More Like this

1. Reversible strain-promoted DNA polymerization

   https://doi.org/10.1126/sciadv.ado8020  

   Han, Zhenyu; Hayes, Oliver G; Partridge, Benjamin E; Huang, Chi; Mirkin, Chad A (April 2024, Science Advances)

   Molecular strain can be introduced to influence the outcome of chemical reactions. Once a thermodynamic product is formed, however, reversing the course of a strain-promoted reaction is challenging. Here, a reversible, strain-promoted polymerization in cyclic DNA is reported. The use of nonhybridizing, single-stranded spacers as short as a single nucleotide in length can promote DNA cyclization. Molecular strain is generated by duplexing the spacers, leading to ring opening and subsequent polymerization. Then, removal of the strain-generating duplexers triggers depolymerization and cyclic dimer recovery via enthalpy-driven cyclization and entropy-mediated ring contraction. This reversibility is retained even when a protein is conjugated to the DNA strands, and the architecture of the protein assemblies can be modulated between bivalent and polyvalent states. This work underscores the utility of using DNA not only as a programmable ligand for assembly but also as a route to access restorable bonds, thus providing a molecular basis for DNA-based materials with shape-memory, self-healing, and stimuli-responsive properties. 

   more » « less
2. Thiol–Anhydride Dynamic Reversible Networks

   https://doi.org/10.1002/anie.202001388  

   Podgórski, Maciej; Mavila, Sudheendran; Huang, Sijia; Spurgin, Nathan; Sinha, Jasmine; Bowman, Christopher N. (June 2020, Angewandte Chemie International Edition)
3. Approximately Reversible Stochastic Processing Networks

   Shah, Devavrat (July 2019, INFORMS Applied Probability Society Conference)

   The property of (quasi-)reversibility of Markov chains have led to elegant characterization of steady-state distribution for complex queueing networks, e.g. celebrated Jackson networks, BCMP (Baskett, Chandi, Muntz, Palacois) and Kelly theorem. In a nutshell, despite the complicated interaction, in the steady-state, the queues in such networks exhibit independence and subsequently lead to explicit calculations of distributional properties of the queuing network that may seem impossible at the outset. The model of stochastic processing network (cf. Harrison 2000) captures variety of dynamic resource allocation problems including the flow-level networks used for modeling bandwidth sharing in the Internet, switched networks (cf. Shah, Wischik 2006) for modeling packet scheduling in the Internet router and wireless medium access, and hybrid flow-packet networks for modeling job-and-packet level scheduling in data centers. Unlike before, an appropriate resource allocation or scheduling policy is required in such networks to achieve good performance. Given the complexity, asymptotic analytic approaches such as fluid model or Lyapunov-Foster criteria to establish positive-recurrence and heavy traffic or diffusion approximation to characterize the scaled steady-state distribution became method of choice. A remarkable progress has been made along these lines over the past few decades, but there is a need for much more to match the explicit calculations in the context of reversible networks. In this work, we will present an alternative to this approach that leads to non-asymptotic, explicit characterization of steady-state distribution akin BCMP / Kelly theorems. This involves (a) identifying a "relaxation" of the given stochastic processing network in terms of an appropriate (quasi-)reversible queueing network, and (b) finding a resource allocation or scheduling policy of interest that "emulates" the "relaxed" networks within "small error". The proof is in the puddling -- we will present three examples of this program: (i) distributed scheduling in wireless network, (ii) scheduling in switched networks, and (iii) flow-packet scheduling in a data center. The notion of "baseline performance" (cf. Harrison, Mandayam, Shah, Yang 2014) will naturally emerges as a consequence of this program. We will discuss open questions pertaining multi-hop networks and computation complexity. 

   more » « less
4. Reversible electrowetting transitions on superhydrophobic surfaces

   https://doi.org/10.1039/d1cp04220c  

   Vanzo, D.; Luzar, A.; Bratko, D. (December 2021, Physical Chemistry Chemical Physics)

   An electric field applied across the interface has been shown to enable transitions from the Cassie to the Wenzel state on superhydrophobic surfaces with miniature corrugations. Molecular dynamics (MD) simulations manifest the possibility of reversible cycling between the two states when narrow surface wells support spontaneous expulsion of water in the absence of the field. With approximately 1 nm sized wells between the surface asperities, the response times to changes in the electric field are of O(0.1) ns, allowing up to GHz frequency of the cycle. Because of the orientation preferences of interfacial water in contact with the solid, the phenomenon depends on the polarity of the field normal to the interface. The threshold field strength for the Cassie-to-Wenzel transition is significantly lower for the field pointing from the aqueous phase to the surface; however, once in the Wenzel state, the opposite field direction secures tighter filling of the wells. Considerable hysteresis revealed by the delayed water retraction at decreasing field strength indicates the presence of moderate kinetic barriers to expulsion. Known to scale approximately with the square of the length scale of the corrugations, these barriers preclude the use of increased corrugation sizes while the reduction of the well diameter necessitates stronger electric fields. Field-controlled Cassie-to-Wenzel transitions are therefore optimized by using superhydrophobic surfaces with nanosized corrugations. Abrupt changes indicate a high degree of cooperativity reflecting the correlations between the wetting states of interconnected wells on the textured surface. 

   more » « less
5. The Complexity of Iterated Reversible Computation

   https://doi.org/10.46298/theoretics.23.10  

   Eppstein, David (December 2023, TheoretiCS)

   We study a class of functional problems reducible to computing $$f^{(n)}(x)$$for inputs $$n$$ and $$x$$, where $$f$$ is a polynomial-time bijection. As we prove,the definition is robust against variations in the type of reduction used inits definition, and in whether we require $$f$$ to have a polynomial-time inverseor to be computible by a reversible logic circuit. These problems arecharacterized by the complexity class $$\mathsf{FP}^{\mathsf{PSPACE}}$$, andinclude natural $$\mathsf{FP}^{\mathsf{PSPACE}}$$-complete problems in circuitcomplexity, cellular automata, graph algorithms, and the dynamical systemsdescribed by piecewise-linear transformations. 

   more » « less