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Journal of Scientometric ResearchNOW IN
Article

The Frontier of Solar Energy: Quantum Dots and Density Functional Theory Insights

Iván Darío Arellano-Ramírez1,2★, Leonardo Bohorquez Santiago3, Arles Gil Rebaza4, Sebastián Amaya-Roncancio5, Elisabeth Restrepo-Parra6★ Corresponding author

  1. 1Grupo de Investigación en Modelado y Simulación Computacional, Departamento de Física, Universidad Tecnológica de Pereira, Risaralda, COLOMBIA.
  2. 2Laboratorio de Física del Plasma, Universidad Nacional de Colombia Sede Manizales, Manizales, COLOMBIA.
  3. 3Departamento de Física, Universidad Tecnológica de Pereira, Risaralda, COLOMBIA.
  4. 4Departamento de Física, Universidad Nacional de La Plata UNLP. Instituto de Física La Plata IFLP - CONICET, 1900 La Plata, ARGENTINA.
  5. 5Escuela de Física, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Boyacá, 150003, Tunja, Colombia
  6. 6Laboratorio de Física del Plasma, Universidad Nacional de Colombia Sede Manizales, Manizales, COLOMBIA.

CORRESPONDENCE

Iván Darío Arellano-Ramírez

PhD (c) in physics 1Grupo de Investigación en Modelado y Simulación Computacional, Departamento de Física, Universidad Tecnológica de Pereira, Risaralda, COLOMBIA. 2Laboratorio de Física del Plasma, Universidad Nacional de Colombia Sede Manizales, Manizales, COLOMBIA. Postal address: Cra 27#10-02 Barrio Alamos, Departamento de Física, Pereira 661003, COLOMBIA.

arellano@utp.edu.co

Received: 07-03-2025; Revised: 16-05-2025; Accepted: 24-07-2025.

Volume 14, Issue 2 · pp. 424–436 · PUBLISHED May-Aug 2025 · DOI: 10.5530/jscires.20251270

View on JSR original site ↗

ABSTRACT

Solar cells, a crucial renewable energy source in the fight against climate change, have gained prominence in the scientific community. Sunlight, an almost inexhaustible source of clean and renewable energy, positions solar cells as a fundamental alternative for future energy needs. However, improving their energy efficiency remains a major challenge. Quantum dots, nanocrystals with unique properties, have emerged as a promising solution due to their ability to harvest a wider range of light wavelengths. Despite challenges in producing these cells, computational simulation tools based on Density Functional Theory (DFT) offer a robust theoretical framework. These tools provide a low-cost way to elucidate the internal processes of energy conversion, thereby accelerating development. The existing literature on this topic is scarce and dispersed, underscoring the need for research to consolidate key contributions. This article employs scientometric techniques to identify seminal works and analyze the dynamics in the scientific production of quantum dot-based solar cells. The results reveal a surge in research activity, particularly in the last three years, highlighting the growing interest in this promising technology. Moreover, results show a 38.95% growth between 2012 and 2019, with an upward trend in scientific production. China and the United States of America lead academic production in this field. Three well-defined trends in the development of quantum dot-based solar cells are identified: Halide perovskites, dye-sensitized, and nanocrystals. These findings can assist researchers in gaining a better understanding of the current research landscape and trends in this field.

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INTRODUCTION

Solar energy has emerged as a promising alternative to traditional energy sources. Various methods exist for capturing this energy, but Quantum Dot-based Solar Cells (QDSCs) stand out for their high efficiency potential and growth expectations in the global market.[1] The integration of Quantum Dots (QDs) into photovoltaic devices has opened new horizons for increasing light absorption efficiency. Simulation tools based on Density Functional Theory have become an essential tool for comprehending and predicting the electronic properties of QDs at the atomic level.

QDs are semiconductor particles at the nanometer scale that can convert light energy into electrical energy with greater efficiency than other alternatives.[2] For example, QDs display a quantum confinement effect, which allows for the control of their optical and electronic properties by adjusting their size.[3] Additionally, they can produce multiple excitons from a single high-energy photon,[4] potentially resulting in solar cell efficiencies that exceed the Shockley-Queisser limit.[5] In addition, QDs have a significantly larger absorption cross-section than bulk material, allowing them to absorb more light. Moreover, QDs can be processed and synthesized in solution, enabling low-cost manufacturing techniques such as spin-coating.[6] Therefore, it is essential to conduct research on alternative energies, such as QDSCs, to reduce dependence on traditional energy sources.

Recently, theories have been developed to understand and improve the designs of QDSCs, such as DFT. The DFT enables the prediction of electronic structure, formation energies, magnetic, and optical properties of materials. This theory facilitates the calculation of energy band structures of semiconductor materials, providing insights into electronic and optical bandgaps. This process is essential for the optimal design of semiconductors with higher efficiencies for solar cells. Moreover, DFT predicts absorption and emission energy transitions, offering details on crystalline lattice defects.[7] Through DFT, it is possible to understand how these defects affect the electronic charge density, impacting the recombination of charge carriers and photovoltaic efficiency.

While the importance of solar cells and enhancing their efficiency is recognized, academic literature has exponentially grown in recent years and lacks studies that consolidate key contributions and the dynamics of scientific production. According to our search, very few review studies were found, none utilizing quantitative strategies. For instance, Liang et al.,[8] conducted a review on graphene advancements for solar cell applications. Al-Douri et al.,[9] focused on identifying key contributions in QDs synthesis and properties in solar cells. Lastly, Manzhos et al.,[10] conducted a more general study to identify the latest technologies in designing materials for next-generation solar cells. None of these studies compiled quantitative data, nor focused on DFT. Therefore, this is the first review with a scientometric focus on QDSCs.

This study combines scientometric analysis and computational approach to comprehensively analyze the evolution of research on Quantum Dot Solar Cell (QDSC). Using data from Scopus and Web of Science databases, we performed a detailed bibliometric analysis, including authorship networks, country-wise collaboration patterns, and keyword co-occurrence to identify key research trends and influential contributors in the field. The application of scientiometric approaches to uncover research dynamics has also been successfully demonstrated in other areas, such as pulmonary diseases, highlighting the versatility and value of these methodologies in diverse scientific fields.[11, 12] In this study, the ToS[13, 14] algorithm was used to identify foundational articles, key contributions that have shaped the development of QDSCs, and emerging research trends. Together, these analyses provide a comprehensive overview of the QDSC research landscape and inform future research directions. The following sections detail the methodology, results, and conclusions.

METHODOLOGY

The parameters for the scientometric search QDSCs using DFT are detailed in Table 1. Data were retrieved from WoS and Scopus on January 1, 2024. Keywords were grouped into the three themes of this study. Results indicated that most of the scientific production was found in Scopus. However, following current scientometric trends,[15, 16] results from both databases were utilized to achieve broader coverage (10.79% of the total articles were not found in Scopus). Articles, books, chapters, and conference papers were included as these document types hold significance in certain knowledge areas.[17]

Table 1: Search parameters and results for WoS and Scopus databases.
ParametersWoSScopus
Range2000 - 2023
DateJanuary 1st 2024
Document typesArticles, books, chapters, and conferences
WordsTitle-Abstract-Keywords: ("solar cell" OR ibsc OR "intermediate band solar cell") AND Title-Abstract-Keywords: ("quantum dot" OR "qd") AND Title-Abstract-Keywords: (dft OR ab-initio OR first-principles OR "first principles" OR "density functional theory")
Results67248
Total (WoS+Scopus)278

Compared to other review methods, scientometric analysis relies on quantitative analysis of the scientific literature. These results provide an overview of the existing literature on a particular topic, offering the advantage of rigor and reduced bias, and thus serve as a complement to other qualitative review methods.

Figure 1 shows an adaptation of the PRISMA flowchart. Preprocessing was one of the most important steps in the methodology. It was a complex process due to formatting differences between WoS and Scopus; for example, references in WoS include DOIs, while those in Scopus have comprehensive information but vary in citation format. Web scraping and text mining were required to standardize the references. Since WoS references include DOIs, these were used to capture additional data information not presented in WoS downloads through the Crossref platform. Text mining was also used to standardize Scopus references to extract authors, journals, and years. This process enriches the analysis and allows for more precise explanations of the resulting figures. The result was an Excel file with 22 sheets of organized information ready for analysis and graph generation from both databases. The detailed scientometric analysis and the application of the ToS algorithm are explained below.

Figure 1: PRISMA flowchart for preprocessing data.

Scientometric Analysis

The scientometric analysis was divided into the following sections: scientific production, countries, journals, and authors. This approach begins with a general overview and ends with a more detailed examination through the author analysis. The country, journal, and author analyses are divided into two parts. The first provides a broad perspective through tabular analysis, while the second highlights the relationships between different entities. For the analysis of scientific collaboration, the approach proposed by Hurtado-Marín et al.,[18] which includes authors from references for network construction, was followed. This novel method of analyzing scientific collaboration networks allows a better understanding of networking strategies within a scientific community.[19]

Tree of Science

The ToS algorithm is based on the process of raw and elaborated sap flow in a plant.[20] After citation network construction, the algorithm identifies articles at the root and trunk based on a metric called SAP, which ranges from roots to leaves and then returns to enhance results. This algorithm has been utilized across various fields including marketing,[21, 22] entrepreneurship,[23] environment,[24] tourism,[25] and psychology.[26, 27] The tool was launched in 2015 and is currently available at the following link https://tos.coreofscience.org/.[13] The ToS algorithm is designed to complement other tools like VOSviewer and Bibliometrix. We chose ToS for its user-friendly approach to identifying relevant articles within a research area based on keyword selection (Table 1).

RESULTS AND DISCUSSION

Scientometric Analysis

Scientific production

Analyzing annual scholarly production is crucial for understanding how research on the QDSCs has evolved over time. As shown in Figure 2, this analysis allows us to track publication trends in databases like Scopus and WoS over the past 22 years. There is a notable difference in production between the two databases, with Scopus dominating throughout the period (green bar). However, the unified production (red line) shows that since 2014, WoS has contributed unique articles not found in Scopus. This underlines the importance of considering both databases for reviews and scientometric analyses. Moreover, there is a significant increment in the article production in the Scopus database since 2015. Citations received show three significant peaks in 2012, 2014, and 2017, along with the lag effect typical of citation behavior after 2019. The annual growth during this period was 14.68%, indicating a renewed interest among researchers in the study and improvement of solar panel efficiency. Three periods were divided based on the annual growth percentage, which will be explained below.

Figure 2: Correlation between annual scientific publications and total citations in quantum dot solar cell research.

Starting period (2000-2011)

During this period, there was a growth of 16.95%, with zero production values in the years 2000, 2001, 2002, 2004, and 2005. However, from 2006 to 2011, scientific articles related to QDSCs began to be published.

Growth period (2012-2019)

This period was characterized by a rapid growth of 38.95%. Both WoS and Scopus contributed significantly to the subject. The highest peak of citations occurred in 2012, due to the application of DFT and modelling of optoelectronics devices to improve the performance of solar cells.[28] In 2014, the peak of citations received was due to several studies related to contributions using QDs and graphene.[29]

Stabilization period (2020-2022)

This period shows a renewed interest in solar cells with a growth of 26.03%. The decrease in scientific production in 2020 may be due to the global pandemic, which limited laboratory experiments. However, by 2022, production is almost equal to the highest production in 2018, indicating significant or better growth in the coming years.

Country Analysis

Country analysis based on researcher affiliation allows the identification of government efforts in scientific topics. For example, Table 2 shows the top ten countries for scientific production of QDSCs, along with the impact measured in citations received and quality measured in Scimago quartiles. The scientific production is led by China with 26.49% (71), followed by the USA with 17.16% (46). It is noteworthy that although China's production is 1.5 times that of the US, the citation percentages for both countries are not significantly different (30.21% vs. 26.23%). This suggests that while China is producing larger volume of research, the USA continues to make substantial and influential contributions to the field of QDSC research. It is also important to note that although Saudi Arabia is ranked fifth in Table 2, it is ranked third in terms of citations received.

Table 2: Countries by scientific production and citation.
CountryProductionCitationQ1Q2Q3Q4
China7126.49%316830.21%421040
USA4617.16%275026.23%30121
India4215.67%5154.91%18420
Spain103.73%1121.07%7010
Saudi Arabia93.36%122311.66%4200
Japan82.99%1261.2%4000
Iran72.61%580.55%2300
France62.24%1201.14%6000
Malaysia62.24%1771.69%2000
Australia51.87%960.92%3000

Recent research in China has shown that QDs can be optimized in terms of structure and energy stability, making them a viable option for improving solar cell performance.[30] On the other hand, the USA has been working on high-efficiency phosphors for the construction of white light-emitting diode devices for photovoltaic applications, which have shown good photoelectric properties.[31] In addition, researchers from India are investigating new forms of silicon carbide useful for solar cells.[32]

Scientific collaboration between countries based on authors' affiliations allows the identification of groups of countries working together (see Figure 3). The collaborative network shows three well-defined groups or communities (see Figure 3a). The first community, led by Saudi Arabia, India, and Malaysia, is the largest (see Figure 3b) and has conducted collaborative work to identify new high performance materials for QDSCs.[33] The second group is led by China and the USA, with some research focused on addressing the issue of lead toxicity in solar cells by proposing lead-free oxide perovskites for photovoltaic applications.[34] The third group, led by the Netherlands and Spain, has conducted work related to addressing the cooling process of hot carriers, which results in a loss of efficiency.[35] This collaborative study demonstrated a new way to achieve efficient transfer at room temperature. An interesting aspect highlighted in the nodes and links figure over time (see Figure 3c) is the overlap of link proportions after 2016. This reflects the continuity of collaboration between the same group of countries, strengthening their relationships.

Figure 3: Scientific collaboration between countries a) network of countries, b) community by size and c) nodes and links over time.

Journal Analysis

According to Table 3, journals publishing on QDSCs have the highest quality; of the top 10 journals publishing on this topic, 9 and 8 are in the highest quartile (Q1) according to the Scimago ranking (https://www.scimagojr.com/) and the Journal Citation Report (JCR) (https://www.webofscience.com/wos/woscc/basic-search), respectively. The Journal of Physical Chemistry C has the highest number of publications in Scopus with 22. Recently, this journal published research showing that QDs can be used for experimental design and exhibit a variety of electronic energy gaps depending on their morphology.[36] The journal with the highest H-index is the Journal Of The American Chemical Society (674), which recently published research where a MgO-QDs/TiO2 heterojunction was designed for QDSCs, showing high light absorption efficiency, which could lead to the design of new materials for photovoltaic applications.[37]

Table 3: Journals that publish on QDSCs, its impact factor and H-index according to Scimago and WoS (JCR) rankings.
JournalWoSScopusImpact FactorH-IndexQuartile ScopusQuartile Wos
Journal of Physical Chemistry C5221.03323Q1Q2
Journal of Physical Chemistry Letters491.85235Q1Q2
Physical Chemistry Chemical Physics290.82272Q1Q1
Journal of the American Chemical Society375.95674Q1Q1
Nano Letters183.54531Q1Q1
ACS Nano264.73448Q1Q1
Journal Of Materials Chemistry A073.16270Q1Q1
Chemical Physics Letters440.48248Q2Q1
Chemistry of Materials152.87409Q1Q1
Advanced Functional Materials245.57376Q1Q1

Figure 4 shows the citation analysis between journals. Three prominent groups were identified (see Figure 4a). This analysis allows the identification of thematic groups of journals (see Figure 4b). The first group is related to materials research,[35, 38] the second group emphasizes physical properties in solar cell design,[39, 40] and the third group is associated with computational studies around solar cells.[9, 30] The graph of nodes and links over time (see Figure 4c) shows a consolidation of topics within journals, which is reflected in the overlap of link and node proportions.

Figure 4: Journals where QDSCs topic are mainly published. a) journal network, b) communities by size and c) nodes and links through time.

Author Collaboration Network

This section presents the top ten researchers in the field of solar cells, along with their H-index and affiliation (Table 4). Professor Long Run has the highest H-index among researchers in the field of nanoscale semiconductor development, specifically perovskites to enhance photovoltaic technologies.[41, 42] Sarkar P has conducted research on simulating QDs for organic solar cells to improve its efficiency.[43, 44] Researchers from around the world, particularly those affiliated with countries like China, are actively involved in this field, emphasizing the global need for advancements in alternative energy systems.

Table 4: Total number of publications, Scopus h-index and affiliation of the most productive authors in QDSCs.
Sl. No.ResearcherTotal Articles*Scopus H-indexAffiliation
1Long R1045Beijing Normal University, Beijing, China
2Sarkar P1033Visva-Bharati University, Santiniketan, India
3Wang M1032Ministry of Education of the People's Republic of China
4Yang C1036Ludong University, Yantai, China
5Gao F88Hangzhou City University, Hangzhou, China
6Ma X829Ludong University, Yantai, China
7Infante I748Ikerbasque, Basque Foundation for Science, Bilbao, Spain
8Li X728Harbin Institute of Technology, Harbin, China
9Zhang L770Sichuan University Chengdu, China
10Zhang Z720Fujian Normal University, Fuzhou, China

Figure 5 is created from the personal networks of researchers listed in Table 4. The network demonstrates a cohesive and consolidated community, as evidenced by the formation of a large component (blue) derived from authors' personal networks (Figure 5a). It is also noteworthy that the graph depicting (Figure 5c) nodes and links over time shows that the proportion of links surpasses the proportion of nodes (researchers) after the year 2016, indicating a strengthening of scientific collaboration. For example, although Professor Infante has conducted significant research on QD,[45, 46] he has not collaborated directly with the other researchers listed in Table 4. However, his co-authors have connections with other researchers who have collaborated with some of the most productive investigators worldwide. This is reflected in the collaboration network, where authors may appear isolated from each other but remain part of the same scientific community (Figure 5b). This suggests that while there are key contributors, the overall community is interconnected, which may facilitate knowledge sharing and innovation in QDSC research.

Figure 5: Scientific collaboration network between authors. a) authors’ network, b) communities by size and c) nodes and links through time.

Tree of Science

Root

The development of first-principles simulations of quantum dot-based solar cells is rooted in pioneering works. Shockley & Queisser[5] conducted one of the earliest endeavors in solar cell development, proposing a theory that established the maximum efficiency limit achievable by a p-n junction solar cell. This work paved the way for exploring alternative approaches to surpass the Shockley-Queisser limit (SQ limit). For instance, one strategy to enhance these efficiencies was through simulations. In this way, Kohn & Sham[47] established the foundation for computational calculations by introducing a method to solve the Schrödinger-like equations for many electrons using the electron charge density concept proposed by Hohenberg & Kohn.[48] The method includes Exchange and Correlation (XC) effects through an effective potential that depends on density. The authors propose a simple, efficient method for describing the electronic properties of atomic and molecular systems, which has the potential to study solid-state systems. They also emphasize the need to improve correlation treatment. Lee et al.,[49] proposed an enhancement by devising a formula for Colle-Salvetti correlation energy based on electron density. The authors used the Local Density Approximation (LDA) to estimate exchange energy and electron kinetic energy functionals. They then compared the numerical results of their proposed formula with experimental data and calculations from other methods, demonstrating the validity and efficiency of their approach.

Becke[50] proposed an approximation to the XC functional that combines exact exchange, Spin Density Local Approximation (LSDA), and gradient corrections for XC. The proposed functional is applied to atoms and molecules, yielding a fit to experimental data with an accuracy of approximately 2 kcal/mol. Blöchl[51] formulated the Projector Augmented-Wave (PAW) method for calculating the electronic structure of solids, based on pseudopotential and Linear Augmented Plane Wave (LAPW) methods. The PAW method allows for a description of nuclei and valence electrons, avoiding pseudized potentials and is based on dividing space into atomic and interstitial regions, constructing projected wave functions that satisfy continuity and orthogonality conditions. Perdew et al.,[52] subsequently introduced a new Generalized Gradient Approximation (GGA-PBE) for XC energy. This approximation is simpler and more accurate than the Perdew-Wang 1991 (PW91) GGA.[53] The GGA-PBE improves upon several aspects, including a more accurate description of the linear response of the uniform electron gas and a smoother potential. The authors state that GGA-PBE produces comparable outcomes to PW91, but with a simpler form and derivation.

Kresse & Furthmüller[54] presented an efficient scheme for calculating the Kohn-Sham ground state of metallic systems using the pseudopotential method and a set of plane waves. The method is based on a self-consistency cycle, which divides the problem into matrix diagonalization and charge density mixing. The authors discuss various iterative algorithms for diagonalization. They also demonstrate that the number of iterations needed to achieve a specific accuracy is almost independent of the system size. Kresse & Joubert[55] established a formal relationship between Vanderbilt's ultrasoft pseudopotentials (USPP) and Blochl's PAW method. The authors presented a comparison of the accuracy and efficiency of PAW and USPP methods by linearizing two terms in a modified PAW total energy functional to obtain the total energy functional for ultrasoft pseudopotentials. Tao et al.,[56] proposed the non-empirical construction of a density functional for XC energy called meta-GGA. This functional includes electron density, its gradient, and Kohn-Sham orbital kinetic energy density. It is an objective and precise approach to calculating XC energy. Heyd et al.,[57] developed a density functional based on a screened Coulomb potential for exchange interaction to filter the long-range part of the Hartree-Fock exchange, retaining other unscreened Coulomb interactions. This enables more accurate and faster calculations, even in metallic systems. Despite significant progress in developing improved XC functionals for material description, the exact form of the ideal functional remains an open challenge.[58–60] However, ongoing research holds promise for the continued development of even more accurate functionals.[61] This ongoing pursuit of the optimal XC functional is often referred to as Jacob’s ladder.[62–64]

Trunk

The trunk contains seminal works grounded in foundational research, paving the way for advancements in QDSC studies. Long & Prezhdo[65] investigated the dynamics of photo-induced Electron Transfer (ET) at the interface of a PbSe quantum dot and a TiO2 surface. This process is crucial for enhancing QDSCs. The authors demonstrate that photo-induced ET at the PbSe-TiO2 interface primarily occurs via an adiabatic mechanism due to strong donor-acceptor coupling. Ip et al.,[28] used DFT calculations to examine the electronic and optical properties of hybrid colloidal QDs passivated with various organic and inorganic ligands. The DFT results were compared with experimental data obtained through photoelectron spectroscopy and photoluminescence. Tan et al.,[66] studied the effect of hole-accepting ligands on the photo-stability of CdSe quantum dots, which are potential absorbers for QDs-sensitized solar cells. DFT calculations were utilized to estimate the ionization potentials of organic ligands bound to CdSe QDs using Koopmans' theorem. Additionally, the charge distribution in the molecule-surface complex was characterized using Natural Bond Orbital (NBO) analysis. In their study, Nadler & Sanz[67] investigated the impact of aliphatic and aromatic ligands on the optoelectronic properties of CdSe quantum dots using DFT. The study revealed that aromatic ligands have a greater impact on the optoelectronic properties of QDs compared to aliphatic ligands.

In a related study, Rimal et al.,[68] found that doping PbS quantum dots with manganese atoms resulted in a 300% increase in photocurrent. Ab initio calculations confirmed that the presence of Mn at the Pb quantum dot/Zn2SnO4 interface reduced the tunneling barrier height for electrons, which explains the observed increase in photovoltaic current. Rajbanshi & Sarkar[69] investigated the photovoltaic properties of CdTe quantum dot-porphyrin nanocomposites using the self-consistent charge density functional tight-binding method. The study focused on achieving type II band alignment in the nanocomposites to enhance photovoltaic performance and avoid carrier recombination. Giberti et al.,[70] conducted a study on heterogeneous chalcogenide nanostructures with adjustable energy bandgaps under pressure. The study employed atomistic calculations to investigate how interfacial morphology and defects impact the electronic properties of PbSe and CdSe quantum dots. The study found that interfaces between PbSe quantum dots and CdSe matrices could generate harmful intra-gap states. Conversely, the reverse system (CdSe quantum dots in PbSe) exhibited superior electronic properties for photovoltaic applications. Additionally, applying pressure to the PbSe matrix was predicted to tune the CdSe structure and its energy bandgap.

In another study, Gao et al.,[71] investigated graphene QDs with Copper (Cu) metallized macrocycles using DFT. The optical absorption of optimized structures was calculated by the authors. It was noted that all QDs enhanced absorption in the visible spectrum range. Sharma & Jha[72] investigated the effect of nitrogen (N), boron (B), and phosphorus (P) adatoms on carboxyl-functionalized graphene quantum dots (COOH-GQDs) for solar cell applications. The study showed that COOH-GQDs experienced a 22-30% increase in energy conversion efficiency after being doped with N, B, and P. These doped compounds are promising candidates for use in QDSCs applications.

The most recent research on solar cell efficiency can be divided into three branches (Figure 6). These investigations have led to the development of new materials and a better understanding of the mechanisms affecting solar cell efficiency, which has enabled their enhancement. A clear upward trend in QDSCs research is evident in Figure 7, with the slope of the data indicating a rapid growth in this field since 2010.

Figure 6: Networks and nodes of the main topics in QDSCs.
Figure 7: Evolution of best research-cell efficiencies for different technologies. Highlighted are the emerging photovoltaic technologies. QDSCs evolution is shown over time (2010-2023)

Branch 1 Halide Perovskites solar cells

Ray et al.,[73] investigated the charge transfer mechanism between CsPbBr3 perovskite nanocrystals and Nitrogen-doped Carbon Quantum Dots (NCQDs) to form heterostructures with potential applications in optoelectronics and photocatalysis. The authors used DFT to calculate the electronic structure and charge density difference of the heterostructures to understand the charge transfer process. The study analyzes the impact of the thickness of the nanocrystal shell on carrier mobility and stability. This is crucial for applications such as solar cells and LEDs. Cai et al.,[74] investigated the use of graphene QDs modified with imidazole (IGQDs) in perovskite solar cells. The IGQDs improved energy conversion efficiency by passivating defects at the perovskite and tin dioxide (SnO2) interface and accelerating carrier extraction and transfer. The authors reported an efficiency of 24.11% and high stability under ultraviolet irradiation. Nagal et al.,[75] investigated the slow cooling of hot carriers in CsPbBr3 perovskite quantum dot-carbon nanolayer heterostructures. The authors studied charge transfer in the heterostructures through Ultrafast Transient Absorption Spectroscopy. Additionally, they performed DFT calculations to understand band alignment and confirm experimental results. Xu et al.,[76] investigated CsPbI3 quantum dots with ligands to improve efficiency and perovskite film preparation. The authors reported an increase in grain size, a reduction in defects, a decrease in non-radiative recombination, and an improvement in charge transfer. The energy conversion efficiency improved to 23.32%, surpassing that of the control device at 21.61%. The electronic structure of perovskite films under strain conditions was studied using DFT. Li et al.,[77] used DFT to investigate the electronic structure and optical properties of hexagonal Methylammonium Bismuth Iodide (MBI), employing the LDA-½ method and Spin-Orbit Coupling (SOC) effect. The predicted efficiency of MBI was 11.5%, which is 7 times higher than the experimental value of 1.64%,[78] indicating potential for the development of more efficient solar cells based on MBI. Pandey & Chakrabarti[79] investigated the optical and electronic properties of CsPbI3 quantum dots using DFT and validated the results with experiments. The authors suggest that this material has significant potential for use in optoelectronics and solar cells.

Branch 2 Dye sensitized solar cells

Gao et al.,[71] conducted theoretical investigations on a nanocomposite consisting of Tetraphenylporphyrin (TPP) and Graphene Oxide Quantum Dots (GOQDs) as sensitizers in Dye-Sensitized Solar Cells (DSSCs). The authors used DFT to optimize geometric structures and Time-Dependent Density Functional Theory (TDDFT) to analyze optical absorption. Li et al.,[80] found that the GOQDs (18OH)-TPP compound shows potential as a sensitizer for DSSCs, providing insights for the development of solar energy capture materials. They also studied the optoelectronic properties of graphene-phenothiazine nanocomposites as a photoactive layer in solar cells using TDDFT. The authors reported that the combination of graphene and phenothiazine improved charge separation, light absorption, and light harvesting efficiency. This material shows promise for use in solar cells and optoelectronics. In a related study, Xing et al.,[81] investigated the use of nanocomposites of Phycocyanobilin (PCB) and Phycourobilin (PEB) with Graphene Quantum Dots (GQDs) as sensitizers in DSSCs. The geometric configurations were optimized using DFT, and stability was confirmed through vibrational frequency and formation energy analysis. The electronic properties of the GQD2-PEB nanocomposite suggest its potential as a favorable sensitizer due to apparent charge spatial separation, appropriate frontier orbital energies, and enhanced absorption coefficient in the solar irradiation region. Majid et al.,[82] used TDDFT to model photon injection in organic dye/TiO2 systems. Their aim was to explore enhancements in Dye-Sensitized Solar Cells (DSSCs). The authors proposed structural modifications in carbazole-based organic dyes by altering the π-bridge and introducing thiophene and oxadiazole rings. These modifications affected the optical and electronic properties. Jain et al.,[83] studied the optical and electronic properties of CdS quantum dots sensitized with dyes. They observed a significant distortion in the quantum dot structure when strongly interacting with the dye. The position of the energy levels of the dye and the QDs varies depending on the configuration. In their investigation the use of TiO2 Electron Transport Layers (ELTs) in Sb2Se3 solar cells, Don et al.,[84] aimed to replace toxic CdS ETLs. By optimizing TiO2 processing conditions, the research achieved a power conversion efficiency of 8.12%, highlighting the potential for more efficient and environmentally friendly solar cells.

Branch 3 Nanocrystal solar cells

Kumakura et al.,[85] calculated the temperature-dependent carrier mobility and optical properties of lead sulfide Quantum Dots (PbS QDs) with Formamidinium (FAI) and Chlorine (Cl) ligands using DFT and Non-Equilibrium Green's Function (NEGF) techniques. The authors reported that QDs with Folic Acid (FA) ligands exhibit higher mobility and enhanced optical absorption compared to those with Cl ligands. This is attributed to the intermediate band electronic structure that influences transport properties. These findings suggest that FA ligands could be more efficient for solar cell applications due to their higher mobility and optical absorption. This marks a promising step toward the development of more efficient low-dimensional optoelectronic devices. Yazdani et al.,[86] aimed to comprehend the transport, generation, and trapping of charge carriers in semiconductor-based nanocrystal QDs through DFT simulations. The DFT results were used to create a predictive model to understand how the presence of a charge carrier in an individual quantum dot can lead to polaron formation, which is crucial for the charge transport mechanism in these systems.

Fuhr et al.,[87] investigated the impact of anti-site defects and copper vacancies in CuxIn2-xSy quantum dots (QDs-CIS) on their optical properties, which are essential for energy harvesting applications. The authors utilized DFT calculations to predict the effects of different defects on optical spectra, consolidating various proposed emission models. The authors state that the study enhances the performance of devices such as solar cells and Luminescent Solar Concentrators (LSCs) by providing a clearer understanding of structure-property relationships in QDs-CIS. Oh et al.,[88] conducted research on Silver Bismuth Sulfide Nanocrystals (AgBiS2) for thin-film photovoltaics. The chemical composition and crystal structure of the nanocrystals were revealed through X-ray Photoelectron Spectroscopy (XPS) and X-ray Diffraction (XRD) analyses. To determine the stability of iodine ligands after water treatment, DFT was used to calculate the binding energies of iodine on various AgBiS2 and PbS surfaces. DFT calculations have facilitated a more profound comprehension of chemical interactions on nanocrystal surfaces and their water resistance. This is crucial for the development of stable, lead-free photovoltaic materials.

Singh et al.,[89] conducted DFT calculations to investigate the stability and electronic properties of single-walled Si2BN nanotubes. Their study confirmed the structural stability of these nanotubes and explored the impact of rolling Si2BN sheets into nanotubes on chemical bonding and conductivity. The research highlights the unique properties of Si2BN nanotubes, and their potential applications in electronic and materials science.

CONCLUSION

This study compiled publications related to QDSCs using DFT, classifying 278 consolidated references from Scopus and WoS databases. Two analyses were conducted: a scientometric analysis and one using the ToS algorithm. The study identified changes and the impact of scientific production over the past 22 years, enabling researchers to identify important contributions in the field of QDSC research. The analysis highlights a significant increase in DFT-based research on QDSCs, particularly from 2012 to 2019, with a growth rate of 38.95%. This growth is driven by studies focusing on QDs and graphene to enhance solar cell performance using DFT simulations. The increasing number of Scopus and WoS indexed publications highlights DFT's growing importance as a computational method tool for understanding and optimizing QDSCs. This trend reflects a rising interest in using advanced computational methods to optimize solar cell technologies.

The study reveals that China leads in the number of publications with 71 articles, followed by the United States with 46 articles. However, the citation impact is nearly comparable, with the USA at 26.23% and China 30.21%. This indicates that while China is producing more research, the USA’s contributions remain highly influential, suggesting a competitive landscape in QDSC research. In terms of journals, the findings show that the Journal of Physical Chemistry C has the highest production, with 22 publications in Scopus and 5 in WoS, with a significant number of publications in high-impact journals (nine out of ten in Q1). This underscores the high quality of research in this field and suggests that findings from these journals are likely to influence future studies and applications in solar technology.

The analysis of scientific collaboration networks indicates a high level of cohesion, despite limited collaboration among the most productive researchers.

Although this study did not explore technical aspects and only selected representative research, it still provides valuable insights for researchers interested in studying QDSCs using DFT. Given the significant growth in QDSC research over the past three years, future research should focus on interdisciplinary approaches that combine experimental and computational techniques to optimize the efficiency and practical applications of QDSCs.

DFT has proven to be an important computational method for understanding the electronic properties and stability of materials used in QDSCs. DFT calculations can be used to design new materials with specific properties, potentially leading to a significant improvement in solar cell efficiency.

REFERENCES

As published

Showing references and in-text citations exactly as published.

  1. 1.Nair, A. Quantum dot solar cell market size, share & trends report, 2031 [Internet]. Straits Research. 2023.GOOGLE SCHOLAR
  2. 2.Luque, A; Martí, A. A metallic intermediate band high efficiency solar cell. Prog Photovolt Res Appl. 2001;9(2):73–86. https://doi.org/10.1002/pip.354DOIGOOGLE SCHOLAR
  3. 3.Huang, P; Shi, JJ; Wang, P; Zhang, M; Ding, YM; Wu, M et al. Origin of the wide band gap from 0.6 to 2.3 eV in photovoltaic material InN: quantum confinement from surface nanostructure. J Mater Chem A. 2016;4(44):17412–8. https://doi.org/10.1039/C6TA07700EDOIGOOGLE SCHOLAR
  4. 4.Luque, A; Martí, A. Increasing the efficiency of ideal solar cells by photon induced transitions at intermediate levels. Phys Rev Lett. 1997;78(26):5014–7. https://doi.org/10.1103/PhysRevLett.78.5014DOIGOOGLE SCHOLAR
  5. 5.Shockley, W; Queisser, HJ. Detailed balance limit of efficiency of p-n junction solar cells. J Appl Phys. 1961;32(3):510–9. https://doi.org/10.1063/1.1736034DOIGOOGLE SCHOLAR
  6. 6.Nguyen, TC; Can, TT; Choi, WS. Optimization of quantum dot thin films using electrohydrodynamic jet spraying for solution-processed quantum dot light-emitting diodes. Sci Rep. 2019;9(1):13885. https://doi.org/10.1038/s41598-019-50181-5DOIGOOGLE SCHOLAR
  7. 7.Vyvenko, O; Bondarenko, A. Crystal lattice defects as natural light emitting nanostructures in semiconductors. Progress in photon science: recent advances. Cham: Springer International Publishing. 2019;405–36. https://doi.org/10.1007/978-3-030-05974-3_21DOIGOOGLE SCHOLAR
  8. 8.Liang, X; Tan, X; Zhao, Y; Feng, X; Li, H; He, Y et al. First‐principles electronic structure calculations on modified graphene sheets for solar cell applications: a review. ChemistrySelect. 2023;8(33). https://doi.org/10.1002/slct.202301496DOIGOOGLE SCHOLAR
  9. 9.Al-Douri, Y; Khan, MM; Jennings, JR. Synthesis and optical properties of II–VI semiconductor quantum dots: a review. J Mater Sci Mater Electron. 2023;34(11):993. https://doi.org/10.1007/s10854-023-10435-5DOIGOOGLE SCHOLAR
  10. 10.Manzhos, S; Chueh, CC; Giorgi, G; Kubo, T; Saianand, G; Lüder, J et al. Materials design and optimization for next-generation solar cell and light-emitting technologies. J Phys Chem Lett. 2021;12(19):4638–57. https://doi.org/10.1021/acs.jpclett.1c00714DOIGOOGLE SCHOLAR
  11. 11.Balaei-Kahnamoei, M; Al-Attar, M; Khazaneha, M; Raeiszadeh, M; Ghorbannia-Dellavar, S; Bagheri, M et al. Overview of herbal therapy of acute and chronic pulmonary disease: a conceptual map. Libr Hi Tech. 2024;42(1):79–100. https://doi.org/10.1108/LHT-04-2022-0200DOIGOOGLE SCHOLAR
  12. 12.Khazaneha, M; Osareh, F; Shafiee, K. Trend linking of multiple system atrophy: a scientiometric study. Endocr Metab Immune Disord Drug Targets. 2021;21(4):700–10. https://doi.org/10.2174/1871530320666200607194810DOIGOOGLE SCHOLAR
  13. 13.Zuluaga, M; Robledo, S; Arbelaez-Echeverri, O; Osorio-Zuluaga, GA; Duque-Méndez, N. Tree of science – ToS: A web-based tool for scientific literature recommendation. Search less, research more. Issues Sci Technol Librarianship. 2022;(100). https://doi.org/10.29173/istl2696DOIGOOGLE SCHOLAR
  14. 14.Robledo, S; Zuluaga, M; Valencia-Hernandez, LA; Arbelaez-Echeverri, OA; Duque, P; Alzate-Cardona, JD. Tree of science with Scopus: A shiny application. Issues Sci Technol Librarianship. 2022;(100). https://doi.org/10.29173/istl2698DOIGOOGLE SCHOLAR
  15. 15.Ariza-Colpas, PP; Piñeres-Melo, MA; Morales-Ortega, RC; Rodriguez-Bonilla, AF; Butt-Aziz, S; Naz, S et al. Augmented reality and tourism: A bibliometric analysis of new technological bets in the post-COVID era. Sustainability. 2023;15(21). https://doi.org/10.3390/su152115358DOIGOOGLE SCHOLAR
  16. 16.Grisales, AM; Robledo, S; Zuluaga, M. Topic modeling: perspectives from a literature review. IEEE Access. 2023;11:4066–78. https://doi.org/10.1109/ACCESS.2022.3232939DOIGOOGLE SCHOLAR
  17. 17.Wang, C; Cui, X; Zhao, S; Guo, K; Wang, Y; Song, Y. The application of deep learning in stereo matching and disparity estimation: A bibliometric review. Expert Syst Appl. 2024;238:122006. https://doi.org/10.1016/j.eswa.2023.122006DOIGOOGLE SCHOLAR
  18. 18.Hurtado-Marín, VA; Agudelo-Giraldo, JD; Robledo, S; Restrepo-Parra, E. Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles. Sci Rep. 2021;11(1):5721. https://doi.org/10.1038/s41598-021-85041-8DOIGOOGLE SCHOLAR
  19. 19.Robledo, S; Eider, VJ; Darío, DM; Duque-Uribe, V. Networking as an entrepreneurial marketing tool: the link between effectuation and word of mouth. J Res Mark Entrep. 2022;25(2):270–85. https://doi.org/10.1108/JRME-08-2020-0112DOIGOOGLE SCHOLAR
  20. 20.Valencia-Hernandez, DS; Robledo, S; Pinilla, R; Duque-Méndez, ND; Olivar-Tost, G. SAP algorithm for citation analysis: an improvement to tree of Science. Ing Inv. 2020;40(1):45–9. https://doi.org/10.15446/ing.investig.v40n1.77718DOIGOOGLE SCHOLAR
  21. 21.Duque, P; Cárdenas, M; Robledo, S. Marketing social: evolución y tendencias. Entramado. 2023;20(1). https://doi.org/10.18041/1900-3803/entramado.1.10378DOIGOOGLE SCHOLAR
  22. 22.Robledo, S; Duque, P; Aguirre, AM. Word of mouth marketing: A scientometric analysis. J Scientometric Res. 2023;11(3):436–46. https://doi.org/10.5530/jscires.11.3.47DOIGOOGLE SCHOLAR
  23. 23.Robledo, S; Grisales Aguirre, AM; Hughes, M; Eggers, F. ‘Hasta la vista, baby’ – will machine learning terminate human literature reviews in entrepreneurship?. J Small Bus Manag. 2021;1–30. https://doi.org/10.1080/00472778.2021.1955125DOIGOOGLE SCHOLAR
  24. 24.Ariza-Colpas, PP; Piñeres-Melo, MA; Morales-Ortega, RC; Rodríguez-Bonilla, AF; Butt-Aziz, S; Naz, S et al. Sustainability in hybrid technologies for heritage preservation: A scientometric study. Sustainability. 2024;16(5):1991. https://doi.org/10.3390/su16051991DOIGOOGLE SCHOLAR
  25. 25.Ariza-Colpas, PP; Piñeres-Melo, MA; Morales-Ortega, RC; Rodriguez-Bonilla, AF; Butt-Aziz, S; Naz, S et al. Tourism and conservation empowered by augmented reality: A scientometric analysis based on the science tree metaphor. Sustainability. 2023;15(24):16847. https://doi.org/10.3390/su152416847DOIGOOGLE SCHOLAR
  26. 26.Ovalle-Correa, B; Ramos-Tomalá, D. Tendencias emergentes en la literatura sobre el psicológico y el desempeño laboral: un análisis bibliométrico. RFD. 2024;8(1). https://doi.org/10.37957/rfd.v8i1.127DOIGOOGLE SCHOLAR
  27. 27.Tabares, AS; Arenas, DA; Duque, MC. Research trends on the relationship between parenting and prosocial behaviors in children and adolescents. RIP/IJP. 2023;57(1):e1378–e1378. https://doi.org/10.30849/ripijp.v57i1.1378DOIGOOGLE SCHOLAR
  28. 28.Ip, AH; Thon, SM; Hoogland, S; Voznyy, O; Zhitomirsky, D; Debnath, R et al. Hybrid passivated colloidal quantum dot solids. Nat Nanotechnol. 2012;7(9):577–82. https://doi.org/10.1038/nnano.2012.127DOIGOOGLE SCHOLAR
  29. 29.Long, R; English, NJ; Prezhdo, OV. Minimizing electron-hole recombination on TiO2 sensitized with PbSe quantum dots: time-domain ab initio analysis. J Phys Chem Lett. 2014;5(17):2941–6. https://doi.org/10.1021/jz5013627DOIGOOGLE SCHOLAR
  30. 30.Du, N; Chen, H. First principles study of quantum dots-sensitized solar cells using Type-II core/shell quantum dots as efficient sensitizers. Comput Mater Sci. 2024;232:112654. https://doi.org/10.1016/j.commatsci.2023.112654DOIGOOGLE SCHOLAR
  31. 31.Zhang, Y; Mao, J; Zhu, P; Wang, G. Tunable multicolor luminescence in vanadates from yttrium to indium with enhanced luminous efficiency and stability for its application in WLEDs and indoor photovoltaics. Nano Res. 2023;16(8):11486–94. https://doi.org/10.1007/s12274-023-5821-9DOIGOOGLE SCHOLAR
  32. 32.Sahoo, MK; Kale, P. Integration of silicon nanowires in solar cell structure for efficiency enhancement: a review. J Materiomics. 2019;5(1):34–48. https://doi.org/10.1016/j.jmat.2018.11.007DOIGOOGLE SCHOLAR
  33. 33.Rajhi, AA; Alaziz, KM; Oviedo, BS; Yadav, A; Hernández, E; Gallegos, C et al. Enhancing the performance of quantum dot solar cells through halogen adatoms on carboxyl edge-functionalized graphene quantum dots. J Photochem Photobiol A. 2024;447:115240. https://doi.org/10.1016/j.jphotochem.2023.115240DOIGOOGLE SCHOLAR
  34. 34.Sun, Q; Wang, J; Yin, WJ; Yan, Y. Bandgap engineering of stable lead-free oxide double perovskites for photovoltaics. Adv Mater. 2018;30(15):e1705901. https://doi.org/10.1002/adma.201705901DOIGOOGLE SCHOLAR
  35. 35.Wang, HI; Infante, I; Brinck, ST; Cánovas, E; Bonn, M. Efficient hot electron transfer in quantum dot-sensitized mesoporous oxides at room temperature. Nano Lett. 2018;18(8):5111–5. https://doi.org/10.1021/acs.nanolett.8b01981DOIGOOGLE SCHOLAR
  36. 36.Ghosal, S; Nath, S; Bandyopadhyay, A; Sen, S; Jana, D. Tetragonal silicene and germanene quantum dots: candidates for enhanced nonlinear optical and photocatalytic activity. J Phys Chem C. 2021;125(39):21718–28. https://doi.org/10.1021/acs.jpcc.1c06583DOIGOOGLE SCHOLAR
  37. 37.Saranya, G; Bandaru, S; Shen, K; Jayabal, S; Chen, M. Theoretical designing of atomically precise MgO/TiO2(001) quantum dot-sensitized solar cell for high visible light absorption and fast charge injection. J Phys Chem C. 2024;128(3):1222–9. https://doi.org/10.1021/acs.jpcc.3c04051DOIGOOGLE SCHOLAR
  38. 38.Kroupa, DM; Pach, GF; Vörös, M; Giberti, F; Chernomordik, BD; Crisp, RW et al. Enhanced multiple exciton generation in PbS|CdS Janus-like Heterostructured Nanocrystals. ACS Nano. 2018;12(10):10084–94. https://doi.org/10.1021/acsnano.8b04850DOIGOOGLE SCHOLAR
  39. 39.Shariatinia, Z. Designing novel spiro compounds as favorable hole transport materials for quantum dot sensitized photovoltaics. Sol Energy. 2022;236:548–60. https://doi.org/10.1016/j.solener.2022.03.035DOIGOOGLE SCHOLAR
  40. 40.Assareh Pour, F; Zandi, H. DFT electron transport study of quantum dot sensitized solar cells linkers. Optik. 2017;143:199–204. https://doi.org/10.1016/j.ijleo.2017.05.089DOIGOOGLE SCHOLAR
  41. 41.He, J; Zhu, Y; Long, R. Charge localization induced by reorientation of FA cations greatly suppresses nonradiative electron-hole recombination in FAPbI3 perovskites: A time-domain ab initio study. Chin J Chem Phys. 2020;33(5):642–8. https://doi.org/10.1063/1674-0068/cjcp2006109DOIGOOGLE SCHOLAR
  42. 42.Shi, R; Fang, WH; Vasenko, AS; Long, R; Prezhdo, OV. Efficient passivation of DY center in CH3NH3PbBr3 by chlorine: quantum molecular dynamics. Nano Res. 2022;15(3):2112–22. https://doi.org/10.1007/s12274-021-3840-yDOIGOOGLE SCHOLAR
  43. 43.Habib, M; Ghosh, NN; Sarkar, R; Pramanik, A; Sarkar, P; Pal, S. Controlling the charge transfer and recombination dynamics in hollow ZnO QD based dye sensitized solar cell: an insight from ab initio simulation. Chem Phys Lett. 2018;709:21–5. https://doi.org/10.1016/j.cplett.2018.08.036DOIGOOGLE SCHOLAR
  44. 44.Biswas, S; Pramanik, A; Sarkar, P. Origin of different photovoltaic activities in regioisomeric small organic molecule solar cells: the intrinsic role of charge transfer processes. J Phys Chem C. 2018;122(26):14296–303. https://doi.org/10.1021/acs.jpcc.8b02821DOIGOOGLE SCHOLAR
  45. 45.Akkerman, QA; Martín-García, B; Buha, J; Almeida, G; Toso, S; Marras, S et al. Ultrathin orthorhombic PbS nanosheets. Chem Mater. 2019;31(19):8145–53. https://doi.org/10.1021/acs.chemmater.9b02914DOIGOOGLE SCHOLAR
  46. 46.du Fossé, I; Boehme, SC; Infante, I; Houtepen, AJ. Dynamic formation of metal-based traps in photoexcited colloidal quantum dots and their relevance for photoluminescence. Chem Mater. 2021;33(9):3349–58. https://doi.org/10.1021/acs.chemmater.1c00561DOIGOOGLE SCHOLAR
  47. 47.Kohn, W; Sham, LJ. Self-consistent equations including exchange and correlation effects. Phys Rev. 1965;140(4A):A1133–8. https://doi.org/10.1103/PhysRev.140.A1133DOIGOOGLE SCHOLAR
  48. 48.Hohenberg, P; Kohn, W. Inhomogeneous electron gas. Phys Rev. 1964;136(3B):B864–71. https://doi.org/10.1103/PhysRev.136.B864DOIGOOGLE SCHOLAR
  49. 49.Lee, C; Yang, W; Parr, RG. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys Rev B Condens Matter. 1988;37(2):785–9. https://doi.org/10.1103/physrevb.37.785DOIGOOGLE SCHOLAR
  50. 50.Becke, AD. Density-functional thermochemistry. III. The role of exact exchange. J Chem Phys. 1993;98(7):5648–52. https://doi.org/10.1063/1.464913DOIGOOGLE SCHOLAR
  51. 51.Blöchl, PE. Projector augmented-wave method. Phys Rev B Condens Matter. 1994;50(24):17953–79. https://doi.org/10.1103/physrevb.50.17953DOIGOOGLE SCHOLAR
  52. 52.Perdew, JP; Burke, K; Ernzerhof, M. Generalized gradient approximation made simple. Phys Rev Lett. 1996;77(18):3865–8. https://doi.org/10.1103/PhysRevLett.77.3865DOIGOOGLE SCHOLAR
  53. 53.Perdew, JP; Wang, Y. Accurate and simple analytic representation of the electron-gas correlation energy. Phys Rev B Condens Matter. 1992;45(23):13244–9. https://doi.org/10.1103/physrevb.45.13244DOIGOOGLE SCHOLAR
  54. 54.Kresse, G; Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys Rev B Condens Matter. 1996;54(16):11169–86. https://doi.org/10.1103/physrevb.54.11169DOIGOOGLE SCHOLAR
  55. 55.Kresse, G; Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys Rev B. 1999;59(3):1758–75. https://doi.org/10.1103/PhysRevB.59.1758DOIGOOGLE SCHOLAR
  56. 56.Tao, J; Perdew, JP; Ruzsinszky, A; Scuseria, GE; Csonka, GI; Staroverov, VN. Meta-generalized gradient approximation: non-empirical construction and performance of a density functional. Philos Mag. 2007;87(7):1071–84. https://doi.org/10.1080/14786430601021660DOIGOOGLE SCHOLAR
  57. 57.Heyd, J; Scuseria, GE; Ernzerhof, M. Hybrid functionals based on a screened Coulomb potential. J Chem Phys. 2003;118(18):8207–15. https://doi.org/10.1063/1.1564060DOIGOOGLE SCHOLAR
  58. 58.Mattsson, AE. Density functional theory. In pursuit of the “divine” functional. Science. 2002;298(5594):759–60. https://doi.org/10.1126/science.1077710DOIGOOGLE SCHOLAR
  59. 59.Car, R. Density functional theory: fixing Jacob’s ladder. Nat Chem. 2016;8(9):820–1. https://doi.org/10.1038/nchem.2605DOIGOOGLE SCHOLAR
  60. 60.Zhang, IY; Xu, X. On the top rung of Jacob’s ladder of density functional theory: toward resolving the dilemma of SIE and NCE. WIREs Comput Mol Sci. 2021;11(1). https://doi.org/10.1002/wcms.1490DOIGOOGLE SCHOLAR
  61. 61.Wu, J; Pun, SM; Zheng, X; Chen, G. Construct exchange-correlation functional via machine learning. J Chem Phys. 2023;159(9):90901. https://doi.org/10.1063/5.0150587DOIGOOGLE SCHOLAR
  62. 62.Perdew, JP; Schmidt, K. Jacob’s ladder of density functional approximations for the exchange-correlation energy. AIP Conf Proc. 2001;577(1):1–20. https://doi.org/10.1063/1.1390175DOIGOOGLE SCHOLAR
  63. 63.Sousa, SF; Fernandes, PA; Ramos, MJ. General performance of density functionals. J Phys Chem A. 2007;111(42):10439–52. https://doi.org/10.1021/jp0734474DOIGOOGLE SCHOLAR
  64. 64.Mardirossian, N; Head-Gordon, M. Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals. Mol Phys. 2017;115(19):2315–72. https://doi.org/10.1080/00268976.2017.1333644DOIGOOGLE SCHOLAR
  65. 65.Long, R; Prezhdo, OV. Ab initio nonadiabatic molecular dynamics of the ultrafast electron injection from a PbSe quantum dot into the TiO2 surface. J Am Chem Soc. 2011;133(47):19240–9. https://doi.org/10.1021/ja2085806DOIGOOGLE SCHOLAR
  66. 66.Tan, Y; Jin, S; Hamers, RJ. Influence of hole-sequestering ligands on the photostability of CdSe quantum dots. J Phys Chem C. 2013;117(1):313–20. https://doi.org/10.1021/jp309587kDOIGOOGLE SCHOLAR
  67. 67.Nadler, R; Sanz, JF. Effect of capping ligands and TiO2 supporting on the optical properties of a (CdSe)13 cluster. J Phys Chem A. 2015;119(7):1218–27. https://doi.org/10.1021/acs.jpca.5b00625DOIGOOGLE SCHOLAR
  68. 68.Rimal, G; Pimachev, AK; Yost, AJ; Poudyal, U; Maloney, S; Wang, W et al. Giant photocurrent enhancement by transition metal doping in quantum dot sensitized solar cells. Appl Phys Lett. 2016;109(10):103901. https://doi.org/10.1063/1.4962331DOIGOOGLE SCHOLAR
  69. 69.Rajbanshi, B; Sarkar, P. Optimizing the photovoltaic properties of CdTe quantum dot–porphyrin nanocomposites: A theoretical study. J Phys Chem C. 2016;120(32):17878–86. https://doi.org/10.1021/acs.jpcc.6b04662DOIGOOGLE SCHOLAR
  70. 70.Giberti, F; Vörös, M; Galli, G. Design of heterogeneous chalcogenide nanostructures with pressure-tunable gaps and without electronic trap states. Nano Lett. 2017;17(4):2547–53. https://doi.org/10.1021/acs.nanolett.7b00283DOIGOOGLE SCHOLAR
  71. 71.Gao, F; Yang, CL; Wang, MS; Ma, XG; Liu, WW. Theoretical studies on the possible sensitizers of DSSc: nanocomposites of graphene quantum dot hybrid phthalocyanine/tetrabenzoporphyrin/tetrabenzotriazaporphyrins/cis-tetrabenzodiazaporphyrins/tetrabenzomonoazaporphyrins and their Cu-metallated macrocycles. Spectrochim Acta A Mol Biomol Spectrosc. 2018;195:176–83. https://doi.org/10.1016/j.saa.2018.01.065DOIGOOGLE SCHOLAR
  72. 72.Sharma, V; Jha, PK. Enhancement in power conversion efficiency of edge-functionalized graphene quantum dot through adatoms for solar cell applications. Sol Energy Mater Sol Cells. 2019;200:109908. https://doi.org/10.1016/j.solmat.2019.04.030DOIGOOGLE SCHOLAR
  73. 73.Ray, S; Sahoo, MR; Mukherjee, S; Perumal, A; Nayak, SK; Bhaumik, S. Understanding the charge transfer mechanism in CsPbBr3 nanocrystals and nitrogen-doped carbon quantum dot heterostructures: effect of nanocrystal encapsulation. RSC Adv. 2023;13(50):35551–61. https://doi.org/10.1039/d3ra06307kDOIGOOGLE SCHOLAR
  74. 74.Cai, Q; Sheng, W; Yang, J; Zhong, Y; Xiao, S; He, J et al. Synergistic passivation and down‐conversion by imidazole‐modified graphene quantum dots for high performance and UV‐resistant perovskite solar cells. Adv Funct Materials. 2023;33(43). https://doi.org/10.1002/adfm.202304503DOIGOOGLE SCHOLAR
  75. 75.Nagal, V; Kumar, V; Jain, M; Saini, SK; Kumar, M; Singh, K et al. Slow cooling and transfer dynamics of hot excitons in CsPbBr3 perovskite quantum Dots/g-CN nanosheet heterostructures: implications for optoelectronic applications. ACS Appl Nano Mater. 2023;6(10):8894–906. https://doi.org/10.1021/acsanm.3c01374DOIGOOGLE SCHOLAR
  76. 76.Xu, Y; Ren, Y; Cheng, S; Zhang, L; Niu, P; Lyu, M et al. A residual strain regulation strategy based on quantum dots for efficient perovskite solar cells. J Mater Chem A. 2023;11(2):868–77. https://doi.org/10.1039/D2TA07593HDOIGOOGLE SCHOLAR
  77. 77.Li, Z; Yang, M; Li, L; Tu, Z; Song, L; Ding, B et al. Density functional theory analysis of structural and electronic properties of hexagonal hybrid perovskite (CH3NH3)3Bi2I9. Phys B. 2022;630:413695. https://doi.org/10.1016/j.physb.2022.413695DOIGOOGLE SCHOLAR
  78. 78.Zhang, Z; Li, X; Xia, X; Wang, Z; Huang, Z; Lei, B et al. High-quality (CH3NH3)3Bi2I9 film-based solar cells: pushing efficiency up to 1.64. J Phys Chem Lett. 2017;8(17):4300–7. https://doi.org/10.1021/acs.jpclett.7b01952DOIGOOGLE SCHOLAR
  79. 79.Pandey, N; Chakrabarti, S. First principle investigation of red-emitting CsPbI3 QDs with experimental details for solar device applications. Photonics for solar energy systems. SPIE. 2022;48–53. https://doi.org/10.1117/12.2620035DOIGOOGLE SCHOLAR
  80. 80.Li, Y; Li, X; Xu, Y. Grossly warped nanographene–phenothiazine nanocomposite as photoactive layer for solar cells: insights from theoretical study. Chem Phys Lett. 2021;773:138607. https://doi.org/10.1016/j.cplett.2021.138607DOIGOOGLE SCHOLAR
  81. 81.Xing, FL; Zhang, ZH; Yang, CL; Wang, MS; Ma, XG. First-principles investigations on the feasibility of the GQD-PEB/PUB nanocomposites as the sensitizer of DSSc. Chem Phys Lett. 2022;789:139306. https://doi.org/10.1016/j.cplett.2021.139306DOIGOOGLE SCHOLAR
  82. 82.Majid, A; Sana, M; Khan, SU; Ahmad, N. Time‐dependent density functional theory investigations on structural modification in carbazole‐based organic photosensitizers to improve electron injection in dye‐sensitized solar cell. Int J Quantum Chem. 2020;120(15). https://doi.org/10.1002/qua.26253DOIGOOGLE SCHOLAR
  83. 83.Jain, K; Kishor, S; Singh, KS; Josefsson, I; Odelius, M; Ramaniah, LM. Dye-sensitization of CdS nano-cage - A density functional theory approach. 2016. https://doi.org/10.1063/1.4947704DOIGOOGLE SCHOLAR
  84. 84.Don, CH; Shalvey, TP; Sindi, DA; Lewis, B; Swallow, JE; Bowen, L et al. Reactive DC sputtered TiO2 electron transport layers for cadmium‐free Sb2Se3 solar cells. Adv Energy Mater. 2024;14(34):2401077. https://doi.org/10.1002/aenm.202401077DOIGOOGLE SCHOLAR
  85. 85.Kumakura, K; Chen, CC; Sogabe, T. Electronic, optical, and temperature-dependent carrier mobility simulations of perovskite-type liganded PbS quantum dot array. Adv Condens Matter Phys. 2023;2023:1–10. https://doi.org/10.1155/2023/9580055DOIGOOGLE SCHOLAR
  86. 86.Yazdani, N; Andermatt, S; Yarema, M; Farto, V; Bani-Hashemian, MH; Volk, S et al. Charge transport in semiconductors assembled from nanocrystal quantum dots. Nat Commun. 2020;11(1):2852. https://doi.org/10.1038/s41467-020-16560-7DOIGOOGLE SCHOLAR
  87. 87.Fuhr, AS; Alexandrova, AN; Sautet, P. Stoichiometry-controllable optical defects in CuxIn2−xSy quantum dots for energy harvesting. J Mater Chem A. 2020;8(25):12556–65. https://doi.org/10.1039/D0TA03954CDOIGOOGLE SCHOLAR
  88. 88.Oh, JT; Bae, SY; Ha, SR; Cho, H; Lim, SJ; Boukhvalov, DW et al. Water-resistant AgBiS2 colloidal nanocrystal solids for eco-friendly thin film photovoltaics. Nanoscale. 2019;11(19):9633–40. https://doi.org/10.1039/c9nr01192gDOIGOOGLE SCHOLAR
  89. 89.Singh, D; Shukla, V; Khossossi, N; Hyldgaard, P; Ahuja, R. Stability of and conduction in single-walled Si2BN nanotubes. Phys Rev Materials. 2022;6(11). https://doi.org/10.1103/PhysRevMaterials.6.116001DOIGOOGLE SCHOLAR

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Arellano-Ramírez, I. D., Santiago, L. B., Rebaza, A. G., Amaya-Roncancio, S., & Restrepo-Parra, E. (2025). The Frontier of Solar Energy: Quantum Dots and Density Functional Theory Insights. Journal of Scientometric Research, 14(2), 424–436. https://doi.org/10.5530/jscires.20251270