Tailored Charge Transfer Kinetics in Precursors for Organic Radical Batteries: A Joint Synthetic-Theoretical Approach

The development of sustainable energy storage devices is crucial for the transformation of our energy management. In this scope, organic batteries attracted considerable attention. To overcome the shortcomings of typically applied materials from the classes of redox-active conjugated polymers (i. e., unstable cell voltages) and soft matter-embedded stable organic radicals (i. e., low conductivity), a novel design concept was introduced, integrating such stable radicals within a conductive polymer backbone. In the present theory-driven design approach, redox-active (2,2,6,6-tetramethylpiperidin-1-yl)oxyls (TEMPOs) were incorporated in thiophene-based polymer model systems, while structure-property relationships governing the thermodynamic properties as well as the charge transfer kinetics underlying the charging and discharging processes were investigated in a systematical approach. Thereby, the impact of the substitution pattern, the length as well as the nature of the chemical linker, and the ratio of TEMPO and thiophene units was studied using state-of-the-art quantum chemical and quantum dynamical simulations for a set of six molecular model systems. Finally, two promising candidates were synthesized and electrochemically characterized, paving the way to applications in the frame of novel organic radical batteries.

Decision trees within a molecular memristor

Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues^1-3. The physical complexity is far beyond existing circuit fabrication technologies: moreover, the network in a brain is dynamically reconfigurable, which provides flexibility and adaptability to changing environments^4-6. In contrast, state-of-the-art semiconductor logic circuits are based on threshold switches that are hard-wired to perform predefined logic functions. To advance the performance of logic circuits, we are re-imagining fundamental electronic circuit elements by expressing complex logic in nanometre-scale material properties. Here we use voltage-driven conditional logic interconnectivity among five distinct molecular redox states of a metal-organic complex to embed a 'thicket' of decision trees (composed of multiple if-then-else conditional statements) having 71 nodes within a single memristor. The resultant current-voltage characteristic of this molecular memristor (a 'memory resistor', a globally passive resistive-switch circuit element that axiomatically complements the set of capacitor, inductor and resistor) exhibits eight recurrent and history-dependent non-volatile switching transitions between two conductance levels in a single sweep cycle. The identity of each molecular redox state was determined with in situ Raman spectroscopy and confirmed by quantum chemical calculations, revealing the electron transport mechanism. Using simple circuits of only these elements, we experimentally demonstrate dynamically reconfigurable, commutative and non-commutative stateful logic in multivariable decision trees that execute in a single time step and can, for example, be applied as local intelligence in edge computing^7-9.

Efficient evaluation of Coulomb interactions in kinetic Monte Carlo simulations of charge transport

The application of predictive and reliable modeling techniques for the simulation of charge transport in functional materials is an essential step for the development of advanced platforms for electronics, optoelectronics, and photovoltaics. In this context, kinetic Monte Carlo (KMC) methods have emerged as a valuable tool, especially for the simulation of systems where charge transport can be described by the hopping of charge carriers across localized quantum states, as, for example, in organic semiconductor materials. The accuracy, computational efficiency, and reliability of KMC simulations of charge transport, however, crucially depend on the methods and approximations used to evaluate electrostatic interactions arising from the distribution of charges in the system. The long-range nature of Coulomb interactions and the need to simulate large model systems to capture the details of charge transport phenomena in complex devices lead, typically, to a computational bottleneck, which hampers the application of KMC methods. Here, we propose and assess computational schemes for the evaluation of electrostatic interactions in KMC simulations of charge transport based on the locality of the charge redistribution in the hopping regime. The methods outlined in this work provide an overall accuracy that outperforms typical approaches for the evaluation of electrostatic interactions in KMC simulations at a fraction of the computational cost. In addition, the computational schemes proposed allow a spatial decomposition of the evaluation of Coulomb interactions, leading to an essentially linear scaling of the computational load with the size of the system.