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1. Modeling and Control of Multi-Energy Dynamical Systems: Hidden Paths to Decarbonization.

   Ilic, M. (July 2022, International. Institute of research and Education in Power Systems Dynamics (IREP))

   This paper points out some key drawbacks of today’s modeling and control underlying hierarchical electric power system operations and planning as the hidden roadblocks on the way to decarbonization. We suggest that these can be overcome by enhancing today’s information exchange and control. This can be done by revealing and utilising inherent structurepreserving features of complex physical systems, and, based on this, by establishing multi-layered energy modeling. Each module (component, control area, non-utility-owned entities) can be characterized in terms of its interaction variable, and higher level models can be used to understand the interaction dynamics between different modules. Once the structure is understood, we propose nonlinear energy control for these modules which supports feed-forward self-adaptation to ensure feasible interconnected system. Based on these technology agnostic structures it becomes possible to expand today’s Balancing Authorities (BA) to multi-layered interactive intelligent Balancing Authorities (iBAs) and to introduce protocols for flexible utilization of diverse technologies over broad ranges of temporal and spatial conditions. 

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2. Nano-sandwich composite by kinetic trapping assembly from protein and nucleic acid

   https://doi.org/10.1093/nar/gkab797  

   Chen, Shi; Xing, Li; Zhang, Douglas; Monferrer, Alba; Hermann, Thomas (September 2021, Nucleic Acids Research)

   Abstract Design and preparation of layered composite materials alternating between nucleic acids and proteins has been elusive due to limitations in occurrence and geometry of interaction sites in natural biomolecules. We report the design and kinetically controlled stepwise synthesis of a nano-sandwich composite by programmed noncovalent association of protein, DNA and RNA modules. A homo-tetramer protein core was introduced to control the self-assembly and precise positioning of two RNA–DNA hybrid nanotriangles in a co-parallel sandwich arrangement. Kinetically favored self-assembly of the circularly closed nanostructures at the protein was driven by the intrinsic fast folding ability of RNA corner modules which were added to precursor complex of DNA bound to the protein. The 3D architecture of this first synthetic protein–RNA–DNA complex was confirmed by fluorescence labeling and cryo-electron microscopy studies. The synthesis strategy for the nano-sandwich composite provides a general blueprint for controlled noncovalent assembly of complex supramolecular architectures from protein, DNA and RNA components, which expand the design repertoire for bottom-up preparation of layered biomaterials. 

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3. Implementing Support for Extensible Power Modeling in gem5

   Smith, Alex; Sinclair, Matthew D (June 2025, 6th gem5 Users Workshop)

   Power consumption has increasingly become a first-class design constraint to satisfy requirements for scientific workloads and other widely used workloads, such as machine learning. To meet performance and power requirements, system designers often use architectural simulators, such as gem5, to model component and system-level behavior. However, performance and power modeling tools are often isolated and do not make it accessible to integrate with one another for rapid performance and power system co-design. Although studies have previously explored power modeling with gem5 and validation on real hardware, there are several flaws with this approach. First, power models are sometimes not open source, making it difficult to apply them to different simulated systems. The current interface for implementing power models in gem5 also relies on hard-coded strings provided by the user to model dynamic and static power. This makes defining power models for components cumbersome and restrictive, as gem5’s MathExpr string formula parser has support for limited mathematical operations. Third, previous works only implement one form of power model for one component. This unnecessarily limits users from combining other power models, which may model certain system components with higher accuracy. Instead, we posit that decoupling how power models are integrated with simulators from the design of power models themselves will enable better power modeling in simulators. Accordingly, we extend our prior work on designing and implementing an extensible, generalizable power modeling interface by integrating support for McPAT into it and validating it emits correct power values. 

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4. Block copolymer derived 3-D interpenetrating multifunctional gyroidal nanohybrids for electrical energy storage

   https://doi.org/10.1039/C7EE03571C  

   Werner, J. G.; Rodríguez-Calero, G. G.; Abruña, H. D.; Wiesner, U. (January 2018, Energy & Environmental Science)

   Electrical energy storage systems such as batteries would benefit enormously from integrating all device components in three-dimensional (3-D) architectures on the nanoscale to improve their power capability without negatively impacting the device-scale energy density. However, the lack of large scale synthesis methods of 3-D architectures with precise spatial control of multiple, functional energy materials at the nanoscale remains a key issue holding back the development of such intricate device designs. To achieve fully integrated, multi-material nano-3-D architectures, next-generation nanofabrication requires departure from the traditional top-down patterning methods. Here, we present an approach to such systems based on the bottom-up synthesis of co-continuous nanohybrids with all necessary functional battery components rationally integrated in a triblock terpolymer derived core–shell double gyroid architecture. In our design three-dimensional periodically ordered, functional anode and cathode nanonetworks are separated by an ultrathin electrolyte phase within a single 3-D nanostructure. All materials are less than 20 nm in their layer dimensions, co-continuous and interpenetrating in 3-D, and extended throughout a macroscopic monolith. The electrochemical analysis of our solid-state nano-3-D Li-ion/sulfur system demonstrated battery-like characteristics with stable open circuit voltage, reversible discharge voltage and capacity, and orders of magnitude decreases in footprint area compared to two-dimensional thin layer designs. 

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5. Learning Control for Voltage and Frequency Regulation of an Infinite Bus System

   https://doi.org/10.1109/ICSTCC50638.2020.9259638  

   Duffaut Espinosa, Luis A.; Gray, W. Steven; Venkatesh, G. S. (October 2020, Proc. 24st International Conference on System Theory, Control and Computing)

   null (Ed.)

   A new learning methodology in terms of a discretization of a so-called Chen-Fliess series of a control affine nonlinear system was recently proposed, in part, for the purpose of systematically including system structure and expert knowledge into control strategies. The main objective of this paper is to appropriately embed this learning unit as a supporting predictive controller for power dynamical systems. In particular, an infinite bus system is used for the prototype design of a smart and active control policy to regulate voltage and frequency. It is demonstrated by simulation how a controller employing a Chen-Fliess learning unit can recover from a fault and address modeling mismatch. 

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