DEV Community

AtlasPCBEngineering
AtlasPCBEngineering

Posted on • Originally published at atlaspcb.com

Glass Core Substrates for AI Packaging: How Intel's Clearwater Forest Changes the PCB Substrate Roadmap

The Organic Substrate Wall

For two decades, Ajinomoto Build-up Film (ABF) substrates have been the foundation of advanced semiconductor packaging. The laminate-based approach — layer upon layer of resin-coated copper foil, mechanically drilled and chemically etched — scaled elegantly from flip-chip packages to today's complex multi-die architectures.

But organic substrates have hit a physics wall. As AI accelerators grew larger and more power-dense, three fundamental limitations emerged:

  1. Warpage: Organic materials (CTE 12-17 ppm/°C) expand and contract differently than silicon (CTE 3.1 ppm/°C). At package sizes above 70×70mm, this CTE mismatch creates warpage that prevents reliable flip-chip bonding.

  2. Interconnect density: Standard ABF processes achieve minimum line/space of 8/8 µm in production. AI chiplet architectures require 2/2 µm for die-to-die communication — a 4× density gap.

  3. Signal integrity: At 224G PAM4 signaling speeds emerging in next-generation AI networks, organic dielectric loss tangent (Df 0.003-0.008) becomes a bandwidth limiter. Glass offers Df <0.001 across relevant frequencies.

Intel's decision to bring glass substrates into high-volume manufacturing for Clearwater Forest wasn't incremental improvement — it was an acknowledgment that organic substrates cannot support the AI hardware roadmap beyond current generation.

Intel Clearwater Forest: First HVM Glass Substrate Product

Announced at CES 2026 and entering production in January 2026, Intel's Xeon 6+ "Clearwater Forest" processor represents the first commercial IC product fabricated on glass core substrates at high volume.

Technical Specifications

  • Die: Multiple chiplets on Intel 18A process
  • Package size: >80mm × 80mm (beyond organic warpage limit)
  • Substrate: Glass core with build-up redistribution layers
  • Interconnect: Through-Glass Vias (TGV) at 50µm pitch
  • Line/space: 2/2 µm (vs. 8/8 µm on latest organic ABF)
  • Layers: 10+ redistribution layers on glass core
  • CTE match: Glass core 3.2 ppm/°C vs. silicon 3.1 ppm/°C

Performance Benefits Demonstrated

Parameter Organic ABF (Sapphire Rapids) Glass Core (Clearwater Forest)
Maximum package size 70×70mm (warpage-limited) >100×100mm (no practical limit)
I/O density 500 bump/mm² 2,500+ bump/mm²
Power delivery resistance 1.0 mΩ typical 0.4 mΩ typical
Signal loss at 56 GHz -2.5 dB/cm -0.8 dB/cm
Warpage at reflow 100-300 µm <30 µm
Die-to-die bandwidth 16 Tbps (limited by pitch) 40+ Tbps

How Glass Substrates Are Made

Glass substrate manufacturing is fundamentally different from organic PCB fabrication:

Step 1: Glass Panel Preparation

  • Starting material: High-purity glass panels (Gen 3.5 display glass or specialty borosilicate)
  • Thickness: 300-500 µm (vs. 60-100 µm for ABF core)
  • CTE engineered via composition: adjustable from 3-8 ppm/°C
  • Surface preparation: Chemical mechanical polish (CMP) to <1nm roughness

Step 2: Through-Glass Via (TGV) Formation

  • Laser-induced deep etching: Ultrafast laser creates modification tracks
  • Chemical etch: HF-based wet etch selectively removes laser-modified glass
  • Result: Vias at 30-50 µm pitch (vs. 200-300 µm for organic PTH)
  • Aspect ratio: Up to 20:1 achievable

Step 3: Metallization

  • Seed layer: PVD sputtered TiW/Cu (vs. electroless Cu for organic)
  • Pattern plating: Semi-additive process (SAP) at 2/2 µm L/S
  • Via fill: Electroplated copper fills TGVs from bottom-up
  • Planarization: CMP produces atomically flat surface for next layer

Step 4: Build-Up Layers

  • Dielectric: Photo-definable polyimide or inorganic SiO₂ (vs. ABF resin)
  • Layer count: 6-12 redistribution layers built on each side of glass core
  • Registration: Lithographic alignment <±1 µm (vs. ±10 µm for organic lamination)

Step 5: Bumping and Singulation

  • UBM (Under-Bump Metallurgy): Sputtered multi-layer for flip-chip or micro-bump
  • Singulation: Laser or mechanical dicing of glass panel into individual substrates
  • Final test: Electrical probing of all interconnects

Why Glass Matters for AI Specifically

The connection between glass substrates and AI hardware is direct and structural:

Power Delivery

AI accelerators consume 500-1000W per package. Power must be delivered through the substrate with minimal resistance to avoid voltage droop during transient workloads. Glass substrates enable:

  • Thicker, wider redistribution layer traces (lower resistance)
  • More power/ground via columns (lower inductance)
  • Better planarity = more uniform bump contact = lower contact resistance

The cumulative effect: 40-60% reduction in package-level power delivery impedance, which translates directly to higher clock frequencies and wider voltage margins.

Chiplet Architecture Support

Modern AI processors (NVIDIA Blackwell, AMD MI400, Intel Clearwater Forest) use multi-chiplet designs where 4-12 compute dies communicate on a shared substrate. These die-to-die links require:

  • Extremely fine pitch (36-55µm bump pitch between chiplets)
  • Very flat substrate (warpage <30µm for reliable thermocompression bonding)
  • Low-loss interconnect (die-to-die links at 16-32 Gbps per lane)

Organic substrates cannot maintain flatness at the package sizes these multi-chiplet designs require. Glass solves this geometrically — matching silicon's thermal expansion eliminates the warpage that prevents scaling.

Bandwidth Density

AI training workloads are memory-bandwidth-limited. HBM4 memory stacks communicate with the processor through thousands of parallel lanes at 8-16 Gbps each. The substrate interconnect density directly limits how much memory bandwidth can reach the compute die:

  • Organic: ~500 connections/mm² → limited to 4-6 HBM stacks
  • Glass: ~2,500 connections/mm² → supports 8-12+ HBM stacks per package

More HBM stacks per package = more memory bandwidth = faster training. Glass substrates are literally a prerequisite for next-generation AI training hardware performance scaling.

The Competitive Landscape

Intel: First Mover Advantage

Intel's glass substrate program (announced 2023, HVM 2026) gives them a 2-3 year lead over competitors:

  • Proprietary TGV formation process
  • Integrated panel-level manufacturing in their Advanced Packaging facility
  • Clearwater Forest proves production viability — no longer a research project

Chinese Players Racing to Catch Up

As reported by ETNews and IC&PCB Union, Chinese companies are accelerating glass substrate investment:

Visionox: Display maker pivoting to glass substrates, leveraging existing glass handling and lithography expertise. RMB 5 billion investment program announced for 2026, targeting both display and semiconductor substrate applications.

AKM Meadville: Leading Chinese HDI substrate supplier has established a prototype glass substrate pilot line. Their existing dominance in organic IC substrates provides the customer relationships needed to transition designs to glass.

WG Tech / TGV Tech: Subsidiary focused exclusively on Through-Glass Via technology. Already delivering small-batch glass substrates for 1.6T optical modules — an early commercial application outside of compute.

Korean Push

South Korea is racing to close the packaging gap with Taiwan and China. Samsung's foundry division and Korean substrate makers (Samsung Electro-Mechanics, LG Innotek) are investing in glass substrate R&D to support Samsung's own AI accelerator packaging roadmap.

Impact on the PCB Industry

What Changes for PCB Fabricators

Glass substrates don't replace PCBs — they replace the IC substrate layer between the chip and the PCB. The implications:

  1. Motherboard design changes: Glass substrate packages have different ball patterns, power delivery requirements, and thermal interfaces. PCB motherboards must be redesigned for each glass-substrate processor generation.

  2. Signal integrity requirements increase: With the package-level interconnect no longer the bottleneck, the PCB motherboard traces become the limiting factor. Expect tighter impedance tolerances (±5% standard) and ultra-low-loss material adoption on PCB motherboards.

  3. Power delivery copper weight: Glass substrates enable higher processor power (>600W TDP). PCB power planes must scale proportionally — 4-8 oz copper, embedded bus bars.

  4. IC substrate market disruption: Traditional ABF substrate fabricators (Ibiden, Shinko, Unimicron) must either invest in glass capabilities or risk market share erosion to glass-native manufacturers.

What Stays the Same

  • PCBs still connect everything at the system level
  • Increasing PCB complexity supports glass substrate packages
  • High-layer-count, controlled-impedance PCB demand actually increases
  • Fabricators serving AI server markets see demand growth regardless of substrate technology choice

Timeline: Glass Substrate Adoption Roadmap

Timeframe Application Volume
2026 (now) Intel Xeon 6+ server CPUs Thousands/month
2027 NVIDIA AI accelerators (rumored) Tens of thousands/month
2028 AMD data center CPUs + AI GPUs Hundreds of thousands/month
2029 High-end networking ASICs (800G+) Millions/year
2030+ 5G/6G RF modules, automotive radar Mass market penetration

The transition from organic to glass substrates will take a decade to fully play out — but for AI hardware designers, it's happening now.

What Hardware Engineers Should Do Today

  1. Monitor package ball maps: Next-generation processors will have different substrate ball pitches — plan PCB footprint libraries accordingly
  2. Specify ultra-low-loss PCB materials: Megtron 6/7, Tachyon, or equivalent for signals interfacing with glass-substrate processors
  3. Design for higher power: Plan thermal solutions for >600W packages
  4. Engage your PCB fabricator early: Discuss advanced material availability and controlled impedance capabilities for AI server boards

Further Reading


Building PCB systems for next-generation AI processors? Talk to our engineering team about motherboard design for glass-substrate packages. We'll help you select materials, validate impedance, and optimize power delivery for the most demanding AI hardware platforms.


Originally published on AtlasPCB

Top comments (0)