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Description
1. What is QFLS?Ā
Definition: QFLS (Quasi-Fermi Level Splitting) represents the “internal voltage upper limit” of a material under illumination, directly reflecting internal non-radiative recombination losses.
Detailed Explanation: QFLS describes the non-equilibrium energy level distribution between electrons and holes under illumination. It is a quantitative physical indicator, numerically equivalent to the maximum open-circuit voltage (iVoc) achievable by the material in an ideal state (without resistive losses).
- Visualized Quality Map: Through QFLS imaging, you can intuitively observe the “quality distribution” within the materialāregions with higher QFLS values indicate lower defect density and minimized non-radiative recombination losses.
- Predictive Potential: This allows researchers to foresee the material’s efficiency potential before device fabrication is completed.
2. What is Pseudo J-V?
Definition: Pseudo J-V is an “ideal J-V curve” that excludes the influence of series resistance (Rs), used to predict the theoretical efficiency limit of the device.
Detailed Explanation: Unlike traditional electrical J-V curves, Pseudo J-V is derived utilizing optical data (PLQY and QFLS). It is unaffected by device structure (such as poor electrode contact or transport layer resistance), thereby reflecting the “limiting performance” of the photovoltaic material itself.
- Application Value: Overlay and compare the Pseudo J-V with the Real J-V curve.
- Basis for Judgment: A high degree of overlap indicates an ideal fabrication process; a significant discrepancy (e.g., a drop in Fill Factor, FF) demonstrates that the issue originates from contact resistance or transport layers, rather than the material itself. This assists in rapidly screening high-potential recipes and reducing experimental trial-and-error costs.
3. Core Value: Why QFLS-Maper?
Core Value: Traditional electrical measurements only indicate low efficiency; QFLS-Maper visualizes “where voltage is lost” and “why efficiency drops.”
Detailed Explanation: QFLS-Maper integrates high-throughput imaging technology, completing a full-field scan in under 3 seconds. It addresses the limitation of traditional single-point testing by converting invisible voltage loss (Voc Loss) into high-resolution images.
- Where is voltage lost? Through QFLS Mapping, locate low-voltage hotspots at sample edges or local regions.
- Why does efficiency drop? By combining PL/EL imaging with Pseudo J-V analysis, quickly clarify whether efficiency loss stems from “internal material defects” or “interface energy level mismatch (Energy Alignment),” accelerating the R&D iteration cycle.
Learn More! How does QFLS determine the efficiency limit of your PV devices? A comprehensive guide from theory to measurement!
Features
Predict Material Performance Limits
3-Second Imaging: Acquire high-resolution QFLS visualization images in just 3 seconds, directly revealing internal material uniformity and defect distribution.
2-Minute Prediction: Measure the Pseudo J-V Curve in just 2 minutes to predict the theoretical efficiency limit and iVoc prior to device fabrication.
Visualize
QFLS Image visually displays the overall Quasi-Fermi level distribution in materials, revealing material quality at a glance
Multi-Modal Functionality
Capable of measuring key solar cell parameters including QFLS, iVoc, Pseudo jv, PL image, PLQY, EL image, EL-EQE, and more
Comparison: QFLS-Maper vs. Traditional Detection
Traditional electrical measurements only inform you that “efficiency is low” without explaining the underlying causes; meanwhile, conventional PL imaging, while showing intensity contrast, cannot quantify “how much voltage is lost.” QFLS-Maper overcomes these limitations through Full-Field Scanning technology. It not only visualizes material uniformity but also directly calculates the theoretical efficiency limit excluding resistance effects. Below is a comprehensive comparison between QFLS-Maper and traditional detection methods:
| Comparison Dimension | Traditional PL Detection | QFLS-Maper Quasi-Fermi Level Detector |
|---|---|---|
| Core Metric | Intensity Measures only relative fluorescence counts (Counts / a.u.); lacks absolute physical significance. | Quasi-Fermi Level Splitting (QFLS / iVoc) Converts fluorescence signals into absolute voltage values (Volts / eV), representing the theoretical upper limit of the device’s open-circuit voltage. |
| Data Comparability | Qualitative Analysis Data is highly dependent on sample thickness, surface roughness, and geometric collection angles, making objective cross-batch comparison difficult. | Quantitative Analysis Based on thermodynamic principles and absolute PLQY calibration; excludes geometric interference, allowing direct comparison across samples and processes. |
| Detection Speed | Slow / Point Measurement Traditional spectral point acquisition or raster scanning; usually requires time-consuming manual post-processing to convert to QFLS. | Extremely Fast / Full-Field Scanning ā¢ QFLS Imaging: < 3 seconds ā¢ Pseudo J-V Prediction: < 2 minutes |
| Visualization | Intensity Contrast Map Displays only brightness distribution; cannot directly assess the magnitude of voltage loss. | Voltage Loss Map (Voc Loss Map) Visually presents potential distribution, precisely showing the “spatial distribution of voltage loss” and “causes of efficiency drops.” |
| Efficiency Prediction | None / Manual Calculation Typically does not directly output device efficiency predictions. | Built-in Pseudo J-V Automatically generates an ideal J-V curve excluding series resistance effects, predicting the efficiency limit and Fill Factor (FF) potential. |
| Application Depth | Surface Quality Inspection Mainly observes the quantity of defects (e.g., dark spots, cracks). | Loss Analysis Distinguishes whether loss originates from “intrinsic material properties (non-radiative recombination)” or “contact interfaces (transport layer issues).” |
| Data Output | Raw Spectrum, Intensity Image. | QFLS Map, iVoc Value, Pseudo J-V Curve, PLQY, EL-EQE, Raw Spectrum. |
QFLS Related articles
Specifications
| Item | Specification |
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| Spectral Detection Range |
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| Optical Intensity Dynamic Range |
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| Intensity Control |
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QFLS-Maper transcends the limitation of traditional imaging that only “sees intensity,” translating abstract fluorescence signals into concrete electrical metrics through rigorous photophysical models. To assist you in precisely interpreting test data, the following core system output parameters and their practical value in material screening and device optimization are defined below:
| Term | Full Name | Standardized Definition | Application Value |
|---|---|---|---|
| QFLS (Value) | Quasi-Fermi Level Splitting Value | Describes the energy difference (eV) of the non-equilibrium energy level distribution between photogenerated carriers (electrons and holes) under illumination. |
Theoretical Basis: Directly quantifies the thermodynamic voltage potential of the material; it is the core physical quantity for calculating iVoc. |
| QFLS Image | Quasi-Fermi Level Splitting Image | Uses fluorescence imaging technology to convert QFLS values at each point of the sample into a visualized false-color map. |
Visualization: Assess overall material uniformity at a glance; quickly locate edge defects, low-voltage dead zones, and hotspots. |
| iVoc | Implied Open-Circuit Voltage | The theoretical open-circuit voltage derived from QFLS values. |
Screening: The gold standard for assessing perovskite film quality, reflecting the material’s maximum voltage output capability under ideal conditions. |
| Pseudo J-V | Pseudo Current-Voltage Curve | An “ideal current-voltage curve” free from series resistance effects, derived from PLQY and QFLS data. |
Prediction: Predicts the theoretical efficiency upper limit of the device. Comparing with Real J-V allows precise diagnosis of FF losses caused by transport layer resistance. |
| PLQY | Photoluminescence Quantum Yield | Defined as the ratio of emitted photons to absorbed photons. |
Quantification: Directly quantifies the degree of Non-radiative recombination; higher values indicate fewer defects. |
| PLQY Image | PLQY Image | Spatial imaging of PLQY values, showing the distribution of luminescence efficiency across the sample surface. |
Defect Mapping: Intuitively displays the spatial location of non-radiative recombination centers; determines if issues are local point defects or large-area uniformity problems. |
| EL-EQE | Electroluminescence Quantum Efficiency | Measures the ratio of emitted photons to injected electrons under electrical bias. |
Injection Efficiency: Evaluates carrier injection capability and recombination status in finished devices. |
| EL Image | Electroluminescence Image | Luminescence image of the device captured under electrical excitation. |
Device Diagnostics: Used to inspect process defects such as poor electrode contact, cracks, and local shunts. |
| In Situ PL | In Situ Time-Resolved PL | In-situ fluorescence spectrum or image monitoring of samples over time. |
Dynamic Analysis: Monitors degradation processes or phase segregation behavior of materials under illumination or environmental stress. |
System Design
Applications
Applicable Samples
- Single-junction / Tandem Perovskite Solar Cells
- Perovskite Films & Half-cells
- Novel Photovoltaic Materials & Passivation LayersĀ
1. Target Audience & Value
QFLS-Maper is designed for material scientists and device engineers in the photovoltaic field, offering standardized testing solutions ranging from “basic material screening” to “comprehensive device failure analysis.”
| Target Audience | Sample Type | Analysis Purpose & Value |
|---|---|---|
| Material Scientists | Thin Films / Half-cells | Assess Intrinsic Material Quality & Passivation: Directly measure defect density and carrier lifetime potential of perovskite layers without fabricating complete devices. Quantify the maximum open-circuit voltage (iVoc) of the material in an ideal state using QFLS values. |
| Device Engineers | Complete Devices / Modules | Identify Structural Defects & Interface Losses: Evaluate electrical performance within the complete cell structure. specifically used to diagnose extra Voc losses caused by poor contact of transport layers (ETL/HTL), energy level mismatch, or interface recombination. |
2. Typical R&D Workflows: From Screening to Diagnosis
QFLS-Maper provides physically meaningful standardized testing logic for different R&D stages, assisting researchers in making rapid decisions.
Workflow 1: Film Recipe Screening
- Scenario: Rapidly assess the quality of the perovskite absorber layer itself without fabricating a complete battery.
- Operational Logic:
- Sample Prep: Place the film sample deposited on glass (Glass/Perovskite) onto the stage.
- Data Acquisition: Scan to acquire QFLS images and PLQY values.
- Decision Basis: Directly read the iVoc (Implied Open-Circuit Voltage). If the value is lower than expected, it indicates excessive internal defect density; adjust the precursor recipe or annealing process without proceeding to subsequent transport layer deposition.
Workflow 2: Layer-by-Layer Interface Optimization
- Scenario: Determine if the Electron Transport Layer (ETL) or Hole Transport Layer (HTL) matches the perovskite energy levels, or if it causes interface recombination losses.
- Operational Logic: Adopt a Layer-by-layer Testing strategy to compare value changes before and after stacking:
- Baseline: First measure the QFLS value of the pure perovskite layer (Glass/PVK).
- Stack Test: Measure the sample after covering it with a transport layer (e.g., Glass/ETL/PVK).
- Decision Basis: If the QFLS value drops significantly after stacking (compared to the baseline), it indicates that the transport layer has introduced severe interface non-radiative recombination; replace the transport material or perform interface passivation.
Workflow 3: Device Loss Analysis
- Scenario: The actual cell efficiency (PCE) is lower than expected, and clarification is needed on whether it is due to “poor material” or “poor electrode contact.”
- Operational Logic:
- Theoretical Limit Measurement: Use QFLS-Maper to measure the device’s Pseudo J-V Curve (ideal curve excluding resistance effects).
- Difference Comparison: Import the device’s Real J-V data.
- Decision Basis:
- If the two curves highly overlap: The device structure is good; the efficiency bottleneck lies in recombination losses within the material itself (return to Workflow 1 to optimize the recipe).
- If the Fill Factor (FF) of Real J-V is significantly lower than Pseudo J-V: The material is fine; losses mainly stem from series resistance (Rs) or carrier transport barriers (optimize electrode contact or transport layer conductivity).
QFLS Related research
Customer testimonials
Publication
Yttrium oxide engineered substrate enables improved durability for perovskite solar cells
Haibing Wang, Yansong Ge, Wenlong Shao, Xingyu Xiong, Guang Li, Nengxu Li, Xuzhi Hu, Guoyi Chen, Kailian Dong, Wei Ai, Zixi Yu, Zhimiao Zheng, Chen Wang, Fang Yao, Xiaojuan Cao, Songzhan Li, Jianwei Zhao, Weijun Ke, Chen Tao, Yi Hou, Annamaria Petrozza & Guojia Fang
Published: 28 October 2025 https://doi.org/10.1038/s41467-025-64548-y
ā¦ The characterization of quasi-Fermi level splitting (QFLS) was conducted by QFLS-Maper (Enli Technology Co., Ltd). ā¦
Reference toļ¼QFLS-Maper
Unveiling the Myths of Co-Deposition of Hole Conductors and Perovskite Layers
Xi Yang, Kaifeng Jing, Hengyu Zhang, Qianyi Li, Dongyang Li, Patrick W. K. Fong, Zhenyi Ni, Zi Jing Wong, Gang Li, Guang Yang
First published: 08 December 2025 https://doi.org/10.1002/smll.202513227
ā¦ The EQE measurements were conducted using a QE-R3011 system from Enli Technology Co. The QFLS measurements were performed using a QFLS-Maper from Enli Technology Co. … recorded by an LED photoluminescence quantum yield measurement system (Enli Tech LQ-100) equipped with a Keithley 2400 Source Measure Unit.
Reference toļ¼QFLS-Maper, QE-R, LQ-100
QFLS-Maper FAQ & Selection Guide
This guide outlines the core capabilities, measurement principles, and data interpretation methodologies of the QFLS-Maper, helping you evaluate its application in photovoltaic material screening and device optimization workflows.
Core Functions & Applications
What main problems does QFLS-Maper solve? Why do I need it?
Core Value: Accelerate material screening and defect localization.
Traditional electrical measurements only indicate that the efficiency is low. QFLS-Maper uses imaging technology to directly show you “where the voltage (Voc) is lost” and “why the efficiency is compromised.” By integrating QFLS (Quasi-Fermi Level Splitting), PLQY, and PL/EL imaging, it visualizes non-radiative recombination losses instantly. This eliminates the “blind spots” of single-point measurements, allowing you to directly assess the true uniformity of formulation adjustments, passivation quality, and process upscaling.Ā
How long does a measurement take? Is it suitable for High-Throughput (HTP) screening?
Yes. The system is designed for the fast-paced iteration of R&D.
For single-point or fast imaging modes, typical output time is on the order of 3 seconds. High-resolution, large-area mapping is typically completed within minutes. This means you can screen tens to hundreds of samples in a single day, rapidly building a “Process Parameters vs. Optoelectronic Quality” database and significantly shortening the exploration of the Process Window.
Can QFLS-Maper measure both films and devices?
Yes, both are supported but serve different purposes:
- Films: Used to evaluate intrinsic material quality and passivation efficacy. Examples include defect density or carrier lifetime potential in perovskite layers.
- Devices: Used to evaluate electrical performance of the full stack. It is particularly useful for localizing extra voltage losses caused by poor contact or interface recombination at the transport layers (ETL/HTL).
Technical Principles & Data Interpretation
What is a QFLS Map? How does it differ from a standard PL image?
PL shows “Intensity,” whereas QFLS Map shows “Voltage Potential.”
Standard Photoluminescence (PL) intensity is easily affected by sample thickness, surface roughness, or optical extraction efficiency, making cross-sample comparison difficult. A QFLS Map is based on thermodynamic principles, converting the fluorescence signal into a “Quasi-Fermi Level Splitting” valueāessentially the internal voltage limit achievable at open circuit for that specific pixel. This is a quantitative physical metric that allows for objective comparison of Voc potential and non-radiative loss distribution across different batches and process conditions.
What is Pseudo J-V (Implied J-V)? How does it help R&D?
It is an ideal J-V curve excluding the influence of series resistance.
Pseudo J-V uses optical signals to infer the theoretical current-voltage characteristics of a device without the impact of series resistance (Rs).
- Application Scenario: When measured efficiency (PCE) is low, compare the Pseudo J-V with the actual J-V curve. High overlap indicates the issue lies in material recombination; a large gap (e.g., significantly lower FF) suggests contact resistance or carrier transport barriers. This helps you quickly decide whether to “modify the formulation” or “fix the interface.”
When should I use PL? When should I use EL?
The system supports both modes; switch based on your testing goals:
- PL (Photoluminescence): Non-contact measurement. Ideal for inspecting material quality, crystallization uniformity, and passivation defects at the half-cell or film stage.
- EL (Electroluminescence): Contact measurement (requires current injection). Ideal for checking injection efficiency, electrode contact quality, and identifying localized hotspots or shunt paths in finished devices.
Under what circumstances might PLQY-derived QFLS be inaccurate?
This typically occurs in samples that do not adhere to the “Detailed Balance Principle” or “Reciprocity Relation.”
Common interfering factors include:
- Phase Separation: The appearance of low-bandgap enrichment regions in mixed-halide perovskites.
- Charge Funneling: Carriers being guided to specific emission centers, decoupling emission efficiency from the global carrier concentration.
In these extreme physical scenarios, the conversion formula between optical readings and electrical potential may require correction. Careful evaluation referencing spectral characteristics is required.Ā Ā
Output Specs & Purchasing Assessment
What charts and data does the QFLS-Maper output?
To facilitate downstream analysis and publication, the system provides multi-layered data formats:
- Image Data (Maps): QFLS Map, Voc loss Map, PL/EL Intensity Map.
- Quantitative Data: Absolute spectral data, PLQY values, Pseudo J-V curve parameters (i-Voc, i-FF).
- Raw Files: Supports export of CSV and common image formats, ready for secondary processing in Origin, Python, or MATLAB.
How do I assess if this system is suitable for my lab?
You only need to confirm the following 4 requirements, and we can assist in the assessment:
- Sample Type: Pure films, half-cells, or fully encapsulated devices?
- Size Range: Standard lab coupons (e.g., 1×1 cm) or module-scale large areas?
- Target Bandgap: The energy gap range of your materials (e.g., Perovskite, Silicon, CIGS, or Tandems).
- Key Metric: Is your primary goal to “boost Voc,” “improve uniformity,” or “analyze FF losses”?Ā Ā
Expert View
How to utilize QFLS-Maper to find the root cause of Voc loss?
We recommend a three-step analysis approach: “Locate ā Analyze Spectra ā Correlate”:
- Locate: First, view the QFLS Map and identify the Region of Interest (ROI) with voltage deficits.
- Analyze Spectra: Compare the PL spectra and Pseudo J-V differences between the ROI and normal areas to determine if it’s a defect density issue (low PLQY) or a bandgap shift.
- Correlate: Perform regression analysis on image features against process parameters (e.g., annealing temperature, spin speed) to pinpoint the specific process variable causing the non-uniformity.
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