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Overview
Nucleic Acid Extractor LMNAE-A102 offers processing volume of 50 to 1000µl. It efficiently handles up to 32 samples, enhancing laboratory workflow. Its advanced thermal system ensures uniform heat distribution. It features intuitive programming interface, to customize protocols effectively. Our Nucleic Acid Extractor is ideal for molecular diagnostics, genetic research and clinical laboratories.
Features :
Temperature Regulation
UV lamp
Multi-Mode Operation
Speed Control
Power-Off Protection
Specifications :
| Processing Volume | 50 to 1000 µL |
| Sample Throughput | 1 to 32 |
| Magnetic Bead Recovery Efficiency | Greater than 98% |
| Plate Type | 96-well plate |
| Magnetic Bar | 32 |
| Heating Temperature | Room Temperature to 120°C |
| Internal Program Storage | More than 5000 |
| Magnetic Bead Size | Greater than or equal to100 nm |
| Operating Time | 15 to 30 minutes /run |
| Power Consumption | 500W |
| Power Supply | 100 to 120V, 200 to 240V, 50/60Hz |
| Dimensions | 386 × 439 × 447 mm |
| Net Weight | 36 kg |
Applications :
Nucleic Acid Extractor LMNAE-A102 is suitable for molecular diagnostics, genetic research, clinical laboratories, pharmaceutical and biotechnology industries, and forensic analysis.
Selection Guide :
Nucleic Acid Extractor LMNAE-A102 is a versatile and efficient system designed for automated extraction and purification of nucleic acids (DNA/RNA) from a variety of biological samples such as blood, tissues, swabs, and cultured cells. Based on research studies, it is commonly used in applications such as clinical diagnostics, molecular biology research, disease surveillance, genetic testing, and forensic analysis. The system supports magnetic bead-based purification, ensuring high yield and purity. It is equipped with user-friendly software, customizable protocols, and high throughput capacity, making it suitable for medium to large-scale laboratories. Certifications like CE and ISO compliance assure its quality and safety, which are crucial for regulated environments. Customers can select this model based on their need for reliable performance, standardized protocols, scalability, and validated results across different experimental workflows.