Resolving Donor–Acceptor Interfaces and Charge Carrier Energy Levels of Organic Semiconductors with Polar Side Chains

Abstract

Organic semiconductors consisting of molecules bearing polar side chains have been proposed as potential candidates to overcome the limitations of organic photovoltaics owing to their enhanced dielectric constant. However, introducing such polar molecules in photovoltaic devices has not yet resulted in higher efficiencies. A microscopic understanding of the impact of polar side chains on electronic and structural properties of organic semiconductors is paramount to rationalize their effect. Here, the impact of such side chains on bulk heterojunction overall morphology, molecular configurations at donor-acceptor (DA) interfaces, and charge carrier energy levels is investigated. The multiscale modeling approach used allows to resolve DA interfaces with atomistic resolution while taking into account the large-scale self-organization process which takes place during the processing of an organic thin film. The polar fullerene-based blends are compared to the well-studied reference system, poly(3-hexyl-thiophene) (P3HT):phenyl-C 61butyric acid methyl ester (PCBM). Introduction of polar side chains on a similar molecular scaffold does not affect molecular orientations at the DA interfaces; such orientations are, however, found to be affected by processing conditions and polymer molecular weight. Polar side chains, instead, are found to impact considerably the charge carrier energy levels of the organic blend, causing electrostatic-induced broadening of these levels.

The Martini Model in Materials Science

“…[ 182,183 ] It is possible to model the morphology of organic electronic materials with Martini, in particular to obtain and characterize morphologies, which are often composed of more than one organic semiconductor; [ 53,184–190 ] and to subsequently backmap [ 191 ] the obtained CG morphologies to atomistic resolution, a step often useful in order to perform fine‐grained calculations aimed at evaluating the electronic properties of such materials. [ 53,184,192–194 ] Martini models have been already developed for many prototypical organic semiconductors used in organic electronic devices, such as conjugated polymers, [ 53,114,195 ] small conjugated molecules, [ 184,185,196,197 ] and C 60 fullerene [ 67,68 ] and some of its derivatives. [ 53,185,193 ] Arguably one of the most popular subfields of organic electronics is organic photovoltaics.…”

“…[ 53,184,192–194 ] Martini models have been already developed for many prototypical organic semiconductors used in organic electronic devices, such as conjugated polymers, [ 53,114,195 ] small conjugated molecules, [ 184,185,196,197 ] and C 60 fullerene [ 67,68 ] and some of its derivatives. [ 53,185,193 ] Arguably one of the most popular subfields of organic electronics is organic photovoltaics. Systems such as P3HT:DiPBI, [ 184 ] P3HT:PCBM, [ 53,186–189,198 ] PBDB‐T:F‐ITIC, [ 190 ] and P3HT:PTEG‐1 [ 193 ] have already been simulated with Martini (DiPBI is diperylene bisimide, PCBM is phenyl‐C61‐butyric acid methyl ester, PTEG‐1 is triethyleneglycol‐2‐phenyl‐ N ‐methyl‐pyrrolidino[[3′,4′:1,2]][C60]fullerene, PBDB‐T is poly[(2,6‐(4,8‐bis(5‐(2‐ethylhexyl)thio‐phen‐2‐yl)‐benzo[1,2‐b:4,5‐b0]dithiophene))‐ alt ‐(5,5‐(10,30‐di‐2‐thienyl‐50,70‐bis(2‐ethylhexyl)benzo[10,20‐c:40,50‐c0]dithiophene‐4,8‐dione))], and F‐ITIC is ITIC‐F = fluorinated (2,2′‐[[6,6,12,12‐tetrakis(4‐hexylphenyl)‐6,12‐dihydrodithieno[2,3‐d:2′,3′‐d′]‐s‐indaceno[1,2‐b:5,6‐b′]dithiophene‐2,8‐diyl]‐bis‐[methylidyne(3‐oxo‐1H‐indene‐2,1(3H)‐diylidene)]]bis‐[propanedinitrile])).…”

“…[ 53,185,193 ] Arguably one of the most popular subfields of organic electronics is organic photovoltaics. Systems such as P3HT:DiPBI, [ 184 ] P3HT:PCBM, [ 53,186–189,198 ] PBDB‐T:F‐ITIC, [ 190 ] and P3HT:PTEG‐1 [ 193 ] have already been simulated with Martini (DiPBI is diperylene bisimide, PCBM is phenyl‐C61‐butyric acid methyl ester, PTEG‐1 is triethyleneglycol‐2‐phenyl‐ N ‐methyl‐pyrrolidino[[3′,4′:1,2]][C60]fullerene, PBDB‐T is poly[(2,6‐(4,8‐bis(5‐(2‐ethylhexyl)thio‐phen‐2‐yl)‐benzo[1,2‐b:4,5‐b0]dithiophene))‐ alt ‐(5,5‐(10,30‐di‐2‐thienyl‐50,70‐bis(2‐ethylhexyl)benzo[10,20‐c:40,50‐c0]dithiophene‐4,8‐dione))], and F‐ITIC is ITIC‐F = fluorinated (2,2′‐[[6,6,12,12‐tetrakis(4‐hexylphenyl)‐6,12‐dihydrodithieno[2,3‐d:2′,3′‐d′]‐s‐indaceno[1,2‐b:5,6‐b′]dithiophene‐2,8‐diyl]‐bis‐[methylidyne(3‐oxo‐1H‐indene‐2,1(3H)‐diylidene)]]bis‐[propanedinitrile])). Simulations of neat P3HT [ 192 ] have also been performed, while more organic semiconductor mixtures have been tested in the context of organic thermoelectric devices [ 185,196 ] and organic mixed ion–electron conductors (which will be described as part of the next section).…”

“…[ 53 ] Other Martini organic semiconductor thin films have been solution‐processed in silico. [ 186–189,193–195,198 ] In particular, Alessandri et al. studied the evolution of the morphology of P3HT:PCBM blends as a function of the molecular weight of P3HT, the solvent evaporation rate, and thermal annealing.…”

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

“…Numerous CG models have been developed during the past two decades, with different levels of coarsening and different mathematical representations. CG models have been successfully applied to study a large range of processes in biology (Yen et al, 2018;Bruininks et al, 2020;Lucendo et al, 2020) and materials science (Casalini et al, 2019;Alessandri et al, 2020;Li et al, 2020;Vazquez-Salazar et al, 2020). Applications such as structure-based drug design are particularly challenging for CG modeling because of the severe requirements: (1) high chemical specificity (i.e., allowing to distinguish most chemical groups); (2) capability to represent all possible components of the system (proteins, cofactors, nucleic acids, drug candidates, waters, lipids, etc.)…”