We derive a kinetic Monte Carlo algorithm to simulate Ô¨Çow-induced nucleation in polymer melts. The crystallisation kinetics are modiÔ¨Åed by both stretching and orientation of the amorphous chains under Ô¨Çow, which is modelled by a recent non-linear tube theory. Rotation of the crystallites under Ô¨Çow is modelled by a simultaneous Brownian dynamics simulation. Our kinetic Monte Carlo approach is highly efÔ¨Åcient at simulating nucleation and is tractable even at low under-cooling. The simulations predict enhanced nucleation under both transient and steady state shear. Furthermore the model predicts the growth of shish-like elongated nuclei for sufÔ¨Åciently fast Ô¨Çows, which grow by a purely kinetic mechanism. We perform kinetic Monte Carlo simulations of Ô¨Çow-induced nucleation in polymer melts with an algorithm that is tractable even at low undercooling. The conÔ¨Åguration of the noncrystallized chains under Ô¨Çow is computed with a recent nonlinear tube model. Our simulations predict both enhanced nucleation and the growth of shish-like elongated nuclei for sufÔ¨Åciently fast Ô¨Çows. The simulations predict several experimental phenomena and theoretically justify a previously empirical result for the Ô¨Çow-enhanced nucleation rate. The simulations are highly pertinent to both the fundamental understanding and process modeling of Ô¨Çow-induced crystallization in polymer melts. Flow-induced crystallization (FIC) behavior of a high-density polyethylene melt in two entry-exit flow geometries was investigated by direct optical observation using a multi-pass rheometer and the results compared with a viscoelastic flow simulation. A set of experiments was performed at several piston speeds using a sharp and a rounded entry-exit slit and the region of onset for visible FIC was identified in both cases. During flow narrow crystal filament regions localized at the sidewalls and in a downstream ‚Äúfang‚Äù region of stress accumulation were identified. A melt flow two-dimensional numerical simulation using a Lagrangian solver, FLOWSOLVE, and an 11-mode Pom-Pom model satisfactorily matched experimental pressure difference and birefringence fringe distribution for the flow. An algorithm to calculate the specific work accumulated by each fluid element in the complex flow field was implemented within FLOWSOLVE and a method was proposed to estimate the critical specific work for the onset of visible oriented FIC. The concept of specific work applied to the numerical simulations was capable of successfully predicting the experimental regions where FIC occurred. protein L Beta-sheet proteins are generally more able to resist mechanical deformation than a-helical proteins. Experiments measuring the mechanical resistance of b-sheet proteins extended by their termini led to the hypothesis that parallel, directly hydrogen-bonded terminal b-strands provide the greatest mechanical strength. Here we test this hypothesis by measuring the mechanical properties of protein L, a domain with a topology predicted to be mechanically strong, but with no known mechanical function. A pentamer of this small, topologically simple protein is resistant to mechanical deformation over a wide range of extension rates. Molecular dynamics simulations show the energy landscape for protein L is highly restricted for mechanical unfolding and that this protein unfolds by the shearing apart of two structural units in a mechanism similar to that proposed for ubiquitin, which belongs to the same structural class as protein L, but unfolds at a significantly higher force. These data suggest that the mechanism of mechanical unfolding is conserved in proteins within the same fold family and demonstrate that although the topology and presence of a hydrogen-bonded clamp are of central importance in determining mechanical strength, hydrophobic interactions also play an important role in modulating the mechanical resistance of these similar proteins. simple models Recent experiments have demonstrated that proteins unfold when two atoms are mechanically pulled apart, and that this process is different to when heated or when a chemical denaturant is added to the solution. Experiments have also shown that the response of proteins to external forces is very diverse, some of them being ‘‘hard,’’ and others ‘‘soft.’’ Mechanical resistance originates from the presence of barriers on the energy landscape; together, experiment and simulation have demonstrated that unfolding occurs through alternative pathways when different pairs of atoms undergo mechanical extension. Here we use simulation to probe the mechanical resistance of six structurally diverse proteins when pulled in different directions. For this, we use two very different models: a detailed, transferable one, and a coarse-grained, structure-based one. The coarse-grained model gives results that are surprisingly similar to the detailed one and qualitatively agree with experiment; i.e., the mechanical resistance of different proteins or of a single protein pulled in different directions can be predicted by simulation. The results demonstrate the importance of pulling direction relative to the local topology in determining mechanical stability, and rationalize the effect of the location of importation/degradation tags on the rates of mitochondrial import or protein degradation in vivo. revisited Single-molecule experiments and their application to probe the mechanical resistance and related properties of proteins provide a new dimension in our knowledge of these important and complex biological molecules. Single-molecule techniques may not have yet overridden solution experiments as a method of choice to characterize biophysical and biological properties of proteins, but have stimulated a debate and contributed considerably to bridge theory and experiment. Here we demonstrate this latter contribution by illustrating the reach of some theoretical findings using a solvable but nontrivial molecular model whose properties are analogous to those of the corresponding experimental systems. In particular, we show the relationship between the thermodynamic and the mechanical properties of a protein. The simulations presented here also illustrate how forced and spontaneous unfolding occur through different pathways and that folding and unfolding rates at equilibrium cannot in general be obtained from forced unfolding experiments or simulations. We also study the relationship between the energy surface and the mechanical resistance of a protein and show how a simple analysis of the native state can predict much of the mechanical properties of a protein. x_u Mechanical unfolding of polyproteins by force spectroscopy provides valuable insight into their free energy landscapes. Most experiments of the unfolding process have been fit to two-state and/or one dimensional models, with the details of the protein and its dynamics often subsumed into a zero-force unfolding rate and a distance x_u(1D) to the transition state. We consider the entire phase space of a model protein under a constant force, and show that x_u(1D) contains a sizeable contribution from exploring the full multidimensional energy landscape. This effect is greater for proteins with many degrees of freedom that are affected by force; and surprisingly, we predict that externally attached flexible linkers also contribute to the measured unfolding characteristics. Jarzynski The equilibrium free energy difference between two long-lived molecular species or “conformational states” of a protein (or any other molecule) can in principle be estimated by measuring the work needed to shuttle the system between them, independent of the irreversibility of the process. This is the meaning of the Jarzynski equality (JE), which we test in this paper by performing simulations that unfold a protein by pulling two atoms apart. Pulling is performed fast relative to the relaxation time of the molecule and is thus far from equilibrium. Choosing a simple protein model for which we can independently compute its equilibrium properties, we show that the free energy can be exactly and effectively estimated from nonequilibrium simulations. To do so, one must carefully and correctly determine the ensemble of states that are pulled, which is more important the farther from equilibrium one performs simulations; this highlights a potential problem in using the JE to extract the free energy from forced unfolding experiments. The results presented here also demonstrate that the free energy difference between the native and denatured states of a protein measured in solution is not always equal to the free energy profile that can be estimated from forced unfolding simulations (or experiments) using the JE.