SPICE MODEL of IDH06G65C5 (Professional Model) in SPICE PARK

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SPICE MODEL of IDH06G65C5 (Professional Model) in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.

Technology

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
1
Device Modeling Report
Bee Technologies Inc.
COMPONENTS: SiC Schottky Barrier Diode
PART NUMBER: IDH06G65C5
MANUFACTURER: Infineon
REMARK: Professional Model

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
2
Circuit Configuration
DIODE MODEL PARAMETERS
PSpice
model
parameter
Model description
IS Saturation Current
N Emission Coefficient
RS Series Resistance
IKF High-injection Knee Current
CJO Zero-bias Junction Capacitance
M Junction Grading Coefficient
VJ Junction Potential
ISR Recombination Current Saturation Value
BV Reverse Breakdown Voltage(a positive value)
IBV Reverse Breakdown Current(a positive value)
TT Transit Time
EG Energy-band Gap

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
3
U1
IDH06G65C5
R1
0.01m
V1
0Vdc
0
R2
100MEG
V _ V 1
0V 0.5V 1.0V 1.5V 2.0V 2.5V 3.0V
I(R1)
0A
1A
2A
3A
4A
5A
6A
7A
8A
9A
10A
11A
12A
Forward Current Characteristics
Circuit Simulation result
Evaluation circuit

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
4
Comparison Graph Circuit Simulation result
Comparison table
IF (A) VF (V) %Error Measurement Simulation 0.1 0.880 0.882 0.23 0.2 0.900 0.908 0.89 0.5 0.960 0.957 -0.31 1 1.020 1.018 -0.20 2 1.120 1.121 0.09 5 1.400 1.400 0.00 10 1.840 1.845 0.27 12 2.020 2.020 0.00

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
5
V ( R )
100mV 1.0V 10V 100V 1.0KV
I(V2)/(650V/100u)
0
50p
100p
150p
200p
250p
0
R
V1
TD = 0
TF = 100ns
PW = 100us
PER = 10m
V1 = 0
TR = 100us
V2 = 650
V2
0Vdc
R2
100MEG
U1
IDH06G65C5
Junction Capacitance Characteristic
Circuit Simulation result
Evaluation circuit

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
6
Comparison Graph Circuit Simulation result
Comparison table
VR(V) C (pF) %Error Measurement Simulation 0.1 228.000 224.780 -1.41 0.2 223.000 219.890 -1.39 0.5 209.000 206.470 -1.21 1 190.000 188.000 -1.05 2 162.000 161.000 -0.62 5 121.000 117.100 -3.22 10 89.000 86.000 -3.37 20 64.000 61.830 -3.39 50 43.550 41.690 -4.27 100 34.000 33.080 -2.71 200 27.330 28.136 2.95 500 26.000 25.010 -3.81

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
7
V _ V 1
100V 200V 300V 400V 500V 600V
I(R1)
1.0nA
10nA
100nA
1.0uA
10uA
R4
10G
U1
IDH06G65C5
V1
0Vdc
R1
100m
0
Reverse Characteristic
Circuit Simulation result
Evaluation circuit

All Rights Reserved Copyright (C) Bee Technologies Inc. 2014
8
Comparison Graph Circuit Simulation result
Comparison table
IR (A) VR (V) %Error Measurement Simulation 1.00E-09 450.000 428.800 -4.71 1.00E-08 527.000 527.540 0.10 3.00E-07 650.000 649.000 -0.15

This document provides a device modeling report for a SiC Schottky Barrier Diode with part number TRS20N65D from manufacturer TOSHIBA. It includes the diode model parameters, circuit configurations used in simulations, and comparison graphs between the simulation results and measurement data for forward current, junction capacitance, and reverse characteristics. The simulations show good agreement with measurements within 2% error.

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Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more. The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications. We’ll discuss and demo the benefits of UiPath Apps and connectors including: Creating a compelling user experience for any software, without the limitations of APIs. Accelerating the app creation process, saving time and effort Enjoying high-performance CRUD (create, read, update, delete) operations, for seamless data management. Speakers: Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP Charlie Greenberg, host

LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...

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This LF Energy webinar took place June 20, 2024. It featured: -Alex Thornton, LF Energy -Hallie Cramer, Google -Daniel Roesler, UtilityAPI -Henry Richardson, WattTime In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms. This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups. Three primary specifications will be discussed: -Discovery and client registration, emphasizing transparent processes and secure and private access -Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure -Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data

Must Know Postgres Extension for DBA and Developer during Migration

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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/ Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit. The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers. Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.

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SPICE MODEL of IDH06G65C5 (Professional Model) in SPICE PARK

1. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 1 Device Modeling Report Bee Technologies Inc. COMPONENTS: SiC Schottky Barrier Diode PART NUMBER: IDH06G65C5 MANUFACTURER: Infineon REMARK: Professional Model

2. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 2 Circuit Configuration DIODE MODEL PARAMETERS PSpice model parameter Model description IS Saturation Current N Emission Coefficient RS Series Resistance IKF High-injection Knee Current CJO Zero-bias Junction Capacitance M Junction Grading Coefficient VJ Junction Potential ISR Recombination Current Saturation Value BV Reverse Breakdown Voltage(a positive value) IBV Reverse Breakdown Current(a positive value) TT Transit Time EG Energy-band Gap

3. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 3 U1 IDH06G65C5 R1 0.01m V1 0Vdc 0 R2 100MEG V _ V 1 0V 0.5V 1.0V 1.5V 2.0V 2.5V 3.0V I(R1) 0A 1A 2A 3A 4A 5A 6A 7A 8A 9A 10A 11A 12A Forward Current Characteristics Circuit Simulation result Evaluation circuit

4. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 4 Comparison Graph Circuit Simulation result Comparison table IF (A) VF (V) %Error Measurement Simulation 0.1 0.880 0.882 0.23 0.2 0.900 0.908 0.89 0.5 0.960 0.957 -0.31 1 1.020 1.018 -0.20 2 1.120 1.121 0.09 5 1.400 1.400 0.00 10 1.840 1.845 0.27 12 2.020 2.020 0.00

5. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 5 V ( R ) 100mV 1.0V 10V 100V 1.0KV I(V2)/(650V/100u) 0 50p 100p 150p 200p 250p 0 R V1 TD = 0 TF = 100ns PW = 100us PER = 10m V1 = 0 TR = 100us V2 = 650 V2 0Vdc R2 100MEG U1 IDH06G65C5 Junction Capacitance Characteristic Circuit Simulation result Evaluation circuit

6. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 6 Comparison Graph Circuit Simulation result Comparison table VR(V) C (pF) %Error Measurement Simulation 0.1 228.000 224.780 -1.41 0.2 223.000 219.890 -1.39 0.5 209.000 206.470 -1.21 1 190.000 188.000 -1.05 2 162.000 161.000 -0.62 5 121.000 117.100 -3.22 10 89.000 86.000 -3.37 20 64.000 61.830 -3.39 50 43.550 41.690 -4.27 100 34.000 33.080 -2.71 200 27.330 28.136 2.95 500 26.000 25.010 -3.81

7. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 7 V _ V 1 100V 200V 300V 400V 500V 600V I(R1) 1.0nA 10nA 100nA 1.0uA 10uA R4 10G U1 IDH06G65C5 V1 0Vdc R1 100m 0 Reverse Characteristic Circuit Simulation result Evaluation circuit

8. All Rights Reserved Copyright (C) Bee Technologies Inc. 2014 8 Comparison Graph Circuit Simulation result Comparison table IR (A) VR (V) %Error Measurement Simulation 1.00E-09 450.000 428.800 -4.71 1.00E-08 527.000 527.540 0.10 3.00E-07 650.000 649.000 -0.15

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