The rapid increase in portable battery waste has exposed a deep vulnerability in today’s recycling systems: the inability to accurately classify batteries by their internal composition. For recyclers, waste operators, and materials recovery facilities, this challenge goes far beyond volume management—it affects safety, profitability, and regulatory compliance.
Ni-Cd and Ni-MH batteries require completely different treatment processes, but are visually indistinguishable once damaged or unlabeled. Manual sorting cannot reliably separate them. As a result, facilities face cross-contamination of output streams, reduced material value, and violations of EU Battery Regulation 2023/1542—which strictly prohibits mixing nickel-cadmium with other battery types.
Lithium batteries add further risk. When misclassified, they can cause fires or explosions in processing lines. The consequences of sorting errors include equipment damage, safety shutdowns, financial penalties, and erosion of client confidence.
If your operation still relies on guesswork, visual inspection, or basic automation, you’re likely losing value and risking compliance. BATTERAY ZETA is engineered to solve these exact challenges—with high-accuracy classification, modular flexibility, and regulatory peace of mind. Keep reading to see how it works—or click below to explore the full solution.
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Datasheet
BATTERAY ZETA is a modular platform for AI-powered battery classification. Using patented X-ray imaging and deep learning, it identifies batteries by internal structure—regardless of damage, labeling, or external appearance.
The system evolves through generations, each solving a new layer of complexity in battery recycling. From universal group sorting to precise separation of visually identical chemistries, BATTERAY ZETA is built to grow with your operation.
Key Advantages
- AI-powered classification based on internal battery signature
- Modular design with upgradable architecture and software
- High-accuracy Ni-Cd / Ni-MH separation for regulatory alignment
- Ready for advanced lithium classification with ZETA-Li
Platform Levels
| Version | Core Capability | Use Case |
|---|---|---|
| ZETA Base | Multi-group classification (Zn, Alk, Li-Primary, Ni group, Li-ion) | Entry-level automation for mixed-stream sorting |
| ZETA Gen 1 | Full separation of Ni-Cd and Ni-MH subtypes | Required for compliance with EU Regulation 2023/1542 |
| ZETA Gen 2 (ZETA-Li) | Standalone lithium classification by subtype (LFP, NMC, LCO, NCA) | For advanced lithium recovery and high-value black mass |
Clues
- BATTERAY ZETA is a patented, AI-powered platform for real-time battery classification
- Ni-Cd and Ni-MH are classified independently—essential for compliance and downstream purity
- X-ray imaging and internal geometry analysis remove the need for labels or surface inspection
- Built to scale—upgrade-ready architecture supports lithium classification via ZETA-Li
Overview
BATTERAY ZETA is a next-generation classification platform that uses AI and multi-sensor X-ray technology to identify portable batteries by their internal structure. Designed for industrial recycling, it classifies batteries automatically—even when labels are missing, counterfeit, or damaged.
Unlike visual or optical systems that rely on external markings, BATTERAY ZETA classifies based on what matters most—the composition and physical profile inside the battery. This patented approach allows accurate identification of Alkaline, Zinc–Carbon, Ni-Cd, Ni-MH, Lithium-Ion, and Primary Lithium cells in real time, regardless of condition or format.
BATTERAY ZETA addresses one of the most overlooked problems in the recycling process: reliable Ni-Cd and Ni-MH separation. These battery types require completely different downstream processing, yet look nearly identical from the outside. Without proper classification, streams become cross-contaminated—lowering output purity and exposing recyclers to non-compliance with EU Regulation 2023/1542, which prohibits mixing Ni-Cd with other chemistries.
At the same time, lithium batteries continue to pose growing safety risks and regulatory challenges. BATTERAY ZETA’s modular architecture makes it future-ready: it supports basic lithium recognition and allows full lithium classification via the dedicated ZETA-Li system, which can be deployed when needed—without changing your core platform.
Supported battery groups
- Zinc–Carbon (ZnC)
- Alkaline (Alk)
- Nickel-Cadmium (NiCd)
- Nickel-Metal Hydride (NiMH)
- NiCd/NiMH subgroup precision separation (advanced)
- Lithium-Ion (Li-ion) (on upgrade)
- Lithium Primary (Li-Primary): Li-SOCl₂, Li-MnO₂, Li-FeS₂
Classification Structure
Sort map
| ZN | ALK | NiCd/MH | NiCd | NiMH | Primary Li | Li-Ion | |
| AAAA | + | + | + | + | + | ||
| AAA | + | + | + | + | + | + | + |
| AA | + | + | + | + | + | + | + |
| C | + | + | + | + | |||
| D | + | + | + | + | + | + | |
| 6F22 (9V) | + | + | + | + | |||
| 21700 | + | ||||||
| 18650 | + | ||||||
| A23 | + | ||||||
| A27 | + | ||||||
| CR2 | |||||||
| 16340 (R123) | + | + | |||||
| 1/2 AA | + |
Key features 
AI-driven classification by internal battery structure
BATTERAY ZETA uses multi-sensor X-ray imaging and machine learning to classify batteries by internal geometry and material density — eliminating dependency on external labels, markings, or shape.
Separation of Ni-Cd and Ni-MH for regulatory compliance
Generation 2 configuration enables automated high-purity classification of Ni-Cd and Ni-MH batteries, ensuring compliance with EU Regulation 2023/1542 and eliminating contamination penalties.
Lithium-ready with standalone ZETA-Li upgrade
The system supports lithium detection by default and enables full subtype classification (NMC, LFP, LCO, NCA) through ZETA-Li — a dedicated Generation 3 system for lithium-only processing.
Sorting accuracy up to 99.5% for Zn and Alk
Delivers exceptional purity for zinc and alkaline chemistries, with over 95% accuracy for lithium, Ni-MH, and Ni-Cd groups — even when batteries are corroded, unrecognized, or counterfeit.
Industrial-grade throughput with AI optimization
BATTERAY ZETA processes up to 18,000 batteries or 430 kg per hour, with continuous operation and adaptive learning to optimize performance across complex, mixed waste streams.
Modular architecture with patented design
BATTERAY ZETA is a patented, scalable platform developed by LINEV Systems. Modular upgrades and software-based sorting programs allow flexible adaptation to future battery types and recycling needs
AI-driven classification by internal battery structure
BATTERAY ZETA uses multi-sensor X-ray imaging and machine learning to classify batteries by internal geometry and material density — eliminating dependency on external labels, markings, or shape.
Separation of Ni-Cd and Ni-MH for regulatory compliance
Generation 2 configuration enables automated high-purity classification of Ni-Cd and Ni-MH batteries, ensuring compliance with EU Regulation 2023/1542 and eliminating contamination penalties.
Lithium-ready with standalone ZETA-Li upgrade
The system supports lithium detection by default and enables full subtype classification (NMC, LFP, LCO, NCA) through ZETA-Li — a dedicated Generation 3 system for lithium-only processing.
Sorting accuracy up to 99.5% for Zn and Alk
Delivers exceptional purity for zinc and alkaline chemistries, with over 95% accuracy for lithium, Ni-MH, and Ni-Cd groups — even when batteries are corroded, unrecognized, or counterfeit.
Industrial-grade throughput with AI optimization
BATTERAY ZETA processes up to 18,000 batteries or 430 kg per hour, with continuous operation and adaptive learning to optimize performance across complex, mixed waste streams.
Modular architecture with patented design
BATTERAY ZETA is a patented, scalable platform developed by LINEV Systems. Modular upgrades and software-based sorting programs allow flexible adaptation to future battery types and recycling needs
After the operator loads the portable battery sorting machine, batteries move through the initial separation conveyor, which filters out small debris, dust, broken parts, and miniature batteries. This protects system components and improves purity of sorting.
Batteries pass through the AI-powered detection zone, where the system uses multi-sensor X-ray imaging to scan internal geometry and composition. No labels or surface details are needed — classification is based entirely on internal structure.
Real-time machine learning algorithms process the captured data and assign each battery to one of the pre-defined groups (e.g., Alkaline, Zinc, NiCd, NiMH, Primary Li, Li-ion). Advanced configurations enable NiCd/NiMH separation or lithium subtype recognition.
Using pneumatic injectors, each identified battery is directed into the correct output bin. Misidentified or unreadable units are diverted to a separate re-check container. This step ensures high-purity fractions and eliminates contamination risks.
Conveyor speed of 1.0 m/s ensures stable, continuous sorting up to 430 kg/h — ideal for industrial-scale operations.
Built-in calibration and performance checks keep classification precise with minimal operator input.
The system performs internal calibration routines and performance checks to maintain peak accuracy. This minimizes the need for manual intervention, reduces maintenance frequency, and ensures long-term consistency in classification quality.
BATTERAY Classic
Since its introduction, the original BATTERAY system has become one of the most widely adopted automated battery classification solutions in the industry. It set the foundation for today’s ZETA platform, but continues to be actively used and sold — delivering consistent performance in real-world operations.
Powered by AI and safe X-ray imaging, BATTERAY Classic enables precise separation of household and industrial batteries by internal structure — ensuring regulatory compliance, fire safety, and high-purity material recovery.
While it does not support Ni-Cd/Ni-MH separation or lithium subtype classification, it provides an ideal solution for clients focusing on core battery groups like Alkaline, Zinc-Carbon, Li-ion, and NiMH. For many facilities, BATTERAY Classic remains the optimal balance of capability, cost-efficiency, and operational simplicity.
Core Advantages
- Trusted by recyclers worldwide — proven in daily use for 6+ years
- Accurate AI-based classification for key chemistries: Zn, Alk, NiMH, Li-ion
- Throughput up to 350 kg/h, or 18,000 units per hour
- Compatible with most standard formats: AAAA, AAA, AA, C, D, 6F22 (9 V), A23, 18650, 21700
- Integrated into existing material flow — minimal installation or retraining required
- Expandable software map to add new battery types as waste streams evolve
Technical Note
BATTERAY Classic shares core architectural elements with the BATTERAY ZETA system — including interface, conveyor logic, classification display, and output ejection logic.
Classification Capabilities
| Battery Type | Zn | Alk | NiMH | Li-ion | NiCd | Primary Li |
|---|---|---|---|---|---|---|
| AA / AAA / C / D | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ |
| 18650 / 21700 | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |
| 6F22 (9 V) | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ |
*Full NiCd/NiMH separation and lithium subtype detection (NMC, LFP, LCO, etc.) are only available with BATTERAY ZETA and ZETA-Li.*
Most BATTERAY video demos and customer installations featured on our site, YouTube, and event materials showcase the Classic system. Its reliability, speed, and simplicity continue to make it the go-to choice for first-time adopters or facilities focused on core compliance.
Product Videos
Technical data
X-ray source
| X-ray emission | Complies with the standard: 1 μSv/h at any point at a distance of 10 cm from the device. Typical value of our system less than 0.3 μSv |
| X-ray protection | Full operator protection |
Loading
| Loading hopper capacity, up to | 350 kg |
| Loading hopper volume | 250 L |
| Conveyor speed | 1.0 m/s |
| Productivity of pure fractions | up to 18000 batteries/hour |
| Pneumatic | 10 bar ±10%, ≥500 SLPM |
| Throughput capacity | 430 kg/hour |
Dimensions
| Overall dimensions (maximum) | ||
|---|---|---|
| Lenght | 8960mm | |
| Width | 2690 mm | |
| Height | 2400 mm |
| Layout | 15000 x 8000 mm |
|---|
| Weight (maximum) | 2500 kg |
|---|
Purity
| Zinc-carbon, alkaline | 99,5 % |
| All groups | >95 % |
X-ray source
| X-ray emission | Complies with the standard: 1 μSv/h at any point at a distance of 4 in from the device. Typical value of our system less than 0.3 μSv/h |
| X-ray protection | Full operator protection |
Loading
| Loading hopper capacity, up to | 772 lbs |
| Loading hopper volume | 66 gal (US) |
| Conveyor speed | 3.3 ft/s (≈7.4 mph) |
| Productivity of pure fractions | up to 18,000 batteries/hour |
| Pneumatic | 145 psi ±10%, ≥17.7 SCFM |
| Throughput capacity | 948 lbs/hour |
Dimensions
| Overall dimensions (maximum) | ||
|---|---|---|
| Length | 29 ft 5 in | |
| Width | 8 ft 10 in | |
| Height | 7 ft 10 in |
| Layout | 49 ft 3 in × 26 ft 3 in |
|---|
| Weight (maximum) | 5,512 lbs |
|---|
Purity
| Zinc-carbon, alkaline | 99.5 % |
| All groups | >95 % |
Feedbacks and related links about BATTERAY Classic
Customer Reviews & Installation Videos
Today’s battery waste contains over 200 active formats—differing in size, shape, chemistry, and regulatory classification. Many fall under hazardous waste due to cadmium, lead, or lithium content, making accurate sorting a safety-critical step in recycling.
Traditional sorting systems rely on optical recognition and manual inspection. But in real-world conditions, labels are often missing, degraded, or misleading—leading to misclassification, compliance failures, and contamination of recovery streams.
BATTERAY ZETA takes a fundamentally different approach. Using low-dose X-ray imaging and proprietary machine learning, it classifies each battery by internal structure and material density. This ensures accurate, automated separation—even for damaged, unmarked, or hybrid batteries—and enables the high purity and compliance demanded by modern recycling.
Developed by LINEV Systems, this patented technology replaces guesswork with precision, empowering facilities to meet industrial throughput targets while preparing for evolving regulations and complex chemistries.
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