XQ4013XL-3PQ240N
XQ4013XL-3PQ240N
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rohs

AMD Xilinx

XQ4013XL-3PQ240N


XQ4013XL-3PQ240N
F20-XQ4013XL-3PQ240N
Active
FIELD PROGRAMMABLE GATE ARRAY, CMOS, 32 X 32.50 MM, EIAJ, PLASTIC, MO-143GA, QFP-240
32 X 32.50 MM, EIAJ, PLASTIC, MO-143GA, QFP-240

XQ4013XL-3PQ240N ECAD Model


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XQ4013XL-3PQ240N Attributes


Type Description Select
Rohs Code No
Part Life Cycle Code Obsolete
Supply Voltage-Nom 3.3 V
Number of Inputs 192
Number of Outputs 192
Number of Logic Cells 1368
Number of Equivalent Gates 10000
Number of CLBs 576
Combinatorial Delay of a CLB-Max 1.6 ns
Programmable Logic Type FIELD PROGRAMMABLE GATE ARRAY
Screening Level MIL-PRF-38535
Temperature Grade MILITARY
Package Shape SQUARE
Technology CMOS
Organization 576 CLBS, 10000 GATES
Additional Feature TYPICAL GATES = 10000 TO 30000
Clock Frequency-Max 166 MHz
Power Supplies 3.3 V
Supply Voltage-Max 3.6 V
Supply Voltage-Min 3 V
JESD-30 Code S-PQFP-G240
Qualification Status Not Qualified
JESD-609 Code e0
Moisture Sensitivity Level 3
Operating Temperature-Max 125 °C
Operating Temperature-Min -55 °C
Peak Reflow Temperature (Cel) 225
Time@Peak Reflow Temperature-Max (s) 30
Number of Terminals 240
Package Body Material PLASTIC/EPOXY
Package Code FQFP
Package Equivalence Code QFP240,1.3SQ,20
Package Shape SQUARE
Package Style FLATPACK, FINE PITCH
Surface Mount YES
Terminal Finish Tin/Lead (Sn85Pb15)
Terminal Form GULL WING
Terminal Pitch 500 µm
Terminal Position QUAD
Width 32 mm
Length 32 mm
Seated Height-Max 4.1 mm
Ihs Manufacturer XILINX INC
Reach Compliance Code unknown
HTS Code 8542.39.00.01
Part Package Code QFP
Package Description 32 X 32.50 MM, EIAJ, PLASTIC, MO-143GA, QFP-240
Pin Count 240
ECCN Code 3A001.A.2.C

XQ4013XL-3PQ240N Datasheet Download


XQ4013XL-3PQ240N Overview



Chip model XQ4013XL-3PQ240N is a product of the semiconductor industry, and it is a product of the latest generation of technology. It is a new type of chip that integrates a variety of functions, including signal processing, signal transmission, signal recognition, and data storage. With its high performance, it has become the most popular chip in the industry.


The chip model XQ4013XL-3PQ240N is a perfect choice for the development of future intelligent systems. It is a powerful tool for the development of networks, intelligent systems, and robots. It can be used to create a variety of intelligent scenarios, such as the Internet of Things (IoT), machine learning, and autonomous driving. It can also be used to develop robots that can interact with humans, as well as robots that can perform complex tasks.


In addition, the chip model XQ4013XL-3PQ240N can also be used in the development and popularization of future intelligent robots. It can be used to develop robots that can interact with humans, as well as robots that can perform complex tasks. With its powerful processing capabilities, it can be used to create robots that can respond to a variety of inputs, such as voice, vision, and touch. It can also be used to develop robots that can recognize and react to their environment, as well as robots that can move and interact with objects.


In order to use the chip model XQ4013XL-3PQ240N effectively, it is necessary to have a good understanding of the technology and its applications. Technical talents with knowledge in artificial intelligence, robotics, and machine learning are needed to develop and use the model effectively. It is also necessary to have a good understanding of the application environment and the technologies needed to support it.


In conclusion, the chip model XQ4013XL-3PQ240N is a powerful tool for the development of networks, intelligent systems, and robots. It can be used to create a variety of intelligent scenarios and to develop robots that can interact with humans, as well as robots that can perform complex tasks. In order to use the chip model XQ4013XL-3PQ240N effectively, it is necessary to have a good understanding of the technology and its applications, as well as the application environment and the technologies needed to support it. Technical talents with knowledge in artificial intelligence, robotics, and machine learning are needed to develop and use the model effectively.



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