Keithley Dual SMU Parameter Analyzer - Software Description A Python-based graphical interface for electrical characterization using Keithley 26xx dual-channel sourcemeters. This software enables automated measurement and analysis of photovoltaic devices, transistors, and neuromorphic/memristive devices with advanced data processing and visualization capabilities. Core Functionalities 1. Current-Voltage (IV) Characterization Automated JV sweeps with configurable voltage range, step size, and measurement speed (NPLC) Multi-curve overlay plotting for comparative analysis Dual y-axis visualization showing current density and power density simultaneously Semilog plotting mode for analyzing devices across wide current ranges Hysteresis measurement with configurable forward/reverse sweep cycles Dark and illuminated measurements with photovoltaic parameter extraction 2. Photovoltaic Device Analysis Automatic PV parameter extraction: Open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF), and power conversion efficiency (PCE) Interpolation-based Voc calculation for improved accuracy Configurable irradiance settings (W/m²) for standardized testing Batch processing with multi-sample storage and CSV export 3. Transistor Characterization Automated gate-voltage sweep measurements for OFET/TFT devices Dual-channel operation with independent gate and drain control Output characteristics generation with multi-Vgs curve families Transfer curve analysis with data export capabilities 4. Neuromorphic Synapse Characterization Pulse-read sequences for electrical, optical, and memristor-based synapses Configurable stimulus parameters: voltage/current drive, pulse width, period, and amplitude Real-time conductance monitoring across pulse trains Synaptic metrics calculation: Paired-pulse facilitation (PPF), conductance change (ΔG), potentiation/depression quantification Safety checks for high-voltage operations 5. Spike-Rate-Dependent Plasticity (SRDP) Frequency sweep characterization (linear or logarithmic scaling) Rate-dependent learning curves showing ΔG vs. spike frequency Configurable frequency range (0.1 Hz - 1 kHz+) Multi-point analysis with automated data collection 6. Spike-Timing-Dependent Plasticity (STDP) Timing-dependent plasticity window measurement Pre-post spike pair generation with precise Δt control Bidirectional plasticity characterization (LTP/LTD regions) STDP curve plotting with automatic LTP/LTD region annotation 7. Simulation Mode Hardware-free testing with physics-based device models Exponential conductance change simulation for memristive behavior Realistic noise injection for measurement validation SRDP and STDP simulation engines for protocol development 8. Instrument Communication Multi-interface support: GPIB, RS-232, and LAN/Ethernet Automatic timeout management based on measurement parameters 4-wire and 2-wire sensing modes Current compliance protection (100 nA to 1.5 A range) Autorange capabilities for current measurement 9. Data Management CSV export with embedded metadata headers Multi-sample batch storage with unique cell identifiers Derived metrics calculated and stored automatically Timestamp tracking for temporal analysis Parameter presets for common measurement protocols (LTP, LTD, PPF, high-speed) 10. User Interface Modern CustomTkinter GUI with scrollable parameter panels Real-time plotting using Matplotlib with dual-axis support Parameter display panel showing calculated metrics live Preset selector for rapid protocol switching Measurement mode tabs: Diode, Transistor, Synapse, SRDP, STDP Technical Specifications Programming Language: Python 3.x Key Dependencies: PyVISA, CustomTkinter, Matplotlib, NumPy Target Hardware: Keithley 2636A/B Dual-Channel SMU Communication Protocols: GPIB (IEEE-488), RS-232, TCP/IP Data Format: CSV with metadata headers Measurement Resolution: 0.1-10 NPLC (power line cycles) Use Cases Memristor and resistive RAM device testing Artificial synapse characterization for neuromorphic computing Organic and perovskite solar cell characterization Organic field-effect transistor (OFET) analysis Optoelectronic device measurements Solar Cells Author: Zacharie Jehl Li-KaoContact: zacharie.jehl@upc.edu Source code: https://github.com/SOLIS-project