Evidence map›Paper›PMID 41068508›Full record

ReviewJournal of molecular modeling2025

Theoretical investigation into molecular level encapsulation and active layer strategies with carbon dot integration for micro-sized photovoltaic cell.

Azeez Ahamed, Piumantha Samaranayake, Lakshitha Madhushan, Muhammad Raziq Rahimi Kooh, K R Koswattage, Roshan Thotagamuge

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In one paragraph

Review in Journal of molecular modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Azeez AhamedCentre for Nano Device Fabrication and Characterization, Faculty of Technology, Sabaragamuwa University of Sri Lanka, Belihuloya, 70140 , Sri Lanka.
Piumantha SamaranayakeDepartment of Physics, Faculty of Science, University of Ruhuna, Matara, 81000, Sri Lanka.
Lakshitha MadhushanCentre for Nano Device Fabrication and Characterization, Faculty of Technology, Sabaragamuwa University of Sri Lanka, Belihuloya, 70140 , Sri Lanka.
Muhammad Raziq Rahimi KoohCentre for Advanced Material and Energy Sciences, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, BE, 1410, Brunei Darussalam.
K R KoswattageCentre for Nano Device Fabrication and Characterization, Faculty of Technology, Sabaragamuwa University of Sri Lanka, Belihuloya, 70140 , Sri Lanka. koswattagekr@appsc.sab.ac.lk.
Roshan ThotagamugeDepartment of Optometry, Faculty of Allied Health Sciences, University of Sri Jayewardenepura, Nugegoda, 10250, Sri Lanka. roshan@sjp.ac.lk.

Funding

the Science and Technology Human Resource Development Project, Ministry of Education, Sri Lanka, funded by the Asian Development Bank CRG-R2-SB-1
6 · The paper itself

Abstract

contextThis s tudy explores the potential of functionalized carbon dots (CDs) for integration into the encapsulation and active layers of micro-sized photovoltaic cells (PVCs), with a focus on applications in renewable energy, biomedical devices, optoelectronics, and environmental sensors. Traditional photovoltaic materials such as perovskites and organic polymers, while efficient, pose challenges related to toxicity and environmental instability. In contrast, CDs derived from biocompatible sources offer enhanced safety and sustainability due to their high quantum yield, photostability, and tunable optical properties. Among the variants studied, amide-functionalized carbon dots (CD-CONH₂) were found optimal for encapsulation when paired with graphene (Gr-CD-CONH₂), while nitrogen-doped CD-CONH₂ (CD-CONH₂/N), integrated with silicon quantum dots (Si-CD-CONH₂/N), demonstrated superior characteristics for active layer performance. Key results include high HOMO-LUMO energy gaps of 3.50 eV (vacuum) and 3.48 eV (water) for CD-CONH₂, and 2.11-2.15 eV for Si-(CD-CONH₂/N), along with strong dipole moments and negative formation energies, indicating stability and efficiency across environments. These findings suggest that Gr-(CD-CONH₂) and Si-(CD-CONH₂/N) composites are promising materials for enhancing the environmental sustainability and performance of next-generation micro-sized PVCs.

methodsAll theoretical simulations were performed using Gaussian 09W. Geometry optimizations and frequency analyses of functionalized CDs (-OH, -NO₂, -NH₂, -COOH, -CONH₂, -CHO) were conducted using the B3LYP-D3BJ functional with the 6-311G(d) basis set. Frequency analyses confirmed convergence by the absence of imaginary frequencies. Time-dependent DFT (TD-DFT) calculations were employed for UV-Vis spectral analysis using the TD-SCF method, with solvent effects modeled via the SMD approach (water as solvent). Water was selected as the solvent because our theoretical PVC model is intended to have potential biomedical relevance in non-invasive photodynamic treatments. In this context, water serves as a representation of the physiological environment of the human body. All TD-SCF calculations were done using default Gaussian settings for 10 excited states. Visualization and input generation were performed using GaussView 6.0. Encapsulation studies involving CD-CONH₂ and graphene were initially modeled using AutoDock Vina (SwissDock) to determine optimal binding poses, followed by full DFT optimization in Gaussian 09W. Adsorption and solvation energies were computed using standard DFT protocols. For active layer modeling, the Si-(CD-CONH₂/N) composite underwent similar optimization and TD-DFT analysis. Reactivity descriptors (chemical hardness, softness, chemical potential, and electrophilicity) were derived from HOMO-LUMO energies. Additional analyses such as transition density matrix (TDM), electrostatic potential (ESP) maps, and electron localization function (ELF) were performed using Multiwfn (version 3.8) to further evaluate electronic structure and stability of the composites.

Indexed as

Encapsulation and active layer material for photovoltaic cellFunctionalized carbon dotsMicro-sized photovoltaic cellPhotovoltaic material stabilityUV–vis spectra

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.