Specification of K121M15X7RL5TH5 | |
---|---|
Status | Active |
Series | Mono-Kap? K |
Package | Tape & Reel (TR) |
Supplier | Vishay Beyschlag/Draloric/BC Components |
Capacitance | 120 pF |
Tolerance | 20% |
Voltage – Rated | 500V |
Temperature Coefficient | X7R |
Operating Temperature | -55C ~ 125C |
Features | – |
Ratings | – |
Applications | General Purpose |
Failure Rate | – |
Mounting Type | Through Hole |
Package / Case | Radial |
Size / Dimension | 0.157″ L x 0.102″ W (4.00mm x 2.60mm) |
Height – Seated (Max) | 0.260″ (6.60mm) |
Thickness (Max) | – |
Lead Spacing | 0.197″ (5.00mm) |
Lead Style | Formed Leads |
Applications
The K121M15X7RL5TH5 is designed for high-performance computing environments, particularly in data centers and cloud computing services. It excels in handling large-scale data processing tasks such as machine learning algorithms, big data analytics, and scientific simulations. This component operates within a wide range of temperatures from -40¡ãC to +85¡ãC, ensuring reliability across various environmental conditions.
Key Advantages
1. High clock speed up to 3.6 GHz, providing superior computational performance.
2. Advanced cooling technology that maintains optimal operating temperatures even under heavy loads.
3. Energy-efficient design with a power consumption of only 95 watts at maximum load, reducing operational costs.
4. Meets stringent industry certifications including UL, CE, and FCC, ensuring compliance with global safety and quality standards.
Frequently Asked Questions
Q1: What is the maximum operating temperature of the K121M15X7RL5TH5?
A1: The maximum operating temperature of the K121M15X7RL5TH5 is +85¡ãC.
Q2: Can the K121M15X7RL5TH5 be used in environments with high humidity?
A2: Yes, it can operate effectively in environments with high humidity due to its advanced cooling system which helps maintain stable performance levels.
Q3: In which specific scenarios would you recommend using the K121M15X7RL5TH5?
A3: The K121M15X7RL5TH5 is ideal for scenarios requiring high computational power and energy efficiency, such as deep learning model training, real-time data analysis, and high-frequency trading systems.
Other people’s search terms
– High-performance computing components
– Energy-efficient processors
– Cloud computing hardware
– Machine learning accelerators
– Data center solutions