pchang718
562 lines
30 KiB
Python
562 lines
30 KiB
Python
import pickle
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import os
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import sys
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import glob
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import gc
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# Limit the thread count for parallel solvers to prevent WSL from resource starvation/disconnecting
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os.environ["OMP_NUM_THREADS"] = "6"
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os.environ["MKL_NUM_THREADS"] = "6"
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os.environ["TBB_NUM_THREADS"] = "6"
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os.environ["OPENBLAS_NUM_THREADS"] = "6"
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# Disable MKL internal memory manager to prevent memory accumulation (OOM) across solve calls
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os.environ["MKL_DISABLE_FAST_MM"] = "1"
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# Auto-detect and load Intel MKL before devsim is imported
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mkl_libs = glob.glob(os.path.join(os.path.dirname(sys.executable), "../lib/libmkl_rt.so.*"))
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if mkl_libs:
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os.environ["DEVSIM_MATH_LIBS"] = mkl_libs[0]
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import devsim
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import numpy as np
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DEV_DIR = os.environ.get("DEV_DIR", "devices/Triac_rp")
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sys.path.insert(0, os.path.abspath(DEV_DIR))
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OUT_DIR = os.path.join(os.environ.get("OUT_DIR", os.path.join(DEV_DIR, "output_this_run")), "")
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os.makedirs(OUT_DIR, exist_ok=True)
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import matplotlib.pyplot as plt
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import time
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# Enable Intel MKL PARDISO multi-threaded sparse solver
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devsim.set_parameter(name="solver_type", value="pardiso")
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from device_config import *
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from physics.model_create import *
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from physics.new_physics import *
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device = "device_2d"
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# 1. Load the mesh
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mesh_file = os.path.join(DEV_DIR, "device_2d.msh")
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print(f"Loading mesh: {mesh_file}...")
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devsim.create_gmsh_mesh(mesh=device, file=mesh_file)
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devsim.add_gmsh_region(mesh=device, gmsh_name="Silicon", region="Silicon", material="Silicon")
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devsim.add_gmsh_region(mesh=device, gmsh_name="Oxide", region="Oxide", material="Oxide")
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devsim.add_gmsh_region(mesh=device, gmsh_name="Molding", region="Molding", material="Molding")
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# Add contacts for Silicon region
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT1_Si", name="MT1_Si", region="Silicon", material="metal")
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT2_Si", name="MT2_Si", region="Silicon", material="metal")
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT1_P12_Si", name="MT1_P12_Si", region="Silicon", material="metal")
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT2_P12_Si", name="MT2_P12_Si", region="Silicon", material="metal")
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# Add contacts for Oxide region
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT1_Ox", name="MT1_Ox", region="Oxide", material="metal")
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT2_Ox", name="MT2_Ox", region="Oxide", material="metal")
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# Add contacts for Molding region
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT1_Mold", name="MT1_Mold", region="Molding", material="metal")
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devsim.add_gmsh_contact(mesh=device, gmsh_name="MT2_Mold", name="MT2_Mold", region="Molding", material="metal")
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# Add interfaces
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devsim.add_gmsh_interface(mesh=device, gmsh_name="Si_Ox_Interface", name="Si_Ox", region0="Silicon", region1="Oxide")
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devsim.add_gmsh_interface(mesh=device, gmsh_name="Ox_Mold_Interface", name="Ox_Mold", region0="Oxide", region1="Molding")
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devsim.add_gmsh_interface(mesh=device, gmsh_name="Si_Mold_Interface", name="Si_Mold", region0="Silicon", region1="Molding")
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devsim.finalize_mesh(mesh=device)
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devsim.create_device(mesh=device, device=device)
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# 2. Set up doping in Silicon region
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if os.environ.get("USE_PCAD", "false").lower() == "true":
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from device_pcad_config import apply_pcad_doping_2d
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apply_pcad_doping_2d(device, region="Silicon")
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else:
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devsim.node_model(device=device, region="Silicon", name="nD_sub", equation=f"{N_SUB}")
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def get_erfc_expr(peak, x1, x2, hdiff, vdiff):
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return f"{peak} * erfc(y / {vdiff}) * 0.5 * (erf((x - ({x1})) / {hdiff}) - erf((x - ({x2})) / {hdiff}))"
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p11_left_expr = get_erfc_expr(P11_PEAK, -P11_X2, -P11_X1, P_WELL_HDDIFF, P_WELL_VDDIFF)
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p11_right_expr = get_erfc_expr(P11_PEAK, P11_X1, P11_X2, P_WELL_HDDIFF, P_WELL_VDDIFF)
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devsim.node_model(device=device, region="Silicon", name="nA_p11_l", equation=p11_left_expr)
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devsim.node_model(device=device, region="Silicon", name="nA_p11_r", equation=p11_right_expr)
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p12_left_expr = get_erfc_expr(P12_PEAK, -P12_X2, -P12_X1, P_WELL_HDDIFF, P_WELL_VDDIFF)
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p12_right_expr = get_erfc_expr(P12_PEAK, P12_X1, P12_X2, P_WELL_HDDIFF, P_WELL_VDDIFF)
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devsim.node_model(device=device, region="Silicon", name="nA_p12_l", equation=p12_left_expr)
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devsim.node_model(device=device, region="Silicon", name="nA_p12_r", equation=p12_right_expr)
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p13_left_expr = get_erfc_expr(P13_PEAK, -P13_X2, -P13_X1, P_WELL_HDDIFF, P_WELL_VDDIFF)
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p13_right_expr = get_erfc_expr(P13_PEAK, P13_X1, P13_X2, P_WELL_HDDIFF, P_WELL_VDDIFF)
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devsim.node_model(device=device, region="Silicon", name="nA_p13_l", equation=p13_left_expr)
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devsim.node_model(device=device, region="Silicon", name="nA_p13_r", equation=p13_right_expr)
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nplus_left_expr = get_erfc_expr(NPLUS_PEAK, -NPLUS_X2, -NPLUS_X1, NPLUS_HDDIFF, NPLUS_VDDIFF)
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nplus_right_expr = get_erfc_expr(NPLUS_PEAK, NPLUS_X1, NPLUS_X2, NPLUS_HDDIFF, NPLUS_VDDIFF)
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devsim.node_model(device=device, region="Silicon", name="nD_nplus_l", equation=nplus_left_expr)
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devsim.node_model(device=device, region="Silicon", name="nD_nplus_r", equation=nplus_right_expr)
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mring_l_expr = get_erfc_expr(NPLUS_PEAK, -W_DEVICE, -MRING_X1, NPLUS_HDDIFF, NPLUS_VDDIFF)
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mring_r_expr = get_erfc_expr(NPLUS_PEAK, MRING_X1, W_DEVICE, NPLUS_HDDIFF, NPLUS_VDDIFF)
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devsim.node_model(device=device, region="Silicon", name="nD_mring_l", equation=mring_l_expr)
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devsim.node_model(device=device, region="Silicon", name="nD_mring_r", equation=mring_r_expr)
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devsim.node_model(device=device, region="Silicon", name="Donors",
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equation="nD_sub + nD_nplus_l + nD_nplus_r + nD_mring_l + nD_mring_r")
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devsim.node_model(device=device, region="Silicon", name="Acceptors",
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equation="1e10 + nA_p11_l + nA_p11_r + nA_p12_l + nA_p12_r + nA_p13_l + nA_p13_r")
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devsim.node_model(device=device, region="Silicon", name="NetDoping", equation="Donors - Acceptors")
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devsim.node_model(device=device, region="Silicon", name="LogNetDoping", equation="asinh(NetDoping / 2.0) / log(10.0)")
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# 3. Initialize electrostatic potential simulation (Poisson only)
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CreateSolution(device, "Silicon", "Potential")
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temp_val = os.environ.get("TEMP", "300")
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devsim.set_parameter(device=device, name="T", value=temp_val)
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CreateSiliconPotentialOnly(device, "Silicon")
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# Oxide potential equations
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def CreateOxidePotentialOnly(device, region):
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if not InNodeModelList(device, region, "Potential"):
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CreateSolution(device, region, "Potential")
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devsim.set_parameter(device=device, region=region, name="Permittivity", value=3.9 * 8.85e-14)
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efield = "(Potential@n0 - Potential@n1)*EdgeInverseLength"
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CreateEdgeModel(device, region, "EField", efield)
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CreateEdgeModelDerivatives(device, region, "EField", efield, "Potential")
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dfield = "Permittivity*EField"
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CreateEdgeModel(device, region, "PotentialEdgeFlux", dfield)
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CreateEdgeModelDerivatives(device, region, "PotentialEdgeFlux", dfield, "Potential")
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devsim.equation(device=device, region=region, name="PotentialEquation", variable_name="Potential",
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edge_model="PotentialEdgeFlux", variable_update="default", min_error=1e-3)
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CreateOxidePotentialOnly(device, "Oxide")
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# Molding potential equations
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def CreateMoldingPotentialOnly(device, region):
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if not InNodeModelList(device, region, "Potential"):
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CreateSolution(device, region, "Potential")
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devsim.set_parameter(device=device, region=region, name="Permittivity", value=4.0 * 8.85e-14)
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efield = "(Potential@n0 - Potential@n1)*EdgeInverseLength"
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CreateEdgeModel(device, region, "EField", efield)
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CreateEdgeModelDerivatives(device, region, "EField", efield, "Potential")
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dfield = "Permittivity*EField"
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CreateEdgeModel(device, region, "PotentialEdgeFlux", dfield)
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CreateEdgeModelDerivatives(device, region, "PotentialEdgeFlux", dfield, "Potential")
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devsim.equation(device=device, region=region, name="PotentialEquation", variable_name="Potential",
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edge_model="PotentialEdgeFlux", variable_update="default", min_error=1e-3)
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CreateMoldingPotentialOnly(device, "Molding")
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# Interfaces continuous potential
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def CreateContinuousPotentialInterface(device, interface):
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model_name = CreateContinuousInterfaceModel(device, interface, "Potential")
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devsim.interface_equation(device=device, interface=interface, name="PotentialEquation",
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interface_model=model_name, type="continuous")
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CreateContinuousPotentialInterface(device, "Si_Ox")
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CreateContinuousPotentialInterface(device, "Ox_Mold")
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CreateContinuousPotentialInterface(device, "Si_Mold")
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# Potential contacts setup
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silicon_contacts = ["MT1_Si", "MT2_Si", "MT1_P12_Si", "MT2_P12_Si"]
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for c in silicon_contacts:
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devsim.set_parameter(device=device, name=GetContactBiasName(c), value=0.0)
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CreateSiliconPotentialOnlyContact(device, "Silicon", c)
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def CreateOxidePotentialOnlyContact(device, region, contact):
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contact_bias = GetContactBiasName(contact)
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contact_model = f"Potential - {contact_bias}"
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contact_model_name = f"{contact}_bc"
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CreateContactNodeModel(device, contact, contact_model_name, contact_model)
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CreateContactNodeModelDerivative(device, contact, contact_model_name, contact_model, "Potential")
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devsim.contact_equation(device=device, contact=contact, name="PotentialEquation",
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node_model=contact_model_name, edge_charge_model="PotentialEdgeFlux")
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oxide_contacts = ["MT1_Ox", "MT2_Ox"]
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for c in oxide_contacts:
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devsim.set_parameter(device=device, name=GetContactBiasName(c), value=0.0)
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CreateOxidePotentialOnlyContact(device, "Oxide", c)
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def CreateMoldingPotentialOnlyContact(device, region, contact):
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contact_bias = GetContactBiasName(contact)
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contact_model = f"Potential - {contact_bias}"
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contact_model_name = f"{contact}_bc"
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CreateContactNodeModel(device, contact, contact_model_name, contact_model)
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CreateContactNodeModelDerivative(device, contact, contact_model_name, contact_model, "Potential")
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devsim.contact_equation(device=device, contact=contact, name="PotentialEquation",
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node_model=contact_model_name, edge_charge_model="PotentialEdgeFlux")
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molding_contacts = ["MT1_Mold", "MT2_Mold"]
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for c in molding_contacts:
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devsim.set_parameter(device=device, name=GetContactBiasName(c), value=0.0)
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CreateMoldingPotentialOnlyContact(device, "Molding", c)
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# Solve initial zero-bias Poisson
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print("Solving initial Poisson at thermal equilibrium...")
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devsim.solve(type="dc", absolute_error=1.0, relative_error=1e-10, maximum_iterations=50)
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print("Initial Poisson converged.")
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# 4. Set up carrier solutions for Silicon Drift-Diffusion
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# Compute initial guess for Electrons and Holes based on Potential
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CreateSolution(device, "Silicon", "Electrons")
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CreateSolution(device, "Silicon", "Holes")
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devsim.set_node_values(device=device, region="Silicon", name="Electrons", init_from="IntrinsicElectrons")
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devsim.set_node_values(device=device, region="Silicon", name="Holes", init_from="IntrinsicHoles")
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# Redefine IntrinsicElectrons, IntrinsicHoles, and related models to avoid potential exponential overflow at high bias.
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print("Redefining equilibrium models to prevent high-bias exponential overflow...")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicElectrons", equation="Electrons")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicElectrons:Potential", equation="0")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicElectrons:Electrons", equation="1")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicElectrons:Holes", equation="0")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicHoles", equation="Holes")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicHoles:Potential", equation="0")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicHoles:Electrons", equation="0")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicHoles:Holes", equation="1")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge", equation="Holes - Electrons + NetDoping")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Potential", equation="0")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Electrons", equation="-1")
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devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Holes", equation="1")
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devsim.node_model(device=device, region="Silicon", name="PotentialIntrinsicCharge", equation="0")
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devsim.node_model(device=device, region="Silicon", name="PotentialIntrinsicCharge:Potential", equation="0")
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# Mobility and drift diffusion equations
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opts = CreateAroraMobilityLF(device, "Silicon")
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# Bypassing HFMobility to prevent zero-bias convergence oscillations
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CreateSiliconDriftDiffusion(device, "Silicon", **opts)
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devsim.node_model(device=device, region="Silicon", name="LogElectrons", equation="log(Electrons + 1e-10) / log(10.0)")
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devsim.node_model(device=device, region="Silicon", name="LogHoles", equation="log(Holes + 1e-10) / log(10.0)")
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# Re-setup Silicon contacts for Drift-Diffusion
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for c in silicon_contacts:
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CreateSiliconDriftDiffusionContact(device, "Silicon", c, opts['Jn'], opts['Jp'])
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# Solve initial zero-bias Drift-Diffusion with standard tolerances (using default log_damp updates)
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print("Solving initial Drift-Diffusion equations at zero bias...")
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devsim.solve(type="dc", absolute_error=1e10, relative_error=1e30, charge_error=1e12, maximum_iterations=50)
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print("Initial Drift-Diffusion converged successfully!")
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# Switch continuity and potential equations for the bias sweep
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print("Configuring continuity and potential equations for the bias sweep (min_error=1e5, positive update)...")
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# Instantiate Avalanche (Impact Ionization) edge generation model
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CreateAvalancheGeneration(device, "Silicon", opts['Jn'], opts['Jp'])
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devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
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time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model="",
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variable_update="positive", node_model="ElectronGeneration", min_error=1e5)
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devsim.equation(device=device, region="Silicon", name="HoleContinuityEquation", variable_name="Holes",
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time_node_model="PCharge", edge_model=opts['Jp'], edge_volume_model="",
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variable_update="positive", node_model="HoleGeneration", min_error=1e5)
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devsim.equation(device=device, region="Silicon", name="HoleContinuityEquation", variable_name="Holes",
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time_node_model="PCharge", edge_model=opts['Jp'], edge_volume_model="",
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variable_update="positive", node_model="HoleGeneration", min_error=1e5)
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devsim.equation(device=device, region="Silicon", name="PotentialEquation", variable_name="Potential",
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node_model="PotentialNodeCharge", edge_model="DField", variable_update="default", min_error=1e-3)
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# Save zero-bias tecplot and VTK
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devsim.write_devices(file=f"{OUT_DIR}sweep_preview_0V.tec", type="tecplot")
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# devsim.write_devices(file="sweep_preview_0V", type="vtk")
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# 5. Define Sweep Parameters
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v_target = 1000.0
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v_current = 0.0
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step_size = 0.1 # Initial step size (V)
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max_step = 50.0 # Maximum step size (V)
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min_step = 1e-4 # Minimum step size (V)
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compliance_current = 1e-3 # 1 mA compliance current
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# Helper functions to save/restore state in case of convergence failure
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def save_state(device):
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state = {}
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for region in ["Silicon", "Oxide", "Molding"]:
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state[region] = {
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"Potential": list(devsim.get_node_model_values(device=device, region=region, name="Potential"))
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}
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state["Silicon"]["Electrons"] = list(devsim.get_node_model_values(device=device, region="Silicon", name="Electrons"))
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state["Silicon"]["Holes"] = list(devsim.get_node_model_values(device=device, region="Silicon", name="Holes"))
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return state
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def restore_state(device, state):
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for region in ["Silicon", "Oxide", "Molding"]:
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devsim.set_node_values(device=device, region=region, name="Potential", values=state[region]["Potential"])
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devsim.set_node_values(device=device, region="Silicon", name="Electrons", values=state["Silicon"]["Electrons"])
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devsim.set_node_values(device=device, region="Silicon", name="Holes", values=state["Silicon"]["Holes"])
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# File logging setup
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time_log = open(f"{OUT_DIR}simulation_time.log", "w", buffering=1)
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time_log.write("Time\tVoltage(V)\tStep(V)\tCurrent(A)\tIterations\tTimeTaken(s)\n")
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# Arrays to store I-V data
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voltage_list = [0.0]
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current_list = [0.0]
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# Recon variables
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next_recon_v = 50.0
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with open(f"{OUT_DIR}recon_avalanche.log", "w") as f:
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f.write("Voltage(V)\tAvalancheCurrent(A)\n")
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# Save initial state
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state = save_state(device)
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start_sweep_time = time.time()
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print("Beginning adaptive bias sweep...")
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step_count = 0
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# Targets for saving intermediate state checkpoints
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save_targets = [5.0, 50.0, 500.0]
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saved_targets = set()
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while v_current < v_target:
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v_next = min(v_current + step_size, v_target)
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# Apply new bias values to MT1 contacts
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for c in ["MT1_Si", "MT1_P12_Si", "MT1_Ox", "MT1_Mold"]:
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devsim.set_parameter(device=device, name=f"{c}_bias", value=v_next)
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step_start_time = time.time()
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try:
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# Stage 1: Pre-conditioning (Relaxed Tolerance to get a good initial guess)
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iters1 = 10
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try:
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res1 = devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-1, charge_error=1e12, maximum_iterations=10, info=True)
|
|
iters1 = len(res1.get("iterations", []))
|
|
except devsim.error:
|
|
pass # Ignore non-convergence in pre-conditioning
|
|
|
|
import psutil
|
|
mem_stage1 = psutil.Process(os.getpid()).memory_info().rss / (1024**3)
|
|
print(f"Stage 1 (Precondition) Memory Usage: {mem_stage1:.1f} GB")
|
|
|
|
# Stage 2: Precision Newton (Strict Tolerance) - slightly relaxed relative_error to 3e-3 to avoid limit cycle oscillations
|
|
res = devsim.solve(type="dc", absolute_error=1e10, relative_error=3e-3, charge_error=1e12, maximum_iterations=12, info=True)
|
|
iters2 = len(res.get("iterations", []))
|
|
|
|
mem_stage2 = psutil.Process(os.getpid()).memory_info().rss / (1024**3)
|
|
print(f"Stage 2 (Newton) Memory Usage: {mem_stage2:.1f} GB")
|
|
iters = f"{iters1}+{iters2}"
|
|
total_iters = iters1 + iters2
|
|
|
|
if not res.get("converged", False):
|
|
raise devsim.error("Convergence failure")
|
|
|
|
step_end_time = time.time()
|
|
time_taken = step_end_time - step_start_time
|
|
|
|
# Convergence succeeded! Compute current at MT1 terminal
|
|
# MT1 terminal current is the sum of currents on MT1_Si and MT1_P12_Si
|
|
i_n_si = devsim.get_contact_current(device=device, contact="MT1_Si", equation="ElectronContinuityEquation")
|
|
i_p_si = devsim.get_contact_current(device=device, contact="MT1_Si", equation="HoleContinuityEquation")
|
|
i_n_p12 = devsim.get_contact_current(device=device, contact="MT1_P12_Si", equation="ElectronContinuityEquation")
|
|
i_p_p12 = devsim.get_contact_current(device=device, contact="MT1_P12_Si", equation="HoleContinuityEquation")
|
|
|
|
total_curr = i_n_si + i_p_si + i_n_p12 + i_p_p12
|
|
|
|
# Update simulation status
|
|
v_current = v_next
|
|
state = save_state(device)
|
|
|
|
voltage_list.append(v_current)
|
|
current_list.append(total_curr)
|
|
|
|
print(f"Step {step_count}: Converged at V = {v_current:.4f} V, I = {total_curr:.4e} A. Step size: {step_size:.4f} V. Iterations: {iters}. Time: {time_taken:.2f} s")
|
|
|
|
# Log to file
|
|
time_log.write(f"{time.strftime('%X')}\t{v_current:.4f}\t{step_size:.4f}\t{total_curr:.4e}\t{iters}\t{time_taken:.2f}\t{mem_stage1:.1f}GB\t{mem_stage2:.1f}GB\n")
|
|
|
|
# Save checkpoints when crossing target voltages
|
|
for target in save_targets:
|
|
if v_current >= target and target not in saved_targets:
|
|
filename = f"sweep_preview_{int(target)}V.tec"
|
|
filename_vtk = f"sweep_preview_{int(target)}V"
|
|
print(f"Saving checkpoint at V = {v_current:.2f} V to {filename} and VTK...")
|
|
devsim.write_devices(file=f"{OUT_DIR}{filename}", type="tecplot")
|
|
# devsim.write_devices(file=filename_vtk, type="vtk")
|
|
saved_targets.add(target)
|
|
|
|
# Compliance check
|
|
if abs(total_curr) >= compliance_current:
|
|
print(f"Compliance current of {compliance_current:.1e} A reached at V = {v_current:.4f} V. Stopping sweep.")
|
|
time_log.write(f"Compliance current reached at V = {v_current:.4f} V.\n")
|
|
break
|
|
|
|
|
|
# --- RECONNAISSANCE PROBE ---
|
|
if v_current >= next_recon_v:
|
|
state_data = save_state(device)
|
|
seed_data = {"voltage": v_current, "step_size": step_size, "state": state_data}
|
|
seed_filename = f"{OUT_DIR}seed_{int(next_recon_v)}V.pkl"
|
|
with open(seed_filename, "wb") as f:
|
|
pickle.dump(seed_data, f)
|
|
print(f"\n--- RECON PROBE at {v_current:.2f} V ---")
|
|
print(f"Saved seed to {seed_filename}")
|
|
|
|
# Turn ON Avalanche
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model="AvalancheGeneration",
|
|
variable_update="positive", node_model="ElectronGeneration", min_error=1e5)
|
|
devsim.equation(device=device, region="Silicon", name="HoleContinuityEquation", variable_name="Holes",
|
|
time_node_model="PCharge", edge_model=opts['Jp'], edge_volume_model="AvalancheGeneration_p",
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
|
|
try:
|
|
# Stage 1 pre-conditioning
|
|
try:
|
|
devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-1, charge_error=1e12, maximum_iterations=10, info=True)
|
|
except devsim.error:
|
|
pass
|
|
# Stage 2 solve
|
|
res_av = devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-3, charge_error=1e12, maximum_iterations=15, info=True)
|
|
if res_av.get("converged", False):
|
|
# Measure Avalanche current
|
|
ia_n_si = devsim.get_contact_current(device=device, contact="MT1_Si", equation="ElectronContinuityEquation")
|
|
ia_p_si = devsim.get_contact_current(device=device, contact="MT1_Si", equation="HoleContinuityEquation")
|
|
ia_n_p12 = devsim.get_contact_current(device=device, contact="MT1_P12_Si", equation="ElectronContinuityEquation")
|
|
ia_p_p12 = devsim.get_contact_current(device=device, contact="MT1_P12_Si", equation="HoleContinuityEquation")
|
|
av_curr = ia_n_si + ia_p_si + ia_n_p12 + ia_p_p12
|
|
print(f"Avalanche Current at {v_current:.2f} V: {av_curr:.4e} A")
|
|
with open(f"{OUT_DIR}recon_avalanche.log", "a") as f:
|
|
f.write(f"{v_current:.2f}\t{av_curr:.4e}\n")
|
|
else:
|
|
print("Avalanche failed to converge.")
|
|
with open(f"{OUT_DIR}recon_avalanche.log", "a") as f:
|
|
f.write(f"{v_current:.2f}\tFAILED\n")
|
|
except devsim.error:
|
|
print("Avalanche failed to converge.")
|
|
with open(f"{OUT_DIR}recon_avalanche.log", "a") as f:
|
|
f.write(f"{v_current:.2f}\tFAILED\n")
|
|
|
|
# Restore state and Turn OFF Avalanche
|
|
restore_state(device, state_data)
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model="",
|
|
variable_update="positive", node_model="ElectronGeneration", min_error=1e5)
|
|
devsim.equation(device=device, region="Silicon", name="HoleContinuityEquation", variable_name="Holes",
|
|
time_node_model="PCharge", edge_model=opts['Jp'], edge_volume_model="",
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
print("--- END RECON PROBE ---\n")
|
|
next_recon_v += 50.0
|
|
|
|
# Grow step size for next step adaptively based on Newton iterations
|
|
|
|
if total_iters <= 6:
|
|
step_size = min(step_size * 1.2, max_step)
|
|
elif total_iters <= 9:
|
|
pass # Keep step size the same
|
|
else:
|
|
step_size = max(step_size * 0.8, min_step)
|
|
|
|
step_count += 1
|
|
|
|
except devsim.error as e:
|
|
# Convergence failure: restore last state and cut step size
|
|
step_end_time = time.time()
|
|
time_taken = step_end_time - step_start_time
|
|
print(f"Convergence failure at V = {v_next:.4f} V. Restoring state and scaling step size by 0.577 from {step_size:.4f} V.")
|
|
time_log.write(f"{time.strftime('%X')}\t{v_next:.4f}\t{step_size:.4f}\tFAILED\t-\t{time_taken:.2f}\n")
|
|
|
|
restore_state(device, state)
|
|
step_size *= 0.577
|
|
|
|
if step_size < min_step:
|
|
print("Step size has fallen below minimum limit. Aborting simulation.")
|
|
time_log.write(f"Aborted: step size fell below {min_step:.1e} V\n")
|
|
break
|
|
|
|
total_sweep_time = time.time() - start_sweep_time
|
|
print(f"Sweep completed in {total_sweep_time:.2f} s.")
|
|
time_log.write(f"Total Sweep Time: {total_sweep_time:.2f} s\n")
|
|
time_log.close()
|
|
|
|
# 6. Save final results and generate plots
|
|
# Save final tecplot and VTK at highest voltage
|
|
devsim.write_devices(file=f"{OUT_DIR}sweep_preview_final.tec", type="tecplot")
|
|
# devsim.write_devices(file="sweep_preview_final", type="vtk")
|
|
|
|
# Save I-V data to CSV
|
|
np.savetxt(f"{OUT_DIR}sweep_iv_2d.csv", np.column_stack((voltage_list, current_list)),
|
|
header="Voltage(V),Current(A)", delimiter=",")
|
|
|
|
# Plot and save I-V curve
|
|
plt.figure(figsize=(8, 6))
|
|
plt.plot(voltage_list, np.abs(current_list), 'o-', color='#1f77b4', markersize=4)
|
|
plt.yscale('log')
|
|
plt.grid(True, which="both", ls="--")
|
|
plt.xlabel("Bias Voltage (V)")
|
|
plt.ylabel("Terminal Current Magnitude (A)")
|
|
plt.title(f"TVS 2D Bidirectional Bias Sweep I-V Curve (Log Scale) (T={temp_val}K)")
|
|
plt.tight_layout()
|
|
plt.savefig(f"{OUT_DIR}sweep_iv_2d.png", dpi=300)
|
|
plt.close()
|
|
|
|
# Generate potential & electric field plots at final converged bias
|
|
# Extract final node values
|
|
x_si = np.array(devsim.get_node_model_values(device=device, region="Silicon", name="x")) / um
|
|
y_si = np.array(devsim.get_node_model_values(device=device, region="Silicon", name="y")) / um
|
|
pot_si = np.array(devsim.get_node_model_values(device=device, region="Silicon", name="Potential"))
|
|
tri_si = np.array(devsim.get_element_node_list(device=device, region="Silicon"))
|
|
|
|
# Compute final Emag
|
|
for reg in ["Silicon", "Oxide", "Molding"]:
|
|
devsim.element_from_edge_model(edge_model="EField", device=device, region=reg)
|
|
devsim.element_model(device=device, region=reg, name="Emag", equation="(EField_x^2 + EField_y^2)^(0.5)")
|
|
|
|
emag_si = np.array(devsim.get_element_model_values(device=device, region="Silicon", name="Emag"))[::3]
|
|
|
|
x_ox = np.array(devsim.get_node_model_values(device=device, region="Oxide", name="x")) / um
|
|
y_ox = np.array(devsim.get_node_model_values(device=device, region="Oxide", name="y")) / um
|
|
pot_ox = np.array(devsim.get_node_model_values(device=device, region="Oxide", name="Potential"))
|
|
tri_ox = np.array(devsim.get_element_node_list(device=device, region="Oxide"))
|
|
emag_ox = np.array(devsim.get_element_model_values(device=device, region="Oxide", name="Emag"))[::3]
|
|
|
|
x_mold = np.array(devsim.get_node_model_values(device=device, region="Molding", name="x")) / um
|
|
y_mold = np.array(devsim.get_node_model_values(device=device, region="Molding", name="y")) / um
|
|
pot_mold = np.array(devsim.get_node_model_values(device=device, region="Molding", name="Potential"))
|
|
tri_mold = np.array(devsim.get_element_node_list(device=device, region="Molding"))
|
|
emag_mold = np.array(devsim.get_element_model_values(device=device, region="Molding", name="Emag"))[::3]
|
|
|
|
def draw_device_boundaries(ax):
|
|
ax.plot([-W_DEVICE/um, W_DEVICE/um], [-T_OX/um, -T_OX/um], color='black', linestyle='--', linewidth=0.8)
|
|
ax.plot([-W_DEVICE/um, W_DEVICE/um], [0, 0], color='black', linestyle='-', linewidth=0.8)
|
|
ax.plot([-W_DEVICE/um, -W_DEVICE/um], [0, H_SI/um], color='black', linestyle='-', linewidth=0.8)
|
|
ax.plot([W_DEVICE/um, W_DEVICE/um], [0, H_SI/um], color='black', linestyle='-', linewidth=0.8)
|
|
ax.plot([-W_SIM/um, W_SIM/um], [H_SI/um, H_SI/um], color='black', linestyle='-', linewidth=1.2)
|
|
|
|
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 14))
|
|
|
|
# Plot Potential
|
|
tcf1_si = ax1.tripcolor(x_si, y_si, tri_si, pot_si, cmap='RdYlBu_r', shading='gouraud')
|
|
tcf1_ox = ax1.tripcolor(x_ox, y_ox, tri_ox, pot_ox, cmap='RdYlBu_r', shading='gouraud')
|
|
tcf1_mold = ax1.tripcolor(x_mold, y_mold, tri_mold, pot_mold, cmap='RdYlBu_r', shading='gouraud')
|
|
fig.colorbar(tcf1_si, ax=ax1, label='Electrostatic Potential (V)')
|
|
draw_device_boundaries(ax1)
|
|
ax1.set_xlabel('X (μm)')
|
|
ax1.set_ylabel('Y (μm)')
|
|
ax1.set_title(f'2D Electrostatic Potential at V = {v_current:.2f} V')
|
|
ax1.set_xlim(-W_SIM / um, W_SIM / um)
|
|
ax1.set_ylim(H_SI/um + 15.0, -110.0)
|
|
|
|
# Plot EField Magnitude
|
|
tcf2_si = ax2.tripcolor(x_si, y_si, tri_si, facecolors=emag_si, cmap='inferno', shading='flat')
|
|
tcf2_ox = ax2.tripcolor(x_ox, y_ox, tri_ox, facecolors=emag_ox, cmap='inferno', shading='flat')
|
|
tcf2_mold = ax2.tripcolor(x_mold, y_mold, tri_mold, facecolors=emag_mold, cmap='inferno', shading='flat')
|
|
fig.colorbar(tcf2_si, ax=ax2, label='Electric Field Magnitude (V/cm)')
|
|
draw_device_boundaries(ax2)
|
|
ax2.set_xlabel('X (μm)')
|
|
ax2.set_ylabel('Y (μm)')
|
|
ax2.set_title(f'2D Electric Field Magnitude at V = {v_current:.2f} V')
|
|
ax2.set_xlim(-W_SIM / um, W_SIM / um)
|
|
ax2.set_ylim(H_SI/um + 15.0, -110.0)
|
|
|
|
plt.tight_layout()
|
|
plt.savefig(f"{OUT_DIR}sweep_potential_2d.png", dpi=300)
|
|
plt.close()
|
|
|
|
print(f"Sweep visualization plots saved: sweep_iv_2d.png and sweep_potential_2d.png.")
|
|
import os; os.system(f'{sys.executable} plot_speed.py')
|