Thermoelectric devices based on conducting polymers are promising energy conversion systems; however, the intrinsic semiconducting nature inherent to the macromolecular architecture of common conjugated polymers (CPs) in their neutral form requires doping to impart electrical conductivity and requires optimization of the complex dopant–polymer interactions in order to enhance thermoelectric performance. Therefore, designing and synthesizing CPs that have readily tunable properties and that can be doped in a facile manner using stable and noncorrosive dopants is a significant opportunity in the field. Here, we report the expedient synthesis of a donor–acceptor CP based on an alternating cyclopenta­dithiophene and thiadiazolo­quinoxaline framework that exhibits a narrow band gap, an open-shell electronic ground state, intrinsic electrical conductivity (σ ∼ 10–3 S cm–1), and a large Seebeck coefficient (S > 1000 μV K–1) in the absence of dopants. The addition of a tailored open-shell dopant significantly increases σ and allows for the systematic manipulation of the thermoelectric properties, resulting in an optimized power factor of >10 μW m–1 K–2, one of the largest values reported for nontraditional CP thermoelectric systems. This combination of a next-generation, radical-containing macromolecule with an open-shell small molecule dopant opens a new pathway by which to control charge transport and enable improved behavior in next-generation polymer thermoelectric systems.

Classical excitonic models are unsuitable for describing the electronic structure of polypeptides, and explicit consideration of water is essential.

We present an open-source software package, NIC-CAGE (Novel Implementation of Constrained Calculations for Automated Generation of Excitations), for predicting quantum optimal control fields in photo-excited chemical systems. Our approach utilizes newly derived analytic gradients for maximizing the transition probability (based on a norm-conserving Crank-Nicolson propagation scheme) for driving a system from a known initial quantum state to another desired state. The NIC-CAGE code is written in the MATLAB and Python programming environments to aid in its readability and general accessibility to both users and practitioners. Throughout this work, we provide several examples and outputs on a variety of different potentials, propagation times, and user-defined parameters to demonstrate the robustness of the NIC-CAGE software package. As such, the use of this predictive tool by both experimentalists and theorists could lead to further advances in both understanding and controlling the dynamics of photo-excited systems. File list (2)download file view on ChemRxiv Quantum_Optimal_Control.pdf (0.94 MiB) download file view on ChemRxiv Supplementary_Information.pdf (1.15 MiB)

We investigate the UV absorption spectra of a series of cationic GxG (where x denotes a guest residue) peptides in aqueous solution and find that the spectra of a subset of peptides with x = A, L, I, K, N, and R (and, to a lesser extent, peptides with x = D and V) vary as a function of temperature. To explore whether or not this observation reflects conformational dependencies, we carry out time-dependent density functional calculations for the polyproline II (pPII) and β-strand conformations of a limited set of tripeptides (x = A, V, I, L, and R) in implicit and explicit water. We find that the calculated CD spectra for pPII can qualitatively account for the experimental spectra irrespective of the water model. The reproduction of the β-strand UV-CD spectra, however, requires the explicit consideration of water. Based on the calculated absorption spectra, we explain the observed temperature dependence of the experimental spectra as being caused by a reduced dispersion (larger spectral density) of the overlapping NV 2 band and the influence of water on electronic transitions in the β-strand conformation. Contrary to conventional wisdom, we find that both the NV 1 and NV 2 band are the envelopes of contributions from multiple transitions that involve more than just the HOMOs and LUMOs of the peptide groups. A natural transition orbital analysis reveals that some of the transitions with significant oscillator strength have a charge-transfer character. The overall manifold of transitions, in conjunction with their strengths and characters, depends on the peptide's backbone conformation, peptide hydration, and also on the side chain of the guest residue. It is particularly noteworthy that molecular orbitals of water contribute significantly to transitions in β-strand conformations. Our results reveal that peptide groups, side chains, and hydration shells must be considered as an entity for a physically valid characterization of UV absorbance and circular dichroism. File list (2) download file view on ChemRxiv UV_CD_Absorption paper_final.pdf (4.17 MiB) download file view on ChemRxiv SI_UV_CD_Absorption_paper.pdf (11.34 MiB)

We present a detailed analysis of the linear polarizability (α) and second hyperpolarizability (γ) in a series of streptocyanines, as predicted with various range-separated functionals and CCSD(T)based methods. Contrary to previous work on these systems, we find that the lowest-energy electronic states for the larger streptocyanine oligomers are not closed-shell singlets, and improved accuracy can be obtained with certain DFT methods by allowing the system to relax to a lower-energy broken-symmetry solution. Our extensive analyses are complemented by new large-scale CCSD(T) and explicitly correlated CCSD(T)-F12 calculations that comprise the most complete and accurate benchmarks of α and γ for the streptocyanine systems to date. Taken together, our CCSD(T) and broken-symmetry DFT calculations (1) show that the MP2 benchmarks used in previous studies still exhibit significant errors (~25% for α and~100% for γ) and, therefore, the MP2 calculations should not be used as reliable benchmarks for polarizabilities or hyperpolarizabilities, and (2) emphasize the importance of testing for a lower-energy open-shell configuration when calculating nonlinear optical properties for these systems.

Inverse problems continue to garner immense interest in the physical sciences, particularly in the context of controlling desired phenomena in non-equilibrium systems. In this work, we utilize a series of...

No abstract

Metadynamics calculations of large chemical systems with ab initio methods are computationally prohibitive due to the extensive sampling required to simulate the large degrees of freedom in these systems. To address this computational bottleneck, we utilized a GPU-enhanced density functional tight binding (DFTB) approach on a massively parallelized cloud computing platform to efficiently calculate the thermodynamics and metadynamics of biochemical systems. To first validate our approach, we calculated the free-energy surfaces of alanine dipeptide and showed that our GPU-enhanced DFTB calculations qualitatively agree with computationally-intensive hybrid DFT benchmarks, whereas classical force fields give significant errors. Most importantly, we show that our GPU-accelerated DFTB calculations are significantly faster than previous approaches by up to two orders of magnitude. To further extend our GPU-enhanced DFTB approach, we also carried out a 10 ns metadynamics simulation of remdesivir, which is prohibitively out of reach for routine DFT-based metadynamics calculations. We find that the free-energy surfaces of remdesivir obtained from DFTB and classical force fields differ significantly, where the latter overestimates the internal energy contribution of high free-energy states. Taken together, our benchmark tests, analyses, and extensions to large biochemical systems highlight the use of GPU-enhanced DFTB simulations for efficiently predicting the free-energy surfaces/thermodynamics of large biochemical systems.