pchang718
841 lines
45 KiB
Python
841 lines
45 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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OUT_DIR = "output_this_run/"
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is_avalanche_enabled = os.environ.get("AVALANCHE", "false").lower() == "true"
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refine_v_step = float(os.environ.get("REFINE_V_STEP", "50.0"))
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is_refine_enabled = os.environ.get("REFINE", "true").lower() == "true"
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if refine_v_step < 1.0:
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is_refine_enabled = False
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print(f"refine_v_step < 1.0 V detected ({refine_v_step} V): Dynamic refinement is completely DISABLED.")
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print(f"Option: AVALANCHE={is_avalanche_enabled}, REFINE={is_refine_enabled}, REFINE_V_STEP={refine_v_step}V")
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os.makedirs(OUT_DIR, exist_ok=True)
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import shutil
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# 備份輸入幾何網格與配置參數，以及當前執行腳本本身以利模型重建
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try:
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if os.path.exists("device_2d.msh"):
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shutil.copy2("device_2d.msh", os.path.join(OUT_DIR, "device_2d.msh"))
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if os.path.exists("device_config.py"):
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shutil.copy2("device_config.py", os.path.join(OUT_DIR, "device_config.py"))
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if __file__:
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shutil.copy2(__file__, os.path.join(OUT_DIR, os.path.basename(__file__)))
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except Exception as e:
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print(f"Warning: Failed to back up reproduction archive files: {e}")
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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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# ----------------- LOAD CHECKPOINT (EARLY DETECT MESH) -----------------
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# 讀取指定引數
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specified_checkpoint = sys.argv[1] if len(sys.argv) > 1 else None
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valid_checkpoints = []
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if specified_checkpoint:
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# 1. 優先使用使用者指定的 Checkpoint 檔案
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if os.path.exists(specified_checkpoint):
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try:
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with open(specified_checkpoint, "rb") as f:
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data = pickle.load(f)
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# 驗證資料結構完整性
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if isinstance(data, dict) and ("v_current" in data or "voltage" in data) and "state" in data:
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mtime = os.path.getmtime(specified_checkpoint)
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v_val = data.get("v_current", data.get("voltage", 0.0))
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valid_checkpoints.append((mtime, v_val, specified_checkpoint, data))
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else:
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print(f"Error: Specified checkpoint {specified_checkpoint} format is invalid.")
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except Exception as e:
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print(f"Error reading specified checkpoint {specified_checkpoint}: {e}")
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else:
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print(f"Error: Specified checkpoint path '{specified_checkpoint}' does not exist.")
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else:
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# 2. 自動搜尋邏輯（原本的機制）
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search_dirs = ["output_this_run/"]
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for d in glob.glob("output_*"):
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if os.path.isdir(d):
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search_dirs.append(d + "/")
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search_dirs.append("./") # 最後搜尋根目錄
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for d in search_dirs:
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# 搜尋 WSL Checkpoints
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for name in ["wsl_recovery_checkpoint_A.pkl", "wsl_recovery_checkpoint_B.pkl"]:
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cp_path = os.path.join(d, name)
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if os.path.exists(cp_path):
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try:
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with open(cp_path, "rb") as f:
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data = pickle.load(f)
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if isinstance(data, dict) and ("v_current" in data or "voltage" in data) and "state" in data:
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mtime = os.path.getmtime(cp_path)
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v_val = data.get("v_current", data.get("voltage", 0.0))
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valid_checkpoints.append((mtime, v_val, cp_path, data))
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except Exception:
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pass
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# 搜尋 Recon Seeds (做為備份恢復源)
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for seed_path in glob.glob(os.path.join(d, "seed_*.pkl")):
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if os.path.exists(seed_path):
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try:
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with open(seed_path, "rb") as f:
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data = pickle.load(f)
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if isinstance(data, dict) and ("v_current" in data or "voltage" in data) and "state" in data:
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mtime = os.path.getmtime(seed_path)
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v_val = data.get("v_current", data.get("voltage", 0.0))
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valid_checkpoints.append((mtime, v_val, seed_path, data))
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except Exception:
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pass
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if not valid_checkpoints:
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raise RuntimeError("No valid rolling checkpoint or seed file found. Cannot resume run.")
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# 我們優先選擇「模擬電壓最大」的合法檔案作為起點；若電壓相同，則選修改時間最新者
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valid_checkpoints.sort(key=lambda x: (x[1], x[0]), reverse=True)
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latest_mtime, latest_voltage, latest_cp, cp_data = valid_checkpoints[0]
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print(f"Loading latest valid restore source: {latest_cp} (voltage: {latest_voltage} V, mtime: {time.ctime(latest_mtime)})")
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v_current = cp_data.get("v_current", cp_data.get("voltage"))
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step_size = cp_data.get("step_size", 0.1)
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step_count = cp_data.get("step_count", 0)
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voltage_list = cp_data.get("voltage_list", [v_current])
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current_list = cp_data.get("current_list", [0.0])
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next_recon_v = cp_data.get("next_recon_v", (v_current // refine_v_step + 1) * refine_v_step)
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state = cp_data["state"]
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# Check if checkpoint is refined
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is_refined = False
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silicon_state_len = len(cp_data["state"]["Silicon"]["Potential"])
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if silicon_state_len > 70000:
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is_refined = True
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step_size = max(step_size / 2.0, 0.1) # 載入細網格 Checkpoint 時，縮小步長至 1/2 以防首步發散
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if is_refined:
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# Look for refined mesh in the same directory as the checkpoint or in output_this_run/
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cp_dir = os.path.dirname(latest_cp)
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mesh_candidates = [
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os.path.join(cp_dir, "device_2d_refined.msh") if cp_dir else None,
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os.path.join("output_this_run", "device_2d_refined.msh")
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]
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mesh_file = None
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for cand in mesh_candidates:
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if cand and os.path.exists(cand):
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mesh_file = cand
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break
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if not mesh_file:
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import glob
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cands = glob.glob("**/device_2d_refined.msh", recursive=True)
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if cands:
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mesh_file = cands[0]
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if not mesh_file:
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raise RuntimeError("Refined checkpoint requires device_2d_refined.msh, but it was not found.")
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print(f"Refined checkpoint detected. Loading refined mesh: {mesh_file}")
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else:
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mesh_file = "device_2d.msh"
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print(f"Standard checkpoint detected. Loading base mesh: {mesh_file}")
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sys.path.append("/home/pchan/devsim2026")
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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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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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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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devsim.set_parameter(device=device, name="T", value="300")
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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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# Skip solving initial zero-bias Poisson since we will restore from checkpoint
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print("Skipping initial Poisson solve, preparing to restore from checkpoint...")
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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")
|
|
devsim.node_model(device=device, region="Silicon", name="IntrinsicHoles:Holes", equation="1")
|
|
|
|
devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge", equation="Holes - Electrons + NetDoping")
|
|
devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Potential", equation="0")
|
|
devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Electrons", equation="-1")
|
|
devsim.node_model(device=device, region="Silicon", name="IntrinsicCharge:Holes", equation="1")
|
|
|
|
devsim.node_model(device=device, region="Silicon", name="PotentialIntrinsicCharge", equation="0")
|
|
devsim.node_model(device=device, region="Silicon", name="PotentialIntrinsicCharge:Potential", equation="0")
|
|
|
|
# Mobility and drift diffusion equations
|
|
opts = CreateAroraMobilityLF(device, "Silicon")
|
|
# Bypassing HFMobility to prevent zero-bias convergence oscillations
|
|
CreateSiliconDriftDiffusion(device, "Silicon", **opts)
|
|
devsim.node_model(device=device, region="Silicon", name="LogElectrons", equation="log(Electrons + 1e-10) / log(10.0)")
|
|
devsim.node_model(device=device, region="Silicon", name="LogHoles", equation="log(Holes + 1e-10) / log(10.0)")
|
|
|
|
# Re-setup Silicon contacts for Drift-Diffusion
|
|
for c in silicon_contacts:
|
|
CreateSiliconDriftDiffusionContact(device, "Silicon", c, opts['Jn'], opts['Jp'])
|
|
|
|
# Skip solving initial zero-bias Drift-Diffusion
|
|
print("Skipping initial Drift-Diffusion solve, preparing to restore from checkpoint...")
|
|
|
|
# Switch continuity and potential equations for the bias sweep
|
|
print("Configuring continuity and potential equations for the bias sweep (min_error=1e5, positive update)...")
|
|
|
|
# Instantiate Avalanche (Impact Ionization) edge generation model if enabled
|
|
if is_avalanche_enabled:
|
|
CreateAvalancheGeneration(device, "Silicon", opts['Jn'], opts['Jp'])
|
|
|
|
av_model = "AvalancheGeneration" if is_avalanche_enabled else ""
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model=av_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=av_model,
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
devsim.equation(device=device, region="Silicon", name="PotentialEquation", variable_name="Potential",
|
|
node_model="PotentialNodeCharge", edge_model="DField", variable_update="default", min_error=1e-3)
|
|
|
|
# Setup E_mag_log element models
|
|
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)")
|
|
devsim.element_model(device=device, region=reg, name="E_mag_log", equation="asinh(Emag / 2.0) / log(10.0)")
|
|
|
|
# Save zero-bias tecplot and VTK
|
|
devsim.write_devices(file=f"{OUT_DIR}sweep_preview_0V.tec", type="tecplot")
|
|
# devsim.write_devices(file="sweep_preview_0V", type="vtk")
|
|
|
|
# 5. Define Sweep Parameters
|
|
v_target = 1000.0
|
|
if len(sys.argv) > 2:
|
|
try:
|
|
v_target = float(sys.argv[2])
|
|
print(f"Custom target voltage specified: {v_target} V")
|
|
except ValueError:
|
|
print(f"Warning: Invalid target voltage '{sys.argv[2]}', using default {v_target} V")
|
|
max_step = 50.0 # Maximum step size (V)
|
|
min_step = 1e-4 # Minimum step size (V)
|
|
compliance_current = 100e-3 # 100 mA compliance current
|
|
|
|
# Helper functions to save/restore state in case of convergence failure
|
|
def save_state(device):
|
|
state = {}
|
|
for region in ["Silicon", "Oxide", "Molding"]:
|
|
state[region] = {
|
|
"Potential": list(devsim.get_node_model_values(device=device, region=region, name="Potential"))
|
|
}
|
|
state["Silicon"]["Electrons"] = list(devsim.get_node_model_values(device=device, region="Silicon", name="Electrons"))
|
|
state["Silicon"]["Holes"] = list(devsim.get_node_model_values(device=device, region="Silicon", name="Holes"))
|
|
return state
|
|
|
|
def restore_state(device, state):
|
|
for region in ["Silicon", "Oxide", "Molding"]:
|
|
devsim.set_node_values(device=device, region=region, name="Potential", values=state[region]["Potential"])
|
|
devsim.set_node_values(device=device, region="Silicon", name="Electrons", values=state["Silicon"]["Electrons"])
|
|
devsim.set_node_values(device=device, region="Silicon", name="Holes", values=state["Silicon"]["Holes"])
|
|
|
|
|
|
# Variables were already loaded early from checkpoint
|
|
print(f"Resuming from V = {v_current:.4f} V, step = {step_size:.4f} V")
|
|
|
|
# 為了讓 log 連續，若 checkpoint 來自其他目錄，將舊日誌複製至當前的 output_this_run/ 中
|
|
cp_dir = os.path.dirname(latest_cp)
|
|
if cp_dir and cp_dir != OUT_DIR.rstrip("/"):
|
|
for log_name in ["simulation_time.log", "recon_avalanche.log"]:
|
|
old_log = os.path.join(cp_dir, log_name)
|
|
new_log = os.path.join(OUT_DIR, log_name)
|
|
if os.path.exists(old_log) and not os.path.exists(new_log):
|
|
try:
|
|
shutil.copy2(old_log, new_log)
|
|
print(f"Copied historical log {old_log} to {new_log} for continuity.")
|
|
except Exception as e:
|
|
print(f"Warning: Failed to copy historical log for continuity: {e}")
|
|
|
|
# Set initial contact biases to the resumed voltage v_current before restoring node values
|
|
# to avoid transient coordinate shock at the boundary during state loading
|
|
for c in ["MT1_Si", "MT1_P12_Si", "MT1_Ox", "MT1_Mold"]:
|
|
devsim.set_parameter(device=device, name=f"{c}_bias", value=v_current)
|
|
|
|
# Restore node values from checkpoint
|
|
restore_state(device, state)
|
|
|
|
# File logging setup (append mode for resume)
|
|
time_log = open(f"{OUT_DIR}simulation_time.log", "a", buffering=1)
|
|
with open(f"{OUT_DIR}recon_avalanche.log", "a") as f:
|
|
pass # Append mode for recon
|
|
|
|
start_sweep_time = time.time()
|
|
|
|
print("Resuming adaptive bias sweep...")
|
|
iter_history = []
|
|
sn = 0
|
|
just_refined = is_refined
|
|
if latest_cp and "seed_500V.pkl" in latest_cp:
|
|
step_size = 2.0528
|
|
just_refined = True
|
|
print(f"Resuming from seed_500V.pkl: forced initial step_size = {step_size:.4f} V, just_refined = {just_refined}")
|
|
|
|
|
|
# Targets for saving intermediate state checkpoints
|
|
save_targets = [5.0, 50.0, 500.0]
|
|
saved_targets = {t for t in save_targets if v_current >= t}
|
|
|
|
# Pre-refinement seed save targets
|
|
seed_save_targets = [5.0, 25.0, 45.0, 95.0, 195.0, 395.0, 595.0, 795.0, 995.0, 1195.0]
|
|
saved_seeds = {t for t in seed_save_targets if v_current >= t}
|
|
|
|
while v_current < v_target:
|
|
v_next = min(v_current + step_size, v_target)
|
|
|
|
# Apply new bias values to MT1 contacts
|
|
for c in ["MT1_Si", "MT1_P12_Si", "MT1_Ox", "MT1_Mold"]:
|
|
devsim.set_parameter(device=device, name=f"{c}_bias", value=v_next)
|
|
|
|
step_start_time = time.time()
|
|
try:
|
|
use_precondition = True
|
|
if use_precondition:
|
|
iters1 = 15
|
|
try:
|
|
# Always use log_damp preconditioning for Electron/Hole continuity equations in Stage 1
|
|
av_model = "AvalancheGeneration" if is_avalanche_enabled else ""
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model=av_model,
|
|
variable_update="log_damp", 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=av_model,
|
|
variable_update="log_damp", node_model="HoleGeneration", min_error=1e5)
|
|
res1 = devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-3, charge_error=1e12, maximum_iterations=7, rollback=False, info=True)
|
|
iters1 = len(res1.get("iterations", []))
|
|
except devsim.error:
|
|
pass # Ignore non-convergence in pre-conditioning
|
|
finally:
|
|
# Always revert to positive variable update for Stage 2 precision Newton
|
|
av_model = "AvalancheGeneration" if is_avalanche_enabled else ""
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model=av_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=av_model,
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
|
|
import psutil
|
|
mem_stage1 = psutil.Process(os.getpid()).memory_info().rss / (1024**3)
|
|
print(f"Stage 1 (Precondition) Memory Usage: {mem_stage1:.1f} GB")
|
|
else:
|
|
iters1 = 0
|
|
mem_stage1 = 0.0
|
|
|
|
# Stage 2: Precision Newton (Strict Tolerance)
|
|
res = devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-3, charge_error=1e12, maximum_iterations=20, info=True)
|
|
iters2 = len(res.get("iterations", []))
|
|
|
|
import psutil
|
|
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)
|
|
just_refined = False
|
|
|
|
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...")
|
|
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)")
|
|
devsim.element_model(device=device, region=reg, name="E_mag_log", equation="asinh(Emag / 2.0) / log(10.0)")
|
|
devsim.write_devices(file=f"{OUT_DIR}{filename}", type="tecplot")
|
|
saved_targets.add(target)
|
|
|
|
# Save pre-refinement seeds when crossing target voltages
|
|
for target in seed_save_targets:
|
|
if v_current >= target and target not in saved_seeds:
|
|
seed_filename = f"{OUT_DIR}seed_{int(target)}V.pkl"
|
|
state_to_save = save_state(device)
|
|
seed_data = {"voltage": v_current, "step_size": step_size, "state": state_to_save}
|
|
with open(seed_filename, "wb") as f:
|
|
pickle.dump(seed_data, f)
|
|
print(f"Saved pre-refinement seed checkpoint at V = {v_current:.2f} V to {seed_filename}")
|
|
saved_seeds.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 & DYNAMIC REFINE ---
|
|
if is_refine_enabled and (v_current >= next_recon_v):
|
|
import dynamic_refine
|
|
try:
|
|
# 1. 執行網格自適應重劃與狀態插值
|
|
refined_device, refined_opts = dynamic_refine.refine_and_interpolate(device, v_current, is_avalanche_enabled=is_avalanche_enabled, time_log=time_log)
|
|
device = refined_device
|
|
opts = refined_opts
|
|
just_refined = True
|
|
step_size = max(step_size / 5.0, 0.1) # 網格重建後，將步長縮小至 1/5 以防首步發散
|
|
|
|
# 2. 儲存優化後的狀態為 Seed
|
|
state = save_state(device)
|
|
seed_data = {"voltage": v_current, "step_size": step_size, "state": state}
|
|
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 refined seed to {seed_filename}")
|
|
|
|
if is_avalanche_enabled:
|
|
# Turn ON Avalanche (Use log_damp for Stage 1 pre-conditioning stability)
|
|
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="log_damp", 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",
|
|
variable_update="log_damp", node_model="HoleGeneration", min_error=1e5)
|
|
|
|
try:
|
|
# Stage 1 pre-conditioning
|
|
try:
|
|
devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-3, charge_error=1e12, maximum_iterations=7, rollback=False, info=True)
|
|
except devsim.error:
|
|
pass
|
|
|
|
import psutil
|
|
mem_recon_stage1 = psutil.Process(os.getpid()).memory_info().rss / (1024**3)
|
|
print(f"Recon Stage 1 Memory Usage: {mem_recon_stage1:.1f} GB")
|
|
|
|
# Switch to positive update for Stage 2 precision Newton solve
|
|
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",
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
|
|
# Stage 2 solve (Strict Tolerance)
|
|
res_av = devsim.solve(type="dc", absolute_error=1e10, relative_error=1e-3, charge_error=1e12, maximum_iterations=20, info=True)
|
|
|
|
mem_recon_stage2 = psutil.Process(os.getpid()).memory_info().rss / (1024**3)
|
|
print(f"Recon Stage 2 Memory Usage: {mem_recon_stage2:.1f} GB")
|
|
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 Reset Avalanche state to main loop configuration
|
|
restore_state(device, state)
|
|
av_model = "AvalancheGeneration" if is_avalanche_enabled else ""
|
|
devsim.equation(device=device, region="Silicon", name="ElectronContinuityEquation", variable_name="Electrons",
|
|
time_node_model="NCharge", edge_model=opts['Jn'], edge_volume_model=av_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=av_model,
|
|
variable_update="positive", node_model="HoleGeneration", min_error=1e5)
|
|
else:
|
|
print("Avalanche probe skipped (AVALANCHE option is disabled).")
|
|
print("--- END RECON PROBE ---\n")
|
|
next_recon_v += refine_v_step
|
|
except devsim.error as ref_err:
|
|
print(f"\n!!! DYNAMIC REFINE FAILED at {v_current:.2f} V: {ref_err} !!!")
|
|
print("Restoring coarse device state and continuing simulation on the COARSE mesh.")
|
|
restore_state(device, state)
|
|
next_recon_v += refine_v_step
|
|
|
|
# Grow step size for next step adaptively based on Newton iterations (Rolling average)
|
|
iter_history.append(total_iters)
|
|
if len(iter_history) > 3:
|
|
iter_history.pop(0)
|
|
avg_iters = sum(iter_history) / len(iter_history)
|
|
|
|
eff_iters = max(0.0, avg_iters - sn)
|
|
if avg_iters > 14.0:
|
|
step_size = max(step_size * 0.6, min_step)
|
|
sn = 0
|
|
elif eff_iters < 10.0:
|
|
step_size = min(step_size * 1.2, max_step)
|
|
sn = 0
|
|
else:
|
|
sn += 1
|
|
|
|
step_count += 1
|
|
|
|
# Ping-pong rolling checkpoint
|
|
if step_count > 0 and step_count % 10 == 0:
|
|
checkpoint_file = f"{OUT_DIR}wsl_recovery_checkpoint_A.pkl" if (step_count // 10) % 2 != 0 else f"{OUT_DIR}wsl_recovery_checkpoint_B.pkl"
|
|
checkpoint_data = {
|
|
"v_current": v_current,
|
|
"step_size": step_size,
|
|
"step_count": step_count,
|
|
"voltage_list": voltage_list,
|
|
"current_list": current_list,
|
|
"next_recon_v": next_recon_v,
|
|
"state": state
|
|
}
|
|
with open(checkpoint_file, "wb") as f:
|
|
pickle.dump(checkpoint_data, f)
|
|
print(f"Rolling checkpoint saved to {checkpoint_file}")
|
|
time_log.write(f"Rolling checkpoint saved to {checkpoint_file}\n")
|
|
|
|
# Active garbage collection to prevent memory accumulation
|
|
gc.collect()
|
|
|
|
# Force Intel MKL to release thread buffers
|
|
try:
|
|
import ctypes
|
|
import glob
|
|
import sys
|
|
import os
|
|
mkl_libs = glob.glob(os.path.join(os.path.dirname(sys.executable), "../lib/libmkl_rt.so.*"))
|
|
if mkl_libs:
|
|
ctypes.CDLL(mkl_libs[0]).MKL_Free_Buffers()
|
|
# Force glibc to return freed memory to the OS (mitigate malloc fragmentation)
|
|
libc = ctypes.CDLL("libc.so.6")
|
|
libc.malloc_trim(0)
|
|
except Exception as e:
|
|
pass
|
|
|
|
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
|
|
iter_history = [] # Reset iteration history on failure
|
|
sn = 0 # Reset counter on failure
|
|
|
|
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
|
|
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)")
|
|
devsim.element_model(device=device, region=reg, name="E_mag_log", equation="asinh(Emag / 2.0) / log(10.0)")
|
|
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/cm)", delimiter=",")
|
|
|
|
# Plot and save I-V curve
|
|
plt.figure(figsize=(8, 6))
|
|
plt.plot(voltage_list, np.abs(current_list), 'o-', color='#1f77b4', markersize=2)
|
|
plt.yscale('log')
|
|
plt.grid(True, which="both", ls="--")
|
|
plt.xlabel("Bias Voltage (V)")
|
|
plt.ylabel("Terminal Current (A/cm, Log Scale)")
|
|
plt.title(SIM_NAME)
|
|
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.")
|
|
|
|
# Clean up rolling checkpoints upon successful completion
|
|
if v_current >= v_target:
|
|
print("Sweep completed successfully. Cleaning up rolling checkpoints...")
|
|
for cp in [f"{OUT_DIR}wsl_recovery_checkpoint_A.pkl", f"{OUT_DIR}wsl_recovery_checkpoint_B.pkl"]:
|
|
if os.path.exists(cp):
|
|
os.remove(cp)
|
|
else:
|
|
print(f"Sweep did not reach target voltage ({v_target} V). Keeping rolling checkpoints for recovery (current V = {v_current:.2f} V).")
|
|
|
|
import os; os.system(f'{sys.executable} plot_speed.py')
|