Advances in Photovoltaic Materials and Devices Based on Two-Dimensional Systems and Nanomaterials for Solar Energy Conversion

Two-dimensional (2D) materials and nanomaterials have emerged as transformative candidates for next-generation photovoltaic (PV) and solar energy conversion technologies. Their fascinating crystal structures, tunable electronic properties, strong light–matter interactions, and exceptional charge transport characteristics offer unique opportunities for designing high-efficiency, stable, and cost-effective solar cell devices and modules. As global energy demands rise and the urgency for clean, low-cost energy solutions increases, 2D and nanoscale semiconductors provide an attractive route for advancing photovoltaic performance beyond the limits of conventional materials and architectures.

Recent developments in first-principles simulations, machine learning frameworks, and state-of-the-art experimental techniques have further accelerated the discovery, optimization, and understanding of PV behavior in these systems. These approaches enable predictive design of absorber materials, interfaces, and device architectures that directly impact solar energy conversion efficiency, operational stability, and scalability. Despite rapid progress, a comprehensive and integrated exploration of predictive theoretical modelling and/or experimental validation remains essential for identifying promising solar absorbers and translating them into high-performance PV devices and solar energy technologies.

This Research Topic aims to address the key scientific and technological challenges in identifying and optimizing high-efficiency photovoltaic (PV) materials and devices using advanced first-principles, machine learning, and experimental approaches. We seek contributions that collectively advance the predictive understanding and practical realization of next-generation solar energy conversion materials and device architectures.

Key Problems to Address:
- Limited understanding of structure–property–performance relationships in emerging 2D and nanoscale photovoltaic materials and their device implementations.
- Need for accurate prediction of band gaps, excitonic effects, and carrier dynamics linked to device-relevant metrics such as open-circuit voltage, short-circuit current, fill factor, and power conversion efficiency.
- Lack of integrated approaches combining first-principles, machine learning, and experimental validation for device-level optimization and materials screening.
- Existing solar materials and device technologies face limitations in efficiency, scalability, long-term stability, and cost-effectiveness.
- Challenges in identifying stable, high-performing absorber materials and interfaces suitable for commercial solar cell devices and modules.
What We Aim to Achieve:
- Leverage advanced first-principles methods (including hybrid functionals, GW approximation, and many-body approaches) for reliable PV predictions that directly inform device design and performance optimization.
- Utilize machine learning (including deep learning algorithms) to accelerate screening and discovery of 2D and nanomaterials for high-efficiency, stable solar energy conversion.
- Promote experimental synthesis, characterization, and prototype or functional device fabrication that demonstrate device-level performance and durability under realistic conditions.
- Encourage interdisciplinary strategies that bridge modelling, data-driven discovery, and synthesis/fabrication, linking fundamental properties to solar cell and module performance.
- Highlight promising materials, interfaces, and mechanisms that can enable next-generation, sustainable, high-efficiency photovoltaic technologies aligned with SDGs 7, 9, 11, and 13.

We invite submissions to our Research Topic that aim to identify high-efficiency, cost-effective, and sustainable solar cell materials and device concepts based on 2D systems and nanomaterials. This collection welcomes original research, reviews, and mini-reviews featuring first-principles modelling, machine learning-driven prediction, advanced experimental characterization, device and module design, or combined methods. Submissions in the following themes are particularly encouraged, but not limited to:
- Photovoltaic property prediction of 2D systems and nanomaterials using first-principles, machine learning, and experimental methods, with clear implications for solar cell device performance.
- Band-gap engineering, excitonic behavior, charge transport mechanisms, and light–matter interactions in emerging PV materials and their impact on solar energy conversion efficiency and stability.
- High-throughput screening and deep learning-based prediction of high-efficiency solar absorbers and device architectures.
- Stability, defect physics/chemistry, and interface engineering relevant to long-term device and module performance.
- Experimental synthesis, characterization, and prototype solar cell or module fabrication using 2D or nanoscale materials, including novel device architectures and scalable processing routes.
- Integrated computational–experimental frameworks for accelerating PV materials discovery and their translation into manufacturable solar technologies.

Additionally, the journal offers comprehensive fee-support options and institutional partnerships, enabling discounted or waived publication fees for eligible authors on a first-come, first-served basis. The invited works will be peer-reviewed and published within the standard journal timeframe.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Technology and Code

Keywords: photovoltaic, solar cells, 2D materials, nanomaterials, first-principles calculations, machine learning, experimental methods, solar energy conversion, device performance

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.