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At least 1,441 records · Page 80

Robust chain aggregation of low-entropy rigid ladder polymers in solution

Conjugated polymers have been widely investigated where ladder-type conjugated polymers receive more attention due to their rigid backbones and extraordinary properties. However, the understanding of how the rigid conformation of ladder polymers translates to material properties is still limited. Here, we systematically investigated the solution aggregation properties of a carbazole-derived conjugated ladder polymer (LP) and its analogous non-ladder control polymer (CP) via light scattering, neutron scattering, and UV-vis absorption spectroscopy characterization techniques, revealing a highly robust, temperature-insensitive aggregation behavior of the LP. The experimental findings were further validated by computational molecular dynamics simulations. Here we found that the peak positions and intensities of the UV spectra of the LP remained constant between 20 °C and 120 °C in chlorobenzene solution. The polymer also showed a stable hydrodynamic radius measured by dynamic light scattering from 20 °C to 70 °C in the chlorobenzene solution. Using small-angle neutron scattering, no Guinier region was reached in the measured q range down to 0.008 Å –1 , even at elevated temperature. In contrast, the non-ladder control polymer CP was fully soluble in the chlorobenzene solvent without the observation of any notable aggregates. The Brownian dynamics simulation showed that during polymer aggregation, the entropy change of the LP was significantly less negative than that of the non-ladder control polymer. These findings revealed the low entropy nature of rigid conjugated ladder polymers and the low entropy penalty for their aggregation, which is promising for highly robust intermolecular interactions at high temperatures. Such a unique thermodynamic feature of rigid ladder polymers can be leveraged in the design and application of next-generation electronic and optoelectronic devices that function under unconventional high temperature conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental and theoretical study of energy transfer in a chromophore triad: What makes modeling dynamics successful?

Simulation of electronic dynamics in realistically large molecular systems is a demanding task that has not yet achieved the same level of quantitative prediction already realized for its static counterpart. This is particularly true for processes occurring beyond the Born–Oppenheimer regime. Non-adiabatic molecular dynamics (NAMD) simulations suffer from two convoluted sources of error: numerical algorithms for dynamics and electronic structure calculations. While the former has gained increasing attention, particularly addressing the validity of ad hoc methodologies, the effect of the latter remains relatively unexplored. Indeed, the required accuracy for electronic structure calculations to reach quantitative agreement with experiment in dynamics may be even more strict than that required for static simulations. In this study, we address this issue by modeling the electronic energy transfer in a donor–acceptor–donor (D–A–D) molecular light harvesting system using fewest switches surface hopping NAMD simulations. In the studied system, time-resolved experimental measurements deliver complete information on spectra and energy transfer rates. Subsequent modeling shows that the calculated electronic transition energies are “sufficiently good” to reproduce experimental spectra but produce over an order of magnitude error in simulated dynamical rates. We further perform simulations using artificially shifted energy gaps to investigate the complex relationship between transition energies and modeled dynamics to understand factors affecting non-radiative relaxation and energy transfer rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A molecular dynamics study of the effect of thermal boundary conductance on thermal transport of ideal crystal of n-alkanes with different number of carbon atoms

Phase change materials such as n-alkanes that exhibit desirable characteristics such as high latent heat, chemical stability, and negligible supercooling are widely used in thermal energy storage applications. However, n-alkanes have the drawback of low thermal conductivity values. The low thermal conductivity of n-alkanes is linked to formation of randomly oriented nano-domains of molecules in their solid structure that is responsible for excessive phonon scattering at the grain boundaries. Thus, understanding the thermal boundary conductance at the grain boundaries can be crucial for improving the effectiveness of thermal storage systems. The concept of the ideal crystal is proposed in this paper, which describes a simplified model such that all the nano-domains of long-chain n-alkanes are artificially aligned perfectly in one direction. In order to study thermal transport of the ideal crystal of long-chain n-alkanes, four (4) systems (C{sub 20}H{sub 42}, C{sub 24}H{sub 50}, C{sub 26}H{sub 54}, and C{sub 30}H{sub 62}) are investigated by the molecular dynamics simulations. Thermal boundary conductance between the layers of ideal crystals is determined using both non-equilibrium molecular dynamics (NEMD) and equilibrium molecular dynamics (EMD) simulations. Both NEMD and EMD simulations exhibit no significant change in thermal conductance with the molecular length. However, the values obtained from the EMD simulations are less than the values from NEMD simulations with the ratio being nearly three (3) in most cases. This difference is due to the nature of EMD simulations where all the phonons are assumed to be in equilibrium at the interface. Thermal conductivity of the n-alkanes in three structures including liquid, solid, and ideal crystal is investigated utilizing NEMD simulations. Our results exhibit a very slight rise in thermal conductivity values as the number of carbon atoms of the chain increases. The key understanding is that thermal transport can be significantly altered by how the molecules and the nano-domains are oriented in the structure rather than by the length of the n-alkane molecules.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

QuDPy: A Python-based tool for computing ultrafast non-linear optical responses

Nonlinear Optical Spectroscopy is a well-developed field with theoretical and experimental advances that have benefited multiple disciplines, including chemistry, biology, and physics. However, for the accurate interpretation of the corresponding multi-dimensional spectra, there is a need for precise quantum dynamical simulations based on model Hamiltonians. In this article, we present the initial release of our code, QuDPy (Quantum Dynamics in Python), which provides a robust numerical platform for performing quantum dynamics simulations based on model systems, including open quantum systems. Furthermore, a distinguishing feature of our approach is the ability to specify various high-order optical response pathways in the form of double-sided Feynman diagrams through a straightforward input syntax. This syntax outlines the time-ordering of ket-sided or bra-sided optical interactions acting on the time-evolving density matrix of the system. We utilize the quantum dynamics capabilities of QuTip to simulate the spectral response of complex systems, allowing us to compute virtually any $n$-th order optical response of the model system. To illustrate the utility of our approach, we provide a series of example calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

Here, one of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputed potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born–Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3–8 channels and circuit depths < 1000.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Collective dynamics in atomistic models with coupled translational and spin degrees of freedom

When using an atomistic model that simultaneously treats the dynamics of translational and spin degrees of freedom, we perform combined molecular and spin dynamics simulations to investigate the mutual influence of the phonons and magnons on their respective frequency spectra and lifetimes in ferromagnetic bcc iron. Furthermore, by calculating the Fourier transforms of the space- and time-displaced correlation functions, the characteristic frequencies and the linewidths of the vibrational and magnetic excitation modes were determined. A comparison of the results with that of the stand-alone molecular dynamics and spin dynamics simulations reveals that the dynamic interplay between the phonons and magnons leads to a shift in the respective frequency spectra and a decrease in the lifetimes. Moreover, in the presence of lattice vibrations, additional longitudinal magnetic excitations were observed with the same frequencies as the longitudinal phonons.

74 ATOMIC AND MOLECULAR PHYSICS↗

A streamlined approach to characterize microalgae strains for biomass productivity under dynamic climate simulation conditions

Screening microalgae strains under static light and temperature flask conditions cannot directly quantify the biomass productivities of algae growing in the dynamically fluctuating light and temperature conditions of outdoor ponds. In this effort, we describe a testing pipeline that screens for productivity under climate simulated conditions. A validated, miniaturized Laboratory Environmental Algae Pond Simulator (mini-LEAPS) photobioreactor was used to determine optimal medium salinities and biomass productivities of cold-tolerant microalgae collected from Arctic, subarctic, Antarctic, and subalpine habitats. Strains characterized in this effort include: Chlorella antarctica UTEX1959, Chlorella sp. UTEXSNO69, Chloromonas rosae UTEXSNO11, Phaeodactylum tricornutum UTEX646, and Stichococcus minutus CCALA727. Observed productivities of the characterized strains ranged from 1.74 ± 0.25 to 8.18 ± 0.81 g m –2 day –1 (as ash-free dry weight). For each strain, a temperature tolerance profile was generated to identify the most appropriate season (s) for cultivation. The two most promising strains, Chlorella sp. UTEX SNO69 and P. tricornutum UTEX646, were tested alongside the DISCOVR winter benchmark strain Monoraphidium minutum 26B-AM in outdoor open ponds at the PNNL Algae Testbed (PAT) in Arizona. Further, under cold-season outdoor pond conditions, Chlorella sp. UTEXSNO69 achieved average areal biomass productivities of 8.21 ± 0.50 g m –2 day –1 , not significantly different from that of the benchmark strain (8.52 ± 0.43 g m –2 day –1 , p > 0.05). Under spring outdoor pond conditions, P. tricornutum UTEX646 achieved average areal biomass productivities 10.34 ± 0.27 g m –2 day –1 , not significantly different from that of the benchmark (10.07 ± 0.50 g m –2 day –1 ) under the tested conditions (p > 0.05). The streamlined pipeline was thus demonstrated to successfully characterize productive microalgae strains for outdoor deployment by weeding out algae strains that were not productive under the tested dynamic light and temperature conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗

Identifying the dominant interstitial complex in dilute GaAsN alloys

Significant composition-dependent incorporation of N into non-substitutional sites is often reported for dilute GaAsN alloys. To distinguish (N-N){sub As}, (N-As){sub As}, and (As{sub Ga}-N{sub As}) complexes, we compare Rutherford backscattering spectrometry and nuclear reaction analysis (NRA) spectra with Monte Carlo-Molecular Dynamics simulations along the [100], [110], and [111] directions. For the Monte Carlo simulation, we assume that (N-N){sub As} is aligned along the [111] direction, while (N-As){sub As} is aligned along the [010] direction. The measured channeling NRA spectra exhibit the highest (lowest) yield in the [111] ([100]) directions. Similar trends are observed for simulations of (N-As){sub As}, suggesting that (N-As){sub As} is the dominant interstitial complex in dilute GaAsN.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Crystal Structure and Conformational Dynamics of Pyrococcus furiosus Prolyl Oligopeptidase

Enzymes in the prolyl oligopeptidase family possess unique structures and substrate specificities that are important for their biological activity and for potential biocatalytic applications. In this work, the crystal structures of Pyrococcus furiosus (Pfu) prolyl oligopeptidase (POP) and the corresponding S477C mutant were determined to 1.9 and 2.2 Å resolution, respectively. The wild type enzyme crystallized in an open conformation, indicating that this state is readily accessible, and it contained bound chloride ions and a prolylproline ligand. These structures were used as starting points for molecular dynamics simulations of Pfu POP conformational dynamics. The simulations showed that large-scale domain opening and closing occurred spontaneously, providing facile substrate access to the active site. Movement of the loop containing the catalytically essential histidine into a conformation similar to those found in structures with fully formed catalytic triads also occurred. This movement was modulated by chloride binding, providing a rationale for experimentally observed activation of POP peptidase catalysis by chloride. Thus, the structures and simulations reported in this study, combined with existing biochemical data, provide a number of insights into POP catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-Temperature Charging Dynamics of the Ionic Liquid and Its Gating Effect on FeSe 0.5 Te 0.5 Superconducting Films

Ionic liquids (ILs) have been investigated extensively because of their unique ability to form the electric double layer (EDL), which induces high electrical field. For certain materials, low-temperature IL charging is needed to limit the electrochemical etching. Here, we report our investigation of the low-temperature charging dynamics in two widely used ILs—DEME-TF 2 N and C4mim-TF 2 N. Results show that the formation of the EDL at ~220 K requires several hours relative to milliseconds at room temperature, and an equivalent voltage V e is introduced as a measure of the EDL formation during the biasing process. Here, the experimental observation is supported by molecular dynamics simulation, which shows that the dynamics are logically a function of gate voltage, time, and temperature. To demonstrate the importance of understanding the charging dynamics, a 140 nm thick FeSe 0.5 Te 0.5 film was biased using the DEME IL, showing a tunable T c between 18 and 35 K. Notably, this is the first observation of the tunability of the T c in thick film FeSe 0.5 Te 0.5 superconductors.

2D materials↗

Coupling indoor airflow, HVAC, control and building envelope heat transfer in the Modelica Buildings library

Here, this paper describes a coupled dynamic simulation of an indoor environment with heating, ventilation, and air conditioning (HVAC) systems, controls and building envelope heat transfer. The coupled simulation can be used for the design and control of ventilation systems with stratified air distributions. Those systems are commonly used to reduce building energy consumption while improving the indoor environment quality. The indoor environment was simulated using the fast fluid dynamics (FFD) simulation programme. The building fabric heat transfer, HVAC and control system were modelled using the Modelica Buildings library. After presenting the concept, the mathematical algorithm and the implementation of the coupled simulation were introduced. The coupled FFD–Modelica simulation was then evaluated using three examples of room ventilation with complex flow distributions with and without feedback control. Lastly, further research and development needs were also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computational Investigation of the Interplay of Substrate Positioning and Reactivity in Catechol O-Methyltransferase

Catechol O-methyltransferase (COMT) is a SAM- and Mg 2+ -dependent methyltransferase that regulates neurotransmitters through methylation. Simulations and experiments have identified divergent catecholamine substrate orientations in the COMT active site: molecular dynamics simulations have favored a monodentate coordination of catecholate substrates to the active site Mg 2+ , and crystal structures instead preserve bidentate coordination along with short (2.65 Å) methyl donor-acceptor distances. We carry out longer dynamics (up to 350 ns) to quantify interconversion between bidentate and monodentate binding poses. We provide a systematic determination of the relative free energy of the monodentate and bidentate structures in order to identify whether structural differences alter the nature of the methyl transfer mechanism and source of enzymatic rate enhancement. We demonstrate that the bidentate and monodentate binding modes are close in energy but separated by a 7 kcal/mol free energy barrier. Analysis of interactions in the two binding modes reveals that the driving force for monodentate catecholate orientations in classical molecular dynamics simulations is derived from stronger electrostatic stabilization afforded by alternate Mg 2+ and surrounding ligands is permitted. SQM/MM free energy barriers for methyl transfer from bidentate and monodentate catecholate configurations are comparable at around 21–22 kcal/mol, in good agreement with experiment (18–19 kcal/mol). Overall, the work suggests that both binding poses are viable for methyl transfer, and accurate descriptions of charge transfer and electrostatics are needed to provide balanced relative barriers when multiple binding poses are accessible, for example in other transferases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated dynamic analysis simulation of space stations with controllable solar arrays (supplemental data and analyses)

Space station and solar array data and the analyses which were performed in support of the integrated dynamic analysis study. The analysis methods and the formulated digital simulation were developed. Control systems for space station altitude control and solar array orientation control include generic type control systems. These systems have been digitally coded and included in the simulation.

Heinrichs, J. A.↗

Iodine recombination in xenon solvent: Clusters in the gas to liquid-like state transition

Supercritical fluids (SCFs) have attracted significant attention as solvents for chemical reactions due to their unique properties, such as high diffusivity, low viscosity, and tunable solvation properties. These properties profoundly influence reaction kinetics and are often attributed to the formation of molecular clusters within SCFs. To study the effect of supercritical solvent on chemical reactivity and dynamics of reactions, one needs to understand the dynamics of clusters in supercritical fluid. Extensive experiments on the photodissociation and recombination of iodine in supercritical fluids served as a model system for understanding these effects. Experimental studies have been complemented by theoretical and computational investigations, which mostly employ Monte Carlo or empirical molecular dynamics simulations. However, computational studies using non-reactive force fields and ab initio approaches present challenges in capturing reactive processes at larger scales within supercritical fluids. Here, in this work, we developed the ReaxFF parameters by training against quantum mechanics data. ReaxFF reactive force field based molecular dynamics simulations were performed, studying the dynamics of a xenon solvent and cage effect at different thermodynamic conditions for the iodine recombination reaction. We show that the conditions near the critical point are the optimal conditions to study the cage effect. We show that the average lifetime of xenon clusters ranging between 5 and 11 ps is comparable to iodine geminate recombination. Our simulation results of iodine recombination in xenon solvent demonstrate the higher probability of iodine molecule formation in the presence of xenon clusters. Finally, we show that the supercritical condition exhibits the highest recombination rate for iodine atoms.

Cage effect↗