Computation of Oxidation Potentials of Solvated Nucleobases by Static and Dynamic Multilayer Approaches

The determination of the redox properties of nucleobases is of paramount importance to get insight into the charge-transfer processes in which they are involved, as those occurring in DNA-inspired biosensors. Although many theoretical and experimental studies have been conducted, the value of the one-electron oxidation potentials of nucleobases is not well defined. Moreover, the most appropriate theoretical protocol to model the redox properties has not been established yet. In this work, we have implemented and evaluated different static and dynamic approaches to compute the one-electron oxidation potentials of solvated nucleobases. In the static framework, two thermodynamic cycles have been tested to assess their accuracy against the direct determination of oxidation potentials from the adiabatic ionization energies. Then, the introduction of vibrational sampling, the effect of implicit and explicit solvation models, and the application of the Marcus theory have been analyzed through dynamic methods. The results revealed that the static direct determination provides more accurate results than thermodynamic cycles. Moreover, the effect of sampling has not shown to be relevant, and the results are improved within the dynamic framework when the Marcus theory is applied, especially in explicit solvent, with respect to the direct approach. Finally, the presence of different tautomers in water does not affect significantly the one-electron oxidation potentials.

Identifying optimal cycles in quantum thermal machines with reinforcement-learning

The optimal control of open quantum systems is a challenging task but has a key role in improving existing quantum information processing technologies. We introduce a general framework based on reinforcement learning to discover optimal thermodynamic cycles that maximize the power of out-of-equilibrium quantum heat engines and refrigerators. We apply our method, based on the soft actor-critic algorithm, to three systems: a benchmark two-level system heat engine, where we find the optimal known cycle; an experimentally realistic refrigerator based on a superconducting qubit that generates coherence, where we find a non-intuitive control sequence that outperforms previous cycles proposed in literature; a heat engine based on a quantum harmonic oscillator, where we find a cycle with an elaborate structure that outperforms the optimized Otto cycle. We then evaluate the corresponding efficiency at maximum power.

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations

Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.

Quantum alchemy beyond singlets: Bonding in diatomic molecules with hydrogen

Bonding energies are key for the relative stability of molecules in chemical space. Therefore methods employed to search for relevant molecules in chemical space need to capture the bonding behavior for a wide range of molecules, including radicals. In this work, we investigate the ability of quantum alchemy to do so for exploring hypothetical chemical compounds, here diatomic molecules involving hydrogen with various electronic structures. We evaluate equilibrium bond lengths, ionization ener- gies, and electron affinities of these fundamental systems. We compare and contrast how well manual quantum alchemy calculations, i.e. quantum mechanical calculations in which the nuclear charge is altered, and quantum alchemy approximations using a Taylor series expansion can predict these molecular properties. We also investigate the extent of error cancellation of these approaches in terms of ionization energies and electron affinities when using thermodynamic cycles. Our results suggest that the accuracy of Taylor series expansions are greatly improved by error cancellation in thermodynamic cycles, and errors also appear to be generally system-dependent. Taken together, this work provides insights into how quantum alchemy predictions us- ing a Taylor series expansion may be applied to future studies of non-singlet systems as well as which challenges remain open for these cases.

Evaluating quantum alchemy of atoms with thermodynamic cycles: Beyond ground electronic states

Due to the sheer size of chemical and materials space, high throughput computational screening thereof will require the development of new computational methods that are accurate, efficient, and transferable. These methods need to be applicable to electron configurations beyond ground states. To this end, we have systematically studied the applicability of quantum alchemy predictions using a Taylor series expansion on quantum mechanics (QM) calculations for single atoms with different electronic structures arising from different net charges and electron spin multiplicities. We first compare QM method accuracy to experimental quantities including first and second ionization energies, electron affinities, and multiplet spin energy gaps for a baseline understanding of QM reference data. We then investigate the intrinsic accuracy of an approach we call "manual" quantum alchemy schemes compared to the same QM reference data, which employ QM calculations where the basis set of a different element is used for an atom as the limit case of quantum alchemy. We then discuss the reliability of quantum alchemy based on Taylor series approximations at different orders of truncation. Overall, we find that the errors from finite basis set treatments in quantum alchemy are significantly reduced when thermodynamic cycles are employed, which points out a route to improve quantum alchemy in explorations of chemical space. This work establishes important technical aspects that impact the accuracy of quantum alchemy predictions using a Taylor series and provides a foundation for further quantum alchemy studies.

Class 2 Heating Cycles: A New Class of Thermodynamic Cycles

Considering the significance of thermodynamic cycles in the global energy system, it is necessary to develop new general classes of thermodynamic cycles to relieve current energy and environmental problems. Inspired by the relationship between power cycles and refrigeration cycles, we realize that general classes of thermodynamic cycles should occur in pairs with opposite functions. Here we reverse class 1 heating cycles to obtain another new general class of thermodynamic cycles named class 2 heating cycles (HC-2s). HC-2s have two basic forms, and each contains six thermodynamic processes. HC-2s present the simplest and most general approach to utilizing the temperature difference between a medium-temperature heat source and a low-temperature heat sink to achieve efficient high-temperature heating. HC-2s fill the gaps that have existed since the origin of thermal science, and they will play significant roles in the global sustainable energy system.

Class 1 Heating Cycles: A New Class of Thermodynamic Cycles

Thermodynamic cycles are not only the core concepts of thermal science, but also key approaches to energy conversion and utilization. So far, power cycles and refrigeration cycles have been the only two general classes of thermodynamic cycles. While diverse types of systems have been developed to perform thermodynamic cycles, no new general classes of thermodynamic cycles have been proposed. Based on the basic principles of thermodynamics, here we propose and analyze a new general class of thermodynamic cycles named class 1 heating cycles (HC-1s). Two basic forms of HC-1s are obtained by connecting six essential thermodynamic processes in the proper order and forming a thermodynamic cycle. HC-1s present the simplest and most general approach to utilizing the temperature difference between a high-temperature heat source and a medium-temperature heat sink to achieve efficient medium-temperature heating and/or low-temperature cooling. HC-1s fill the gaps that have existed since the origin of thermal science, and they will play significant roles in energy conservation and emission reduction.

Thermodynamic Analysis of Negative CO2 Emission Power Plant Using Aspen Plus, Aspen Hysys, and Ebsilon Software

The article presents results of thermodynamic analysis using a zero-dimensional mathematical models of a negative CO2 emission power plant. The developed cycle of a negative CO2 emission power plant allows the production of electricity using gasified sewage sludge as a main fuel. The negative emission can be achieved by the use this type of fuel which is already a “zero-emissive” energy source. Together with carbon capture installation, there is a possibility to decrease CO2 emission below the “zero” level. Developed models of a novel gas cycle which use selected codes allow the prediction of basic parameters of thermodynamic cycles such as output power, efficiency, combustion composition, exhaust temperature, etc. The paper presents results of thermodynamic analysis of two novel cycles, called PDF0 and PFD1, by using different thermodynamic codes. A comparison of results obtained by three different codes offered the chance to verify results because the experimental data are currently not available. The comparison of predictions between three different software in the literature is something new, according to studies made by authors. For gross efficiency (54.74%, 55.18%, and 52.00%), there is a similar relationship for turbine power output (155.9 kW, 157.19 kW, and 148.16 kW). Additionally, the chemical energy rate of the fuel is taken into account, which ultimately results in higher efficiencies for flue gases with increased steam production. A similar trend is assessed for increased CO2 in the flue gas. The developed precise models are particularly important for a carbon capture and storage (CCS) energy system, where relatively new devices mutually cooperate and their thermodynamic parameters affect those devices. Proposed software employs extended a gas–steam turbine cycle to determine the effect of cycle into environment. First of all, it should be stated that there is a slight influence of the software used on the results obtained, but the basic tendencies are the same, which makes it possible to analyze various types of thermodynamic cycles. Secondly, the possibility of a negative CO2 emission power plant and the positive environmental impact of the proposed solution has been demonstrated, which is also a novelty in the area of thermodynamic cycles.