Climate and Energy Crises from the Perspective of the Intergovernmental Panel on Climate Change: Trade‐Offs between Systemic Transition and Societal Collapse?

AR6 IPCC reports give divergent messages about the different socio‐economic transition approaches to deal with the current climate emergency. The dangers of not giving a clear message to policymakers and to society on the need of changing the current socio‐economic paradigm are considerable: to fall in the SSP3‐7.0 scenario, which is conducive to the collapse of our current civi‐ lization. In this work, key variables to assess the main functionalities of global socio‐economy are analyzed under a system dynamics approach. This allows for understanding what the evolution is of our current socio‐economy in a framework of climate change and resource depletion. The aim of this work is to provide a different perspective on socio‐economic evolution by identifying similar characteristics in the worst‐case IPCC scenarios with historical behavior in complex societies. From such a historical perspective and the current system evolution, a conceptual model is proposed to explain our globalized complex system near to a phase transition. Then, phase transition corre‐ spondences from the model to the current socio‐economic system are proposed and a series of cor‐ responding preventive measures (in terms of social actions, economic measures, and their linked policies) are suggested to avoid collapse scenarios

Unveiling the Local-to-Global Property Functions of Transient and Active Soft Matter: From Dynamic Gels to Fire Ants

&ldquo;Dynamic networks&rdquo; contain bonds that may disconnect and reattach reversibly, imbuing them with nonlinear, viscoelastic mechanical response. Their mechanical response is further complicated when they are comprised of active constituents that can independently do mechanical work as in the case of &ldquo;active networks&rdquo;. Even dynamic and active networks composed of appearingly simple constituents may display complex emergent mechanics. Indeed, active networks may even spontaneously morph, locomote, and perturb their surroundings in a way that seemingly violates the first and second laws of thermodynamics if viewed at the material scale (i.e., not accounting for local energy storage and the entropic increases associated with local energy conversion processes). Given the rich mechanical behaviors such systems may demonstrate, engineers aiming to create synthetic versions of dynamic and active networks &ndash; whether they be dynamic gels used as tissue engineering scaffolds or swarms of modular robots tasked with completing collective functions &ndash; seek to understand how the local, physical interactions in these systems beget their globally emergent responses. In an effort to predictively design these networks, or inversely understand their structure-property functions, engineers often employ multiscale models ranging from continuum approaches (e.g., statistical mechanics) to high fidelity discrete methods (e.g., molecular dynamics). However, hierarchical network structures and transient bonds can introduce steep property gradients and non-affine deformation that render continuum approaches ill-suited for modeling dynamic networks. Furthermore, effective thermodynamic violations imparted by activity render constitutive modeling particulary difficult for active networks. While high resolution discrete approaches circumvent these issues, they often suffer from high computational cost that makes it difficult to properly map microscale tuning parameters to the emergent macroscale mechanical responses. Therefore, researchers have turned to a tertiary class of discrete, mesoscale network models that coarse-grain constituents to reduce computational expense, but sustain information about networks&rsquo; microstructures. In this dissertation, I introduce one such novel, discrete network model and exhibit its general applicability to both dynamic and active networks. In Chapter II of this dissertation, I introduce the discrete model and compare its mechanical stress predictions for star-shaped dynamic polymer networks (undergoing creep and stress relaxation) to those of a state-of-the-art continuum approach, Transient Network Theory (TNT). In Chapter III, I utilize the model to append TNT and introduce a coupled and physically motivated rule of mixture for dynamic networks containing multiple bond types in series that dissociate at different timescales. In Chapter IV, I exhibit the model&rsquo;s use for applied science by using it to accurately predict the topological and mechanical properties of tetra- and octa-poly(ethylene glycol) gels. Finally, in Chapters V and VI I utilize the model to elucidate a set of local interaction rules between fire ants (S. Invicta) that may reproduce the emergent treadmilling and protrusion growth dynamics observed experimentally in their collectively aggregated rafts. While proper application of the introduced model to any given system is always contingent on due consideration and capture of the underlying, first-order physics, this body of work demonstrates the robustness and generality of this illuminating and much-needed mesoscale framework.</p