Chemical Mechanical Planarization Critical in Multilayer Device Fabrication

🔬 Why Photoresist Alone is Not Enough — The Importance of Hard Masks in Advanced Semiconductor Manufacturing In semiconductor fabrication, lithography defines the pattern — but etching defines the structure. One common question I often hear (especially from students and early-career engineers) is: If photoresist (PR) defines the pattern, why do we need a hard mask at all? Let’s break it down. 🧪 The Limitation of Photoresist (PR) Photoresist is an organic polymer designed primarily for pattern definition during lithography. However, when we move into plasma etching — especially for advanced nodes — PR faces several critical limitations: 1️⃣ Limited Etch Resistance PR erodes quickly under: High RF power Long plasma exposure Reactive chemistries This leads to: CD loss Profile distortion Line width variation Pattern collapse 2️⃣ Deep or High Aspect Ratio Etches Processes such as: STI trench formation Deep contact etch Gate patterning require long, anisotropic etches. PR simply cannot survive the full duration of these processes without significant degradation. 3️⃣ Advanced Nodes & Thin PR (EUV Era) With EUV lithography, PR thickness can be as low as 20–40 nm. Thinner PR = lower etch margin. Using PR directly as an etch mask becomes extremely risky. 🛡️ Enter the Hard Mask A hard mask is an inorganic, etch-resistant layer deposited below the PR layer. Common materials include: SiO₂ Si₃N₄ Amorphous carbon TiN Typical Process Flow: Deposit hard mask Apply PR and pattern it Transfer PR pattern to hard mask Strip PR Use hard mask to etch underlying layer Now, the hard mask — not PR — withstands the aggressive plasma etch. 🎯 From a Process Integration Perspective Hard mask selection directly impacts: Etch selectivity Profile control Overlay budget Stack thickness CMP interaction Defectivity Overall yield Yes, it adds extra process steps. But in advanced technology nodes, it’s not optional — it’s strategic. 💡 Simple Analogy Photoresist is like a paper stencil. A hard mask is like a steel stencil. If you're doing light sanding, paper works. If you're sandblasting aggressively, you need steel. As nodes shrink and structures become more complex, materials engineering becomes just as critical as patterning technology. Hard masks are no longer just an option — they are enablers of modern semiconductor scaling.

Gelest, Inc. in research pact with IBM to test dry resist EUV lithography precursors   Gelest, Inc., a Mitsubishi Chemical Group company and US-based manufacturer of silicones, silanes and metal-organics, has signed a research agreement with technology giant, IBM, to test Gelest precursor materials for dry resist EUV (Extreme Ultraviolet) lithography.   The research collaboration will enable Gelest to see the performance results of its materials for dry resist EUV technology, an advanced semiconductor manufacturing technique driving the next generation of logic and DRAM technologies for the semiconductor market.   “The results of IBM testing will inform the kind of materials we make next,” said Ms. Allison Bezden, Gelest, Inc. global program manager – semiconductor materials. “The collaboration with IBM will aim to speed up innovation cycles and allow Gelest to make data-driven decisions, to make iterations in the lab and to drive the industry forward toward smaller and smaller microelectronic devices.”   As part of the collaboration, IBM will leverage its baseline EUV process flows and capabilities to evaluate new materials and concepts from Gelest for use in High NA EUV lithography processes.   “Collaborations like this are essential to understanding the processes and materials that will support continued scaling to develop smaller, more powerful, and energy-efficient semiconductors needed for the AI era,” said Mr. Huiming Bu, Vice President, IBM Semiconductors Global R&D and Albany Operations, IBM Research.   In May 2025, Gelest opened a new 50,000-square-foot production facility to increase its production capabilities and support microelectronics and other customer applications, with the main focus on developing and manufacturing precursor chemicals for use in dry resist EUV lithography. Read more: https://lnkd.in/dyEGKpBp Follow Chemical Weekly page for regular industry updates   Subscribe to Chemical Weekly magazine: https://lnkd.in/g3S4ZSu9   #chemicals #chemicalindustry #chemicalweekly #specialitychemicals #chemical www.chemicalweekly.com

If you’re in electronics, aerospace, medical devices, EVs, or advanced manufacturing, you already know this: everything starts with the chip. But behind every semiconductor is an ultra-precise ecosystem of equipment, enclosures, frames, tooling, and components that must meet cleanroom, tolerance, and durability demands. https://lnkd.in/ea8znrzu In the link above, we offer a plain-English breakdown of how semiconductor manufacturing works — and where precision fabrication and CNC machining support the companies building this equipment. In the article, you’ll learn: - The key stages of semiconductor manufacturing (from wafer to packaged chip) - Why cleanroom compatibility and microscopic tolerances matter - The challenges chipmakers face with miniaturization, heat, and supply chain risk - How precision sheet metal and machined components fit into this advanced process If you work anywhere along the electronics or semiconductor supply chain, this is a helpful read. #Semiconductor #AdvancedManufacturing #PrecisionMachining #SheetMetal #Cleanroom #ElectronicsManufacturing #AerospaceManufacturing #MedicalDeviceManufacturing #USManufacturing #EagleMetalcraft

Why most thermal metamaterial manufacturing over-invests in the wrong parameters — and a systematic fix. – TP-Ch13 (February 21, 2026)   In conventional practice, every layer gets the same ±5% tolerance, every parameter gets the same lot sampling, every interface gets the same inspection protocol. It feels rigorous. But uniform allocation concentrates effort on parameters that have negligible impact on system performance, while under-investing in the few that actually dominate yield. In Chapter 13 of Thermal Photonics (Book 3, Open-Source Engineering Optics Trilogy), I use the Mode-Path Matrix — the same framework from Chapter 4 — as a production engineer. 🟨 The key is the sensitivity coefficient: 💎 beta_i = d(ln G_sys) / d(ln p_i) For every fabrication parameter (layer thickness, conductivity, interface resistance, emissivity), this single number drives: ◾Tolerance allocation: high-sensitivity parameters get ±1–2%; low-sensitivity ones can relax to ±20%+ ◾Metrology specification: 100% inspection where |beta| > 0.5; first-article qualification only where |beta| ≤ 0.1 ◾Instrument selection: 3-omega for cross-plane kappa, TDTR for interfaces, FTIR for emissivity — chosen to match the required precision, not applied uniformly A 10-layer metamaterial has ~30 measurable parameters. The MPM typically identifies 3–5 that control system performance. Measure those rigorously. Sample the rest. You tighten what matters and relax what doesn't — improving yield while reducing cost. 🟨Two aspects make this chapter unusual: 1️⃣The Observer Effect. ◾Every measurement probe adds a parasitic thermal path. ◾We define a 5% perturbation criterion (DR-13.10) and specify maximum allowable probe conductance. ◾This becomes the direct bridge to Chapter 14 (quantum thermal), where contact metrology is fundamentally incompatible with the system being measured. 2️⃣Gamma Validation. ◾Instead of testing only component properties, we design a Thermal Test Vehicle mirroring the MPM topology and measure the mode dominance ratio on every path. ◾The question shifts from "is the film 100 nm thick?" to "does the system still classify correctly on each thermal path?" 🟨 As stated in the chapter: a prescription is not a product. The MPM closes that gap.   Confidentiality: All content is my personal work and contains no employer/client information.   #ThermalEngineering #SemiconductorManufacturing #Metrology #ThermalMetamaterials #OpenScience #ModePathMatrix  

3 ways FIB-SEM is utilized across advanced nodes As semiconductor manufacturing moves into sub-10 nm nodes, inspection is no longer about finding more defects—it’s about understanding the ones that matter. At these dimensions, yield and reliability are limited by buried nanoscale variations, which is why advanced fabs such as TSMC, Intel, and Samsung Foundry rely on FIB-SEM for defect identification and process optimization across the wafer lifecycle. Now the question is - How FIB-SEM Is Utilized Across Advanced Nodes – Well there are 3 ways: Lithography & Pattern Transfer (Reticles → Wafer) At EUV nodes, even small deviations can propagate across millions of devices. FIB-SEM enables site-specific cross-sectioning to verify pattern fidelity, analyze line-edge roughness through etch/clean steps, and identify buried profile distortions invisible to top-down inspection. BEOL & Interconnect Reliability As scaling pressure shifts to BEOL, interconnect integrity becomes critical. FIB-SEM is used to visualize voids and seams, investigate electromigration-prone regions, and correlate microstructural damage with deposition and annealing—often before electrical failure is detected. 3D Architectures & Yield Learning With FinFETs, GAA, 3D NAND, and heterogeneous integration, failure mechanisms are increasingly vertical. FIB-SEM helps inspect gate stacks and contacts, track defect propagation across layers, and accelerate yield learning during ramp-up. The attached image shows a FIB-prepared lamella from my own work, published in “Ce³⁺-doped chalcogenide glass fibre for laser emission beyond 4 µm wavelength”. Using FIB-SEM and HR-TEM, we isolated targeted defects (image (a) & (b)), prepared site-specific lamellae (image (c) & (d)), and revealed nanoscale impurities introduced during fibre processing—long before macroscopic failure appeared (image (e) & (d)). Although the application was optical fibres rather than CMOS, the lesson translates directly to advanced semiconductor manufacturing: If material integrity is compromised at the nanoscale, performance and lifetime are already at risk—whether the device is a laser fibre or a logic transistor. Why This Matters at Advanced Nodes As margins shrink and architectures grow more complex: • Variability is no longer averaged out • There’s no room for error anymore • Reliability must be engineered upstream FIB-SEM sits at the intersection of inspection, defect identification, and process optimization, enabling fabs to connect physical evidence with manufacturing decisions—early enough to matter. Below 10 nm, success isn’t defined by what you can pattern. It’s defined by what you can physically see, understand, and correct in time. #FIBSEM #SemiconductorManufacturing #Inspection #DefectIdentification #ProcessOptimization #AdvancedNodes #Wafer #Reticles #BEOL #MaterialsIntegrity

40% capacity increase, 20% smaller footprint, high flexibility and new features on board: That's the next generation EVG®120! The new, ultra-compact platform adds in-situ resist thickness metrology, wafer edge exposure and incorporates the design encancements leveraged from the widely adopted EVG®150 system. The system will be launched next week at the SPIE Advanced Lithography and Patterning (SPIE-AL+P) Conference where we will also be participating in the technical program: - “High aspect ratio copper pillar structures enabled by digital lithography patterning of thick resists for AI and HPC device packages” (Wed., Feb. 25, 8:10-8:40am, Room 211B) – presented by Dr. Ksenija Varga, Business Development Manager, EV Group; co-authored with JSR Micro and TECHNIC France - “Lithography digitalization in semiconductor technologies through advanced software development of high-throughput maskless exposure” (Thu., Feb. 26, 8:00-8:20am, Room 211B) – presented by Alois Malzer, Product Manager, EV Group - “Ultrasonic spray coating combined with maskless lithography for advanced wafer singulation with complex bump geometries”  (Thu., Feb. 26, 9:20-9:40am, Room 210C) – presented by Johanna Rimböck, Scientist, EV Group - “Exploration and mitigation of local wafer deformations resulting from direct wafer-to-wafer bonding” (Wed., Feb. 25, 5:10-5:30pm, Room 211B) – co-authored with ASML and CEA-Leti To find out more, head over to our website: https://lnkd.in/d8pkT4Zu

We are launching our newest coating & development system EVG120 at SPIE 2026. Visit my invited talk and learn more about Digital Exposure Technology and advanced software features.

A single hair can absolutely spoil chip manufacturing — and here’s why 👇 Semiconductor fabrication happens at an extreme microscopic scale. ⸻ 1️⃣ The Scale Difference Is Massive • Human hair thickness ≈ 70–100 micrometers • Modern chips (like those from TSMC or Intel) are built at 3–7 nanometers 👉 1 micrometer = 1,000 nanometers 👉 A human hair is 10,000–30,000 times thicker than critical chip features. To a chip, a hair is like a tree trunk falling on a highway. ⸻ 2️⃣ Chips Are Built Layer by Layer During fabrication: • Silicon wafer is coated • Patterns are printed using photolithography • Materials are etched and deposited • This is repeated hundreds of times If a hair lands on the wafer: • It blocks light during lithography • Causes incomplete etching • Creates short circuits • Misaligns layers Result? Entire chip (or wafer section) becomes defective. ⸻ 3️⃣ It’s Not Just the Hair — It’s the Particles Hair carries: • Dust • Skin flakes • Oil • Static charge Even a tiny dust particle (smaller than hair) can ruin circuits. That’s why chip fabs use: • Class 1 cleanrooms • Full body “bunny suits” • HEPA + ULPA filtration • Strict airflow control ⸻ 4️⃣ Cost Impact One advanced wafer can cost thousands of dollars. A contamination event can destroy millions worth of production. Companies like ASML build machines so precise that even vibration from footsteps is controlled. Imagine what a hair can do. ⸻ Simple Analogy If chip manufacturing is like drawing ultra-thin pencil lines on paper… A hair is like dropping a rope across the page. Everything underneath becomes unreadable.

Advanced lithography is no longer just a manufacturing topic—it has become a strategic inflection point for the entire semiconductor ecosystem. Recent industry discussions around EUV scaling, high-NA adoption, and patterning complexity highlight a shift from pure node shrink to integration efficiency. Yield learning cycles, process window control, and defectivity management are now as critical as resolution itself. As device architectures move toward GAA, backside power delivery, and heterogeneous integration, lithography decisions increasingly determine downstream variability, cycle time, and cost per wafer. The challenge is not only printing smaller features, but enabling stable, repeatable, high-volume manufacturing under tighter tolerances. Key themes emerging across fabs and equipment partners: Process-driven design enablement rather than design-constrained processes Early co-optimization between materials, patterning strategy, and metrology Data-centric yield engineering and faster excursion response Balancing high-NA benefits with throughput and cost realities Stronger cross-functional alignment between process integration and manufacturing operations In this environment, process development is becoming a systems problem. The competitive edge lies in how quickly organizations can translate lithography innovation into manufacturable, high-yield flows. Scaling is no longer measured only in nanometers—it is measured in stability, learning rate, and manufacturability. #Semiconductor #EUV #Lithography #ProcessEngineering #AdvancedNodes #YieldEngineering #HighNA #Manufacturing

Quantum technologies promise secure communication networks and powerful new forms of information processing, but building these systems at scale remains a major challenge. Diamond is an especially attractive material for quantum devices because it can host atomic-scale defects that emit single photons and store quantum information with exceptional stability. However, fabricating the optical structures needed to control light in diamond typically relies on slow, bespoke processes that are difficult to scale. In this work, we introduce a manufacturing approach that brings diamond quantum photonics closer to industrial production. Instead of sequentially defining each device by lithography written directly on diamond, we fabricate high-precision silicon masks using commercial semiconductor foundries and transfer them onto diamond via microtransfer printing. These masks define large arrays of nanoscale optical structures, shifting the most demanding pattern-definition steps away from the diamond substrate, improving uniformity, yield, and throughput. Using this method, we demonstrate hundreds of diamond "quantum microchiplets" with improved optical performance and controlled interaction with quantum emitters. The chiplet format allows defective devices to be replaced and enables integration with existing photonic and electronic circuits. Our results show that high-quality diamond quantum devices can be produced using scalable, foundry-compatible techniques. This approach provides a practical pathway toward large-scale quantum photonic systems and hybrid quantum-classical technologies built on established semiconductor manufacturing infrastructure.