Research Progress on the Mechanism of Carrier Rate Enhancement

in Organic Semiconductors

Tingyu Wei

School of Materials Science and Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China

Keywords: Organic Semiconductors, Carrier Migration Rate, Device Performance.

Abstract: Organic semiconductors are one of the key research topics nowadays. The researchers conducted an in-depth

exploration of it from multiple aspects, such as materials, performance improvement, and device structure

optimization. In recent years, the topic of increasing carrier migration rate, which is related to semiconductor

performance, has attracted much attention due to its profound academic and application value. This review

summarizes the charge transfer methods, with a focus on several widely applied enhancement strategies such

as traditional doping and molecular optimization strategies. While focusing on the strategies for enhancing

the carrier migration rate, the application drawbacks of each strategy were also summarized, such as the

inherent defects of the dopants themselves and the complexity of the molecular optimization strategies in

practical operations. In addition, special attention has been paid to the latest research achievements in

optimizing the charge transport performance of semiconductors by applying machine learning at present,

closely integrating the research topic with The Times. Finally, this review looks forward to future research on

carrier transport in organic materials, hoping to provide a reference for the design optimization of

semiconductors in the future.

1 INTRODUCTION

Organic semiconductors, as an emerging material,

have been widely applied in multiple fields such as

optoelectronic devices and electronic devices since

their discovery. It is of inorganic semiconductors

have lower cost and better flexible structure design

can be higher. However, while organic

semiconductors are constantly being developed and

applied, their relatively low electrical conductivity

has restricted their development. Therefore, the

research on enhancing the electrical conductivity of

organic semiconductors has attracted widespread

attention. The carrier migration rate in organic

semiconductors is closely related to their electrical

conductivity. Traditional methods for increasing the

carrier migration rate include, but are not limited to,

doping materials and optimizing the molecular

arrangement of organic semiconductors. With the

continuous development of machine learning,

existing studies have applied machine learning to the

improvement of carrier rates in organic

semiconductors.

https://orcid.org/0009-0009-0022-7356

Based on the existing traditional methods for

enhancing the carrier migration rate of organic

semiconductors, this paper reviews several valuable

strategies for improving the carrier migration rate,

including doping organic semiconductors, optimizing

the molecular arrangement of organic

semiconductors, and predicting the carrier migration

rate of organic semiconductors through machine

learning. It aims to guide future research.

2 DOPING

Doping refers to the introduction of impurity atoms

or molecules into organic semiconductors. By

altering their energy band structure and increasing the

concentration of charge carriers, the electrical

conductivity and photoelectric properties of the

material can be enhanced, thereby improving the

carrier migration rate.

Wei, T.

Research Progress on the Mechanism of Carrier Rate Enhancement in Organic Semiconductors.

DOI: 10.5220/0013828200004708

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy (IAMPA 2025), pages 493-497

ISBN: 978-989-758-774-0

493

2.1 Traditional Doping

Traditionally, doping is mainly divided into n-type

and p-type doping.

N-type organic semiconductor doping refers to

the introduction of impurity atoms or molecules that

can provide free electrons into organic semiconductor

materials, thereby increasing the concentration of free

electrons in the materials and enhancing their

electrical conductivity and electron mobility. Based

on this principle, researchers have been constantly

exploring how to improve the doping efficiency to

further enhance the material performance. Ye (2023)

found in his research on the design and synthesis of

n-type organic semiconductors that enhancing the

doping efficiency between dopants and polymers

could effectively increase the electrical conductivity

of organic thermoelectric materials. The N2200 series

of polymers synthesized based on his strategy saw a

significant increase in electrical conductivity under

N-type doping.

Recently, Zhao et al. (2024) proposed an n-type

doping method based on cation exchange. The

research found that by selecting the appropriate

dopant and ionic liquid, both high doping efficiency

and high cation exchange efficiency can be achieved

simultaneously, and a high doping level can be

obtained, thereby significantly improving the

electrical conductivity of electronic devices. The

research results show that the cation exchange doping

method leads to a significant increase in the electrical

conductivity of the samples, and the highest achieved

electrical conductivity is 0.01 S cm

−

. This confirms

that this method has great potential. At the same time,

because it is somewhat difficult to select the

appropriate dopant and ionic liquid, this method also

poses certain challenges in practical operation.

P-type organic semiconductor doping refers to the

introduction of impurity atoms or molecules capable

of accepting electrons into organic semiconductor

materials, thereby generating holes in the materials,

increasing the hole concentration, and enhancing their

electrical conductivity and hole mobility. By

comparing the electrical properties of the device

before and after P-type doping, Shan (2023) found

that after epitaxy of the F6TCNNQ small molecule on

the surface of the DNTT single crystal device, the

shift rate increased by nearly double. Ye (2023),

while researching to enhance the doping efficiency of

N-type semiconductors, found that improving the

doping efficiency could also significantly increase the

electrical conductivity of P-type doped PDPPT series

polymers. It has been confirmed that doping of P-type

organic semiconductors can effectively increase the

carrier migration rate.

2.2 Contact Doping

When a semiconductor comes into contact with a

metal, a potential barrier layer is often formed.

However, when the doping concentration of the

semiconductor is very high, electrons can pass

through the potential barrier through the tunneling

effect, thereby forming a low-resistance ohmic

contact, which facilitates the transport of charges.

Contact doping is an effective way to form ohmic

contacts in organic semiconductor devices.

Zhu (2022), when applying contact doping to

solve the problem of non-operation of polymer

transistors with coplanar structures, deposited

molybdenum trioxide as a doping layer at the contact

interface between the metal electrode and the

semiconductor layer. The research found that the

contact doping improved the overall charge transport

of the device, thus enabling the device to start

working. It can be seen that contact doping is

effective in improving the carrier transport of organic

semiconductors.

2.3 Photocatalytic Doping

Chemical doping is an effective method to improve

the carrier migration rate of organic semiconductors.

Compared with the dopants relied on in other

chemical doping, the significant selectivity and

efficiency of photocatalysts in promoting REDOX

reactions have attracted widespread attention. Jin et

al. (2024), based on the room-temperature treated

solution and by adjusting the light dose to control the

doping level, investigated the N-type doping and p-

type doping in photocatalysis, as well as the

simultaneous n-doping and p-doping, respectively.

The experimental results show that the photocatalytic

P-type doping of PBTTT increases its electrical

conductivity from 10

- 5

S cm

-1

to more than 700 S cm-

1. The photocatalytic n-type doping of BBL makes its

electrical conductivity lower than 10

-5

S cm

-1

before

doping, and increases to nearly 1S cm

-1

after two

minutes of illumination. When N-type doping and p-

type doping are carried out simultaneously, the

conductivity of p (g42T-T) in photocatalytic p-type

doping reaches 200 S cm

-1

, and the conductivity of

BBL in photocatalytic N-type doping reaches 0.1 S

-1

. A series of research results have confirmed that

photocatalytic doping can simply and effectively

increase the carrier migration rate of organic

semiconductors in three cases. This method is fully

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feasible for the performance optimization of organic

semiconductors. This section must be in two columns.

3 MOLECULAR OPTIMIZATION

STRATEGY

3.1 Enhance π-π Stacking

Enhancing the intermolecular π-π packing can

improve the planarity of molecules, optimize the

arrangement of molecules within organic

semiconductors, and thereby increase the carrier

migration rate of organic semiconductors. The

principle is that π-π stacking causes the electron

clouds between molecules to overlap each other,

thereby enhancing the electron coupling between

molecules and improving the carrier transport

efficiency between molecules.

Wang (2022) from Nanchang University

constructed two polymers with dicyanobenztriazole

as the receptor in the experiment. The study found

that the polymer with a stronger π-π packing had a

higher carrier migration rate. In the subsequent

research, three halogen-free ternary donor polymers

based on dicyanobenzotriazole were designed, which

have a more ordered arrangement, stronger π-π

stacking, and also have better charge transport

performance. It is evident that the π-π packing

between molecules is closely related to the carrier

migration.

In addition, there are photoelectric performance

test experiments based on triperylene monoimide

spiralane molecular films. The results show that the

π-π stacking of TNP-6CN films is stronger. The

maximum electron mobility of the thin-film device,

1.0×10-3cm

-1

, has a better carrier transport

capacity than the maximum hole mobility of the TNP-

BF thin-film device, which is 5.2×10

-4

-1

(Zhou, 2023). Both of the above experiments show

that the tight π-π packing between molecules can

effectively improve the carrier migration rate of

organic semiconductors.

3.2 High-Speed Spin Coating and

High-Temperature Annealing

When dealing with materials, such as single-layer

films formed by organic semiconductor materials, the

annealing temperature of the film and the spin coating

speed are two crucial conditions. When conducting

related research, Liu et al. (2024) found that the two

external processing conditions, annealing

temperature and spin coating speed, like the

molecular structure, can directly affect the orientation

of specific molecules in the film: Under the

conditions of high-temperature annealing and high-

speed spin-coating, specific molecules in the film

have enhanced lateral orientation. This led to an

increase in the carrier migration rate of TCDADI-C16

from 0.01 cm

-1

to 0.05 cm

-1

and that of

TCDADI-C24 from 0.13 cm

-1

to 0.20 cm

-1

Dai (2023) found in the study of DPT-TT that as the

annealing temperature gradually increased to 150℃,

the carrier migration rate of the device gradually

increased. This is also evidence that high-temperature

annealing can effectively increase the rate of charge

migration.

Unlike directly manipulating the internal structure

of molecules, controlling the annealing temperature

and spin coating speed to change the molecular

orientation based on the external processing

conditions of the material, thereby enhancing the

carrier migration rate of organic semiconductors, is

more operable.

3.3 Side Chain Engineering

Introducing long alkyl chains into polymers can

increase their solubility, but intermolecular packing

often decreases. The effect of introducing short alkyl

chains is exactly the opposite. Although it will reduce

the solubility, it will effectively increase the

molecular packing, thereby enhancing the carrier

migration rate. Side chain engineering is precisely a

good method to improve the performance of organic

semiconductors by altering the molecular structure by

introducing side chains of different groups into the

main chain of organic material molecules, either by

changing their molecular packing structure to

enhance charge transport or by optimizing their

energy level structure to increase the carrier migration

rate.

Introducing hydrogen bond interactions is a

beneficial strategy for sidechain engineering. Chen et

al. (2023) synthesized three thiazole side group DPP

polymers and confirmed that two of the polymers

with hydrogen bond interactions had better

aggregation than those without hydrogen bond

interactions, thereby having higher carrier migration

rates.

Zhao et al. (2025) from Fudan University obtained

three derivatives by substituting branched alkyl or

alkoxyl groups on the molecules of the y series non-

fullerene acceptor materials. After analyzing and

comparing the single crystal structures, it was found

that after optimizing the crystal packing through side

Research Progress on the Mechanism of Carrier Rate Enhancement in Organic Semiconductors

495

chain engineering, the derivatives were more likely to

transfer charges along the π-π direction due to the

enhanced π-π packing interaction. Thus, it has a

higher carrier migration rate. It once again confirms

the feasibility of sidechain engineering as an effective

method to increase the carrier migration rate of

organic semiconductors.

4 MACHINE LEARNING

PREDICTS THE MIGRATION

RATE OF ORGANIC

SEMICONDUCTORS

The carrier migration rate of organic semiconductors

is mainly affected by the molecular packing structure

and the charge transfer integral. Machine learning can

quickly predict key parameters through modeling.

Continuous training and verification of the model can

achieve high-speed and accurate prediction of the

carrier migration rate.

Johnson et al. (2024) proposed in 2024 to utilize

machine learning to predict organic materials with the

desired crystallization form through the thermal

properties of organic molecules. In its experiment,

ML was successfully applied to identify six organic

molecules, confirming the feasibility of applying

machine learning to the prediction of the thermal

properties of organic semiconductors. Because the

carrier migration rate of crystalline organic

semiconductors is higher than that of amorphous

organic semiconductors, the organic molecules with

crystalline transformation identified through the ML

algorithm in this study not only have excellent

thermal properties of high melting point and

crystallization driving force, but also have a higher

carrier migration rate when applied to

semiconductors. It is strong evidence that machine

learning can be applied to the improvement of carrier

migration rate in organic semiconductors.

Meanwhile, starting from the intrinsic disorder of

organic semiconductors, Padula et al. (2025) derived

a deep learning combined model based on quantum

mechanics and provided a dynamic Monte Carlo

prediction for the carrier migration rate using two

strategies for evaluating dynamic disorder. It has been

confirmed that machine learning can be applied to

effectively eliminate the phenomenon of charge

carrier localization hindering transport caused by the

intrinsic disordered action of organic materials.

The research on high carrier migration rates using

machine learning methods is still ongoing. When

studying the carrier mobility of organic

semiconductors, obtaining the transfer integral of all

molecular pairs of organic materials is an

indispensable prerequisite step. The team led by

Wang (2023) from Tsinghua University has

developed a machine learning model based on

artificial neural networks to accelerate and predict the

transfer integrals of organic semiconductors. This

model has effectively predicted the transfer integrals

of four typical organic semiconductor molecules in

experiments and can be used to explore the

relationship between the carrier migration rate of

organic semiconductors and temperature. After future

improvement, it can also be applied to the study of

static disordered organic thin film charge transport.

Moreover, when the obtained mobility and the

mobility calculated through density functional theory

are almost the same in terms of anisotropy and

absolute magnitude, the time required for the model's

prediction is only one millionth of that required for

the calculation. It has been verified that the machine

learning method has great application value in

exploring the improvement of the carrier migration

rate.

5 CONCLUSION

This review focuses on the research of the mechanism

for improving the carrier migration rate of organic

semiconductors. It reviews and summarizes two

widely used strategies for improving the performance

of organic semiconductor devices at present, namely,

doping and molecular optimization strategies. By

emphasizing the analysis of their advantages and

outlining their disadvantages, it is convenient for

readers to understand the current research status of

the carrier rate of organic semiconductors.

Meanwhile, it summarizes the new method of

applying machine learning methods to predict carrier

migration, which is in line with The Times. This is

conducive to people studying the improvement of

career migration rate while exploring the potential of

this field, and flexibly combining and applying new

technologies and methods in the era of artificial

intelligence, while improving the existing traditional

methods. Against the backdrop of the rapid

development of information technology, research in

the field of organic semiconductors has continuously

stimulated cutting-edge exploration and innovation.

Research in this field will continuously promote the

in-depth integration and development of materials

science with other disciplines, injecting vitality into

the development of The Times. It is believed that the

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research perspective on carrier migration in organic

semiconductor devices will be broad in the future.

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