Conjugated polymers (CPs) enable a wide range of lightweight, lower cost, and flexible organic electronic devices, but a thorough understanding of relationships between molecular structure and dynamics and electronic performance is critical for improved device efficiencies and for new technologies. Molecular dynamics (MD) simulations offer in silico insight into this relationship, but their accuracy relies on the approach used to develop the model's parameters or force field (FF). In this Perspective, we first review current FFs for CPs and find that most of the models implement an arduous reparameterization of inter-ring torsion potentials and partial charges of classical FFs. However, there are few FFs outside of simple CP molecules, e.g., polythiophenes, that have been developed over the last two decades. There is also limited reparameterization of other parameters, such as nonbonded Lennard-Jones interactions, which we find to be directly influenced by conjugation in these materials. We further provide a discussion on experimental validation of MD FFs, with emphasis on neutron and X-ray scattering. We define multiple ways in which various scattering methods can be directly compared to results of MD simulations, providing a powerful experimental validation metric of local structure and dynamics at relevant length and time scales to charge transport mechanisms in CPs. Finally, we offer a perspective on the use of neutron scattering with machine learning to enable high-throughput parametrization of accurate and experimentally validated CP FFs enabled not only by the ongoing advancements in computational chemistry, data science, and high-performance computing but also using oligomers as proxies for longer polymer chains during FF development.
In
this work, contrast-variation small-angle and ultra-small-angle
neutron scattering are used together with wide-angle X-ray scattering
(WAXS) to characterize the bulk molecular conformation and self-assembly
of polythiophene-based conjugated polymers (CPs) in bulk blends with
deuterated polystyrene (PS-d
8) as the
matrix component. A significant and sharp transition from small to
large globular domains is observed in the phase-separated morphology
of all blends as a function of CP concentration. Evidence of self-assembly
into nanofiber networks is also observed in regio-regular poly(3-hexylthiophene)
(RRe-P3HT) blends and found to be promoted by the use of solvents
of moderate quality (i.e., toluene) during the film formation process
and by higher CP loadings when using solvents of good quality (i.e.,
chloroform). Finally, WAXS and conductivity measurements demonstrate
a strong correlation between the degree of crystallinity of the CP
in the π-stacking direction (nanofiber formation) and the electronic
conductivity across the bulk of the film. In addition to RRe-P3HT,
PS-d
8 blends with semi-crystalline poly(3-dodecylthiophene)
(P3DDT) or poly(3,3‴-didodecyl[2,2′:5′,2″:5″,2‴-quaterthiophene]-5,5‴-diyl)
(PQT-12) and blends with amorphous regio-random poly(3-hexylthiophene)
(RRa-P3HT) were investigated over concentrations ranging from 0.1
to 50 wt % of CP. This work highlights the importance of understanding
the factors that influence the phase morphology in blends of CPs and
commodity polymers, as this directly alters charge transport pathways
and performance of the organic electronic devices that rely on these
materials.
This study assesses the required fidelities in modeling particle radiative properties and particle size distributions (PSDs) of combusting particles in Computational Fluid Dynamics (CFD) investigations of radiative heat transfer during oxy-combustion of coal and biomass blends. Simulations of air and oxy-combustion of coal/biomass blends in a 0.5 MW combustion test facility were carried out and compared against recent measurements of incident radiative fluxes. The prediction variations to the combusting particle radiative properties, particle swelling during devolatilization, scattering phase function, biomass devolatilization models, and the resolution (diameter intervals) employed in the fuel PSD were assessed. While the wall incident radiative flux predictions compared reasonably well with the experimental measurements, accounting for the variations in the fuel, char and ash radiative properties were deemed to be important as they strongly influenced the incident radiative fluxes and the temperature predictions in these strongly radiating flames. In addition, particle swelling and the diameter intervals also influenced the incident radiative fluxes primarily by impacting the particle extinction coefficients. This study highlights the necessity for careful selection of particle radiative property, and diameter interval parameters and the need for fuel fragmentation models to adequately predict the fly ash PSD in CFD simulations of coal/biomass combustion.
Conjugated polymer films, nanofibers, and networks can be ideal materials for the design of efficient photovoltaic devices, batteries, thermoelectric cells, light emitting diodes and many emerging technologies.[1] It is also recognized that the structure and dynamics of organic semiconductor materials correlates strongly with large changes in optical, electronic and mechanical properties so that their control and manipulation is essential to advancing the field. This presentation outlines the use of neutron scattering techniques in the development of structure-property relationships for conjugated polymer nano materials.[2] It also highlights recent results on the use of neutron and x-ray scattering techniques for the development of improved molecular simulation force fields and structural parameters specifically produced for conjugated polymers. Quasi-elastic neutron scattering (QENS) experiments are used along with computationally efficient MD simulations to understand the nature of important nanoscale motions. X-ray and polarized neutron diffraction are also used to correlate experimental and model-generated polymer structures. QENS validation of MD force fields presents a unique opportunity to increase the accuracy of highly uncertain parameters used in simulation of conjugated polymers such as partial charges and backbone torsion. These parameters are currently estimated from quantum mechanical calculations such as density functional theory but, unlike many force fields for small molecules, are not parameterized with available experimental data. High variability is observed in these parameters for the small number of force fields that have been proposed in the literature. A vision for the accelerated development of accurate force fields for these classes of materials is also proposed.
He teaches primarily computational-based courses and design courses. His teaching interests include the incorporation of computational tools in engineering education and an emphasis on statistics and scientific writing. His graduate research focused on the use of data science tools to improve the analysis of nanoparticle trajectory datasets for nanotherapeutic applications.
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