Orthodontic Base Stone, White, 22KG

The orthodontic-base is a specialized hard plaster designed to meet the high standards of orthodontic applications. It is categorized under type 3, according to DIN EN ISO 6873: 2013, with a slow setting feature to accommodate meticulous orthodontic work. Its extra white color provides a clear visual for orthodontic analysis, as well as being suitable for plastic dentures, repairs, and diagnostic models.

Specifications:

• Category: Hard Plaster
• Type: Type 3, Slow Setting
• Application: Orthodontics, Plastic Dentures, Repair, and Diagnostic Models
• Color: Extra White

Mixing and Handling:

Parameter	Specification
Mixing Ratio	28 ml of water to 100 g of powder
Stirring Time	30 seconds (mechanical)
Processing Time	Approximately 7-8 minutes
Setting Time	Approximately 13-14 minutes

Physical Properties:

• Hardness (24h): Greater than 140 N/mm²
• Hardness (30/60 min): Approximately 130/140 N/mm²
• Compressive Strength:
  • 1 hour: Approximately 50 MPa
  • 24 hours: Greater than 60 MPa
• Expansion (DIN): Less than 0.10 %

Product Highlights:

• Optimized for Orthodontics: Deliberately slow setting to facilitate detailed orthodontic work.
• Extra White Color: Enhances visibility for precision in orthodontic applications.
• Versatile Use: Also appropriate for the production of plastic dentures, and repair and diagnostic models.
• Consistent Quality: Offers high hardness and compressive strength for reliable model creation.

Usage Instructions:

1. Prepare a mix of 28 ml water with 100 g of orthodontic-base powder.
2. Stir the mixture mechanically for 30 seconds to ensure a lump-free consistency.
3. The plaster remains moldable for about 7-8 minutes, allowing detailed work without haste.
4. The setting time is approximately 13-14 minutes, after which the model can be further processed.
5. Post setting, the plaster exhibits high hardness and compressive strength, ideal for orthodontic purposes.

orthodontic-base is the go-to material for orthodontists demanding a balance between workability and performance in model creation and repair tasks.