2,942 technical terms and definitions
scanning electron microscope, sem, metrology
Scanning Electron Microscope (SEM) is the most widely used high-resolution imaging tool in semiconductor manufacturing — scanning a focused electron beam across a surface…
critical dimension CD measurement, secondary electron imaging, electron beam metrology, SEM defect detection, beam spot size focus, backscattered electron analysis, high resolution nanostructure imaging
Scanning electron microscopy forms an image by rastering a focused electron beam across a sample surface and detecting the electrons that the beam-sample interaction produces…
scanning electron microscopy defect morphology, scanning electron microscopy, electron microscopy defect, microscopy defect morphology, scanning electron, electron microscopy
Scanning Electron Microscopy Defect Morphology with Machine Learning Introduction & Motivation Scanning Electron Microscopy Defect Morphology with Machine Learning addresses…
metrology
Scanning Kelvin probe microscopy (SKPM), also called Kelvin probe force microscopy (KPFM), uses an oscillating atomic force microscope (AFM) cantilever tip to measure contact…
scanning microwave impedance microscopy carrier density prediction, scanning microwave impedance, microwave impedance microscopy, scanning microwave
Scanning Microwave Impedance Microscopy Carrier Density Prediction with Machine Learning Introduction & Motivation Scanning Microwave Impedance Microscopy Carrier Density…
smm, metrology
Spectroscopic ellipsometry and inline optical wafer metrology constitute the non-destructive physical measurement and defect detection disciplines that govern yield control across…
scanning near-field optical microscopy, snom, metrology
Scanning Near-Field Optical Microscopy (SNOM/NSOM) is an optical imaging technique that overcomes the diffraction limit of conventional far-field microscopy by scanning…
scanning probe microscopy, spm, metrology
Scanning Probe Microscopy (SPM) is a family of surface characterization techniques that measure surface properties by scanning a sharp physical probe across the sample — achieving…
ssrm, metrology, dopant profiling, diamond AFM tip, spreading resistance, staircase calibration, FinFET characterization, 2D doping profile, carrier concentration mapping
Scanning spreading resistance microscopy (SSRM) is a contact-mode atomic force microscopy technique that maps dopant concentration across a two-dimensional cross-section of…
metrology
Scanning Surface Inspection Systems (SSIS) are the automated laser-scanning metrology tools that perform full-wafer defect mapping on bare or patterned wafers — generating…
scanning tunneling microscope, stm, metrology
Scanning Tunneling Microscope (STM) is a surface analysis instrument that achieves true atomic resolution by measuring quantum mechanical tunneling current between an atomically…
SCARF Self-Supervised Contrastive Learning using Random Feature Corruption Introduction & Motivation SCARF Self-Supervised Contrastive Learning using Random Feature Corruption…
quality & reliability
Scatter Plot Quality is a bivariate plot used to examine relationships between candidate cause variables and quality responses - It is a core method in modern semiconductor…
lithography
A scattering bar is the most common type of sub-resolution assist feature (SRAF) — a thin line placed on the photomask parallel to and near a main feature to improve its imaging…
device physics
Scattering Mechanisms are the physical interactions that interrupt the ballistic motion of charge carriers (electrons and holes) in a semiconductor, transferring momentum…
optical scatterometry, semiconductor scatterometry, grating scatterometry
Optical critical-dimension scatterometry infers the average geometry of a periodic semiconductor pattern from how that pattern changes reflected or diffracted light. The tool may…
euv scatterometry, euv metrology, actinic scatterometry, lithography metrology
EUV Scatterometry is the optical metrology technique that uses extreme ultraviolet light at 13.5 nm wavelength to measure critical dimensions, overlay, and film properties…
inline cd measurement, optical profile metrology, scatterometry sidewall angle
Optical critical-dimension scatterometry infers the average geometry of a periodic semiconductor pattern from how that pattern changes reflected or diffracted light. The tool may…
scatterometry cd measurement drift prediction machine learning, scatterometry cd, measurement drift prediction, cd, scatterometry cd measurement drift prediction
Scatterometry CD Measurement Drift Prediction with Machine Learning Introduction & Motivation Scatterometry CD Measurement Drift Prediction with Machine Learning addresses…
scatterometry inverse modeling with neural network machine learning, scatterometry inverse modeling, inverse modeling neural, modeling neural network, inverse modeling
Scatterometry Inverse Modeling with Neural Network Machine Learning Introduction & Motivation Scatterometry Inverse Modeling with Neural Network Machine Learning addresses…
scatterometry model fit residual prediction machine learning, scatterometry model, fit residual prediction, cd ocd, scatterometry model fit residual prediction, model fit
Scatterometry Model Fit Residual Prediction with Machine Learning Introduction & Motivation Scatterometry Model Fit Residual Prediction with Machine Learning addresses a central…
ocd scatterometry, optical critical dimension scatterometry, inline ocd metrology
Optical critical-dimension scatterometry infers the average geometry of a periodic semiconductor pattern from how that pattern changes reflected or diffracted light. The tool may…
metrology, diffraction-based overlay, spectroscopic overlay, micro-DBO, 2D grating target, swing curve, overlay throughput, in-die overlay target, optical overlay measurement
Scatterometry overlay measures how precisely two patterned layers line up by analyzing the spectral signature light produces when it reflects or diffracts off a specialized…
scatterometry overlay recipe drift prediction machine learning, scatterometry overlay, recipe drift prediction, scatterometry overlay recipe drift prediction, recipe drift
Scatterometry Overlay Recipe Drift Prediction with Machine Learning Introduction & Motivation Scatterometry Overlay Recipe Drift Prediction with Machine Learning addresses…
scenario-based testing
Scenario-Based Testing Introduction & Motivation Scenario-Based Testing addresses a central problem in verification process control and scenario-completeness-percentage…
Scene Captioning and Description Introduction & Motivation Scene Captioning and Description addresses a central problem in multimodal learning and caption-informativeness-accuracy…
computer vision
Scene Decomposition is the task of breaking down a visual scene into its constituent components—individual objects, background, and their spatial relationships—enabling separate…
computer vision
Scene Flow is the 3D motion estimation task that computes a dense 3D velocity vector for every point in a scene — the three-dimensional generalization of optical flow that…
scene flow 3d motion, scene flow 3d, flow 3d motion, scene flow, flow 3d, 3d motion
Scene Flow 3D Motion Introduction & Motivation Scene Flow 3D Motion addresses a central problem in vision process control and scene-flow-optical-flow-3d prediction: how to Predict…
video understanding
Scene flow estimation is the task of predicting 3D motion vectors for scene points over time, extending optical flow from image-plane displacement to physical-space dynamics - it…
computer vision
Scene graph generation is the task of converting an image into a graph of objects and labeled relationships that captures scene structure - it provides explicit symbolic…
Scene Graph Generation from Images Introduction & Motivation Scene Graph Generation from Images addresses a central problem in multimodal learning and relationship-accuracy-recall…
computer vision
Scene graph parsing is the process of interpreting or refining scene graph structures from visual data or language descriptions into consistent relational representations - it…
3D Scene Synthesis and Composition Introduction & Motivation 3D Scene Synthesis and Composition addresses a central problem in generative generation and scene-realism-quality…
computer vision
Scene understanding is the capability of AI systems to comprehend visual scenes holistically — recognizing objects, understanding spatial relationships, inferring context…
3D Scene Understanding with Language Introduction & Motivation 3D Scene Understanding with Language addresses a central problem in multimodal learning and scene-language-alignment…
scene understanding context, scene understanding, understanding context
Scene Understanding Context Introduction & Motivation Scene Understanding Context addresses a central problem in vision process control and scene-classification-place-recognition…
quality & reliability
Schedule Performance Index is a schedule-efficiency ratio comparing earned value to planned value - It is a core method in modern semiconductor project and execution governance…
production
Scheduled maintenance is the planned periodic downtime for semiconductor equipment to perform preventive maintenance activities — ensuring tool reliability, process quality…
production
Scheduled vs unscheduled downtime is the classification of tool nonproductive time into planned maintenance windows versus unexpected failure interruptions - the ratio between…
scheduler algorithm fairness, scheduler algorithm, algorithm fairness
Scheduler Algorithm Fairness Introduction & Motivation Scheduler Algorithm Fairness addresses a central problem in systems process control and scheduling-latency-response-time…
scheduler resource allocation, scheduler resource, resource allocation
Scheduler Resource Allocation Introduction & Motivation Scheduler Resource Allocation addresses a central problem in cloud process control and scheduling-strategy-bin-packing…
instruction scheduling with resource constraints, instruction scheduling resource, scheduling resource constraints, instruction scheduling, scheduling resource
Instruction Scheduling with Resource Constraints Introduction & Motivation Instruction Scheduling with Resource Constraints addresses a central problem in compiler-optimization…
schema design normalization, schema design, design normalization
Schema Design Normalization Introduction & Motivation Schema Design Normalization addresses a central problem in programming process control…
structured generation
Schema enforcement is the practice of forcing LLM outputs to strictly conform to a predefined data schema — typically a JSON Schema — that specifies exact field names, data types…
schema evolution and compatibility, schema evolution compatibility, schema evolution, evolution compatibility
Schema Evolution and Compatibility Introduction & Motivation Schema Evolution and Compatibility addresses a central problem in ml-ops process control…
Schema Matching via Similarity Flooding and Embeddings Introduction & Motivation Schema Matching via Similarity Flooding and Embeddings addresses a central problem in {subject}…
optimization
Schema Validation is post-generation verification that output fields, types, and required keys match an expected schema - It is a core method in modern semiconductor AI serving…
machine learning force field, atomistic neural network, molecular simulation ai, interatomic potential
Etch Plasma–Surface SchNet and Invariant Neural Interatomic Potential Modeling uses continuous-filter atomistic neural networks to learn a smooth, energy-conserving approximation…
graph neural networks
SchNet is a continuous-filter convolutional network designed for atomistic and molecular property prediction - Learned continuous interaction filters model distance-dependent…