Memory, Emerging Devices & Radiation Effects

Memory, Emerging Devices & Radiation Effects: Semiconductor Memory: SRAM, DRAM, ROM, EEPROM & Flash, SRAM & Memory Design, Non-Volatile Memory Physics: Floating Gate, Charge Trap & Tunnelling, Emerging Devices: TFETs, 2-D FETs, ReRAM, PCM, MRAM & Neuromorphic, Radiation Effects in Semiconductor Devices.

• Semiconductor Memory: SRAM, DRAM, ROM, EEPROM & Flash — How chips store bits. Learn SRAM (6T cell of cross-coupled inverters, read/write, static noise margin, stability vs sizing, leakage), DRAM (1T1C cell, charge storage, charge sharing onto bit lines, sense amplifiers, refresh and retention, trench vs stacked capacitors, row-hammer), ROM family (mask ROM, PROM, EPROM, EEPROM), and flash (floating-gate and charge-trap cells, NAND vs NOR arrays, program/erase, MLC/TLC/QLC multi-level storage, endurance and retention, 3D NAND) — with Python computing DRAM electrons, bit-line signal, retention and refresh margin, flash V_T shift per electron and multi-level spacing.
• SRAM & Memory Design — Memories fill most of a modern SoC's area. Learn the 6T SRAM cell, read and write operations, read stability and writability (cell ratio, pull-up ratio), static noise margin, array organisation (rows, columns, decoders, sense amplifiers), bitline timing, memory compilers, register files, DRAM and non-volatile memories, and how RTL infers memories.
• Non-Volatile Memory Physics: Floating Gate, Charge Trap & Tunnelling — The physics that lets flash remember. Learn the floating-gate transistor and coupling ratios, charge-trap (SONOS/TANOS) cells, Fowler-Nordheim tunnelling through a triangular barrier and its extreme field dependence, channel hot-electron injection, threshold-voltage shift, incremental step-pulse programming, erase mechanisms, retention loss (trap-assisted leakage, detrapping), endurance degradation (oxide trap generation, SILC), read/program/pass disturb, wear, and multi-level storage — with Python computing FN current density vs field, the programming time for a given charge, and Arrhenius retention acceleration for bake tests.
• Emerging Devices: TFETs, 2-D FETs, ReRAM, PCM, MRAM & Neuromorphic — What might come next — and how mature it really is. For each technology — tunnel FETs, 2-D material FETs (MoS₂, WSe₂) and graphene devices, nanowire/GAA extensions, memristors and resistive RAM, phase-change memory, spin-transfer and spin-orbit-torque MRAM, ferroelectric FETs/FeRAM, spintronic logic concepts, neuromorphic and in-memory computing devices, single-electron transistors, quantum-device concepts and molecular electronics — learn structure, operating principle, potential advantage, main limitation and research/application status (from production to research-only), without overstating maturity — with Python comparing subthreshold swings, MRAM TMR, PCM windows, crossbar sneak paths and 2-D channel scale length.
• Radiation Effects in Semiconductor Devices — Semiconductors in space, accelerators and nuclear environments — and on the ground. Learn radiation environments (trapped protons/electrons, solar particles, galactic cosmic rays, atmospheric neutrons, alpha particles from packaging), total ionising dose (oxide-trapped charge and interface traps → V_T shifts, leakage), displacement damage (lifetime and mobility degradation in bipolar, optoelectronic and solar devices), single-event effects (SEU, SET, SEL, SEB, SEGR), linear energy transfer and critical charge, and hardening (radiation-hardened processes, SOI, enclosed-layout transistors, guard rings, TMR, EDAC, latch-up current limiting) — with Python relating LET to collected charge, critical charge vs node, and TID sensitivity vs oxide thickness.