorption free energy of a gold-binding peptide sequence, AuBP1, at the aqueous Au(111), Au(100)(1 × 1) and Au(100)(5 × 1) interfaces. We find adsorption to the Au(111) surface is stronger than to Au(100), irrespective of the reconstruction status of the latter. Our predicted free energies agree with experiment, and correlate with trends in interfacial water structuring. For gold, surface hydration is predicted as a chief determining factor in peptide-surface recognition. Our findings can be used to suggest how shaped seed-nanocrystals of Au, in partnership with AuBP1, could be used to control AuNP nanoparticle morphology.