- PCE
- FF
- Voc
- Jsc
- Rs
- Rsh
- Hysteresis
- Batch analysis
- AI interpretation
Guided Learning Path
Follow this sequence to move from semiconductor fundamentals to a complete, publication-ready device and energy-level diagram.
Learning Objectives
Introduction
Modern photovoltaic devices are multilayer structures in which light absorption, charge generation, carrier selection, transport, and collection are distributed across different functional materials. The sequence of the substrate, transparent conducting electrode, electron-transport layer, absorber, hole-transport layer, interfacial layers, and counter electrode strongly influences charge extraction and recombination.
This Community Edition provides an interactive environment for constructing and comparing representative perovskite solar cells (PSCs), organic solar cells (OSCs/OPVs), and dye-sensitized solar cells (DSSCs). Users can modify layer order and material parameters, then generate a device-structure illustration and a vacuum-referenced energy-level diagram.
Perovskite Solar Cells
PSCs use a metal-halide perovskite absorber between charge-selective contacts. Both conventional n-i-p and inverted p-i-n architectures are widely studied, along with printable carbon-electrode configurations.
Organic Solar Cells
OSCs commonly use donor–acceptor blends. Photoexcitation produces bound electron–hole pairs, and suitable donor–acceptor energy offsets assist charge separation and selective extraction.
Dye-Sensitized Solar Cells
DSSCs combine a dye-sensitized wide-bandgap semiconductor, a redox electrolyte, and a counter electrode. Electron injection and dye regeneration depend on the relative energy levels of these components.
Theory and Scientific Background
1. Vacuum-referenced energy scale
The diagram uses the vacuum level, Evac = 0 eV, as the common reference. Electron energies in a solid are therefore shown as negative values below vacuum. For a semiconductor with electron affinity χ and bandgap Eg, this toolkit estimates:
Here EC represents the conduction-band minimum for inorganic semiconductors or an approximate LUMO level for organic materials; EV represents the valence-band maximum or an approximate HOMO level.
2. Work function and Fermi level
The work function Φ is the energy needed to move an electron from the Fermi level to vacuum. The toolkit therefore places the approximate Fermi level at:
For conductors and electrodes, the displayed horizontal level is based primarily on the work function. Actual values can vary with surface treatment, composition, doping, crystal orientation, contamination, and measurement method.
3. Interfacial band offsets
At an interface between adjacent semiconductor layers 1 and 2, the electron and hole energy discontinuities are represented as:
These offsets help users identify possible extraction barriers and carrier-blocking behavior. A favorable contact should facilitate transport of the desired carrier while suppressing the opposite carrier; however, performance cannot be predicted from offsets alone because defects, dipoles, recombination kinetics, mobility, doping, and morphology are also important.
4. Built-in potential and schematic band bending
When contacts with different work functions form a device, charge redistribution can establish an internal electrostatic potential. The toolkit uses the contact work-function difference as a simple estimate:
Because work functions entered in electron-volts have the same numerical difference as volts per elementary charge, the displayed estimate is numerically the work-function difference in volts. The adjustable band-bending factor applies a schematic linear potential shift across the stack for visualization.
5. Interpretation of the three device families
- PSC: photons generate free or weakly bound carriers in the perovskite absorber; electron- and hole-selective layers direct carriers toward opposite electrodes.
- OSC: excitons generated in donor or acceptor phases reach a donor–acceptor interface, where energetic driving forces and local electric fields support charge-transfer-state formation and separation.
- DSSC: an excited dye injects an electron into the semiconductor conduction band; the oxidized dye is regenerated by the redox mediator, which is then regenerated at the counter electrode.
Representative Materials Database
The values below are the editable starting values used by this Community Edition. They are representative—not universal—and can vary with composition, fabrication, doping, surface treatment, morphology, and measurement method.
| Material | Function | Typical thickness (nm) | Work function (eV) | Electron affinity χ (eV) | Bandgap Eg (eV) |
|---|---|---|---|---|---|
| FTO | Transparent conductor | 500 | 4.40 | 4.00 | 3.50 |
| ITO | Transparent conductor | 150 | 4.70 | 4.50 | 3.70 |
| SnO₂ | Electron-transport layer | 35 | 4.50 | 4.00 | 3.60 |
| TiO₂ | Electron-transport layer | 50–180 | 4.20 | 4.00 | 3.20 |
| MAPbI₃ | Perovskite absorber | 500 | 4.80 | 3.90 | 1.55 |
| CsFAMA perovskite | Perovskite absorber | 550 | 4.80 | 3.95 | 1.58 |
| PM6:Y6 | Organic donor–acceptor absorber | 110 | 4.70 | 3.90 | 1.40 |
| PTAA | Hole-transport layer | 20 | 5.20 | 2.20 | 3.00 |
| Spiro-OMeTAD | Hole-transport layer | 180 | 5.10 | 2.20 | 3.00 |
| NiOₓ | Hole-transport layer | 30 | 5.20 | 1.90 | 3.70 |
| Carbon | Electrode | 10,000 | 5.00 | 4.80 | 0.00 |
| Au / Ag / Al | Metal electrode | 80–100 | 4.30–5.10 | — | 0.00 |
Use the Layer Stack Editor to replace these defaults with values appropriate to your own materials and cited experimental conditions.
Device Templates
Layer Stack Editor
| Type | Material | t nm | WF | χ | Eg | Color |
|---|
Figure Settings
Calculated Metrics
AI-Style Interpretation
Research-Quality Layer Structure
Research-Quality Energy Band Diagram
1. Choose a template
Review the Introduction and Theory, then select an n-i-p PSC, p-i-n PSC, carbon PSC, OSC, or DSSC architecture to load a complete starting structure.
2. Edit the device stack
Change layer order, material, thickness, work function, electron affinity, bandgap, and display colour. Drag rows to reorder layers.
3. Generate and export
Update the structure and energy-band diagrams, review calculated metrics and interpretation, then export SVG, PNG, JSON, or PDF.
Interactive Concept Explorer
Select a term to review its role in the diagram and in photovoltaic device operation.
The explanation will appear here without leaving the simulation.
Upgrade beyond the Community Edition
Access expanded materials, advanced analysis, project management, enhanced AI interpretation, and professional licensing.
Searchable Glossary
Release Notes
Version 1.3 — Related Toolkits Expansion
Added User Guide to the primary navigation and expanded the Related NexSolveAI Research Toolkits™ section with Toolkits 02–06 for electrical, transient, optical, and photoluminescence characterization.
Version 1.2 — Learning Platform Update
Added guided learning path, learning objectives, materials database, concept explorer, searchable glossary, related-toolkit cards, suggested citation, expanded About information, and clearer model limitations.
Version 1.1 — Navigation and Theory Update
Added professional navigation, introduction, scientific theory, selected references, user guide, responsive layout, and edition-upgrade section.
Selected References and Further Reading
- M. A. Green, A. Ho-Baillie, and H. J. Snaith, “The emergence of perovskite solar cells,” Nature Photonics, 8, 506–514 (2014). DOI
- A. Kojima, K. Teshima, Y. Shirai, and T. Miyasaka, “Organometal halide perovskites as visible-light sensitizers for photovoltaic cells,” Journal of the American Chemical Society, 131, 6050–6051 (2009). DOI
- B. O’Regan and M. Grätzel, “A low-cost, high-efficiency solar cell based on dye-sensitized colloidal TiO₂ films,” Nature, 353, 737–740 (1991). DOI
- C. Deibel and V. Dyakonov, “Polymer–fullerene bulk heterojunction solar cells,” Reports on Progress in Physics, 73, 096401 (2010). DOI
- B. A. Gregg, “Excitonic solar cells,” Journal of Physical Chemistry B, 107, 4688–4698 (2003). DOI
- U.S. Department of Energy, “Perovskite Solar Cells” and “Perovskite Research Directions.” DOE overview
- National Renewable Energy Laboratory, “Organic Photovoltaic Solar Cells.” NREL overview
- S. M. Sze and K. K. Ng, Physics of Semiconductor Devices, 3rd ed., Wiley (2007), for work functions, energy bands, junction electrostatics, and carrier transport.
References provide foundational background. The material parameters embedded in the toolkit are representative values and are not claimed to reproduce a single measurement condition or publication.
About, License, and Citation
Toolkit Scope
Browser-based structure design and vacuum-referenced energy-level visualization for organic, perovskite, carbon-based, and dye-sensitized solar cells.
Community License
Designed for personal learning, classroom demonstrations, preliminary research visualization, and evaluation of the NexSolveAI platform. Confirm licensing before commercial use.
Version and Author
NexSolveAI Research Toolkit™ 01 Community Edition v1.2, developed by Dr. Muhammad Hassan Sayyad.
Suggested Citation
Scientific-use notice
The generated band diagrams are schematic, vacuum-referenced design aids. They do not replace experimentally measured energy levels, interface-specific characterization, or full semiconductor/electrochemical device simulation. Cite the source of any parameter values used in scholarly work.
Edition Comparison
Compare Community, Research and Professional Editions of NexSolveAI Research Toolkit™ 01
| Feature |
Community Edition FREE |
Research Edition Request Quote |
Professional Edition Request Quote |
|---|---|---|---|
Device Structure Builder | ✓ | ✓ | ✓ |
Pre-built Device Templates | 5 Templates | Unlimited | Unlimited |
Material Database | Basic (~40 materials) | Comprehensive (100+ materials) | Comprehensive (100+ materials) |
Custom Material Entry | ✓ | ✓ | ✓ |
Energy Band Diagram | ✓ | ✓ | ✓ |
Interface Analysis | ✕ | ✓ | ✓ |
Contact & Barrier Analysis | ✕ | ✓ | ✓ |
Carrier Flow Visualization | ✕ | ✓ | ✓ |
Device Comparison | ✕ | ✓ (Up to 10 devices) | ✓ (Unlimited) |
Parameter Sweeps | ✕ | ✓ | ✓ |
Design Validation & Scoring | Basic | Advanced | Advanced + AI Insights |
AI-Powered Research Reports | Basic | Advanced | Expert with Explanations |
Export (SVG, PNG, CSV, JSON) | SVG, PNG | SVG, PNG, CSV, JSON | SVG, PNG, CSV, JSON + Report (PDF) |
Optical Simulation | ✕ | ✕ | ✓ |
Drift–Diffusion Simulation | ✕ | ✕ | ✓ |
J–V & EQE Simulation | ✕ | ✕ | ✓ |
Optimization & AI Design Assistant | ✕ | ✕ | ✓ |
Experimental Data Fitting | ✕ | ✕ | ✓ |
Priority Support | Community Forum | Email Support | Priority Email + Live Support |
Commercial / Research Use | Non-commercial only | ✓ Allowed | ✓ Allowed |
License | Personal / Educational | Commercial Research License | Commercial / Enterprise License |