Online purchasing creates opportunities to lower the life cycle carbon footprints of consumer products.

A major barrier to transitions to environmental sustainability is that consumers lack information about the full environmental footprints of their purchases. Sellers' incentives do not support reducing the footprints unless customers have such information and are willing to act on it. We explore the potential of modern information technology to lower this barrier by enabling firms to inform customers of products' environmental footprints at the point of purchase and easily offset consumers' contributions through bundled purchases of carbon offsets. Using online stated choice experiments, we evaluated the effectiveness of several inexpensive features that firms in four industries could implement with existing online user interfaces for consumers. These examples illustrate the potential for firms to lower their overall carbon footprints while improving customer satisfaction by lowering the "soft costs" to consumers of proenvironmental choices. Opportunities such as these likely exist wherever firms possess environmentally relevant data not accessible to consumers or when transaction costs make proenvironmental action difficult.

Entropic (de)stabilization of surface-bound peptides conjugated with polymers.

In many emerging biotechnologies, functional proteins must maintain their native structures on or near interfaces (e.g., tethered peptide arrays, protein coated nanoparticles, and amphiphilic peptide micelles). Because the presence of a surface is known to dramatically alter the thermostability of tethered proteins, strategies to stabilize surface-bound proteins are highly sought. Here, we show that polymer conjugation allows for significant control over the secondary structure and thermostability of a model surface-tethered peptide. We use molecular dynamics simulations to examine the folding behavior of a coarse-grained helical peptide that is conjugated to polymers of various lengths and at various conjugation sites. These polymer variations reveal surprisingly diverse behavior, with some stabilizing and some destabilizing the native helical fold. We show that ideal-chain polymer entropies explain these varied effects and can quantitatively predict shifts in folding temperature. We then develop a generic theoretical model, based on ideal-chain entropies, that predicts critical lengths for conjugated polymers to effect changes in the folding of a surface-bound protein. These results may inform new design strategies for the stabilization of surface-associated proteins important for a range technological applications.

A simple mechanism for emergent chirality in achiral hard particle assembly.

For centuries, chirality has been appreciated as a key component in understanding how matter orders. While intuitively chiral particles can self-assemble into chiral superstructures, it is often less obvious how achiral particles can do the same. Here we show that there is a potentially general, packing-based mechanism that explains why many simple, two-dimensional achiral particles assemble into chiral materials. Namely, we use simulations of hard, regular polygons to show that the subtle shape modification of corner rounding surprisingly can induce chiral symmetry breaking by deforming the underlying close-packed lattice. The mechanism quantitatively explains recent experimental results reporting chiral symmetry breaking in the hard triangle system. Moreover, it predicts similar symmetry breaking in the rounded hard rectangle system, which we verify through simulations. Because effective corner rounding is easily realized by modulating repulsive interactions in real systems, this simple mechanism suggests tremendous potential for creating dynamically tunable chiral surfaces with a variety of applications.

A new multiscale algorithm and its application to coarse-grained peptide models for self-assembly.

Peptide self-assembly plays a role in a number of diseases, in pharmaceutical degradation, and in emerging biomaterials. Here, we aim to develop an accurate molecular-scale picture of this process using a multiscale computational approach. Recently, Shell (Shell, M. S. J. Chem. Phys. 2008, 129, 144108-7) developed a coarse-graining methodology that is based on a thermodynamic quantity called the relative entropy, a measure of how different two molecular ensembles behave. By minimizing the relative entropy between a coarse-grained peptide system and a reference all-atom system, with respect to the coarse-grained model's force field parameters, an optimized coarse-grained model can be obtained. We have reformulated this methodology using a trajectory-reweighting and perturbation strategy that enables complex coarse-grained models with at least hundreds of parameters to be optimized efficiently. This new algorithm allows for complex peptide systems to be coarse-grained into much simpler models that nonetheless recapitulate many correct features of detailed all-atom ones. In particular, we present results for a polyalanine case study, with attention to both individual peptide folding and large-scale fibril assembly.