Confidential · Not an offer of securities

VivoVac Pty Ltd · OPAL™ · Information memorandum · 10 September 2026

Slide deck

Section 01Notice to recipients

This document is a confidential positioning and information memorandum for the OPAL™ protonic computing programme. It is prepared by VivoVac Pty Ltd for directors, advisers and qualified counterparties. It is not a prospectus, product disclosure statement, or an offer, invitation or recommendation to subscribe for securities in any Group entity under the Corporations Act 2001 (Cth) or the US Securities Act of 1933.

  • Content is conceptual. Unless a signed contract says otherwise, nothing here is a specification, datasheet, performance guarantee or offer to sell a finished product.
  • Compute statements on the OPALBLACK ledger are conditional on experiments that have not been run. A negative species result (E1) means no computing claim is made.
  • Third-party figures (IEA, Rystad, LBNL, TrendForce) are public and dated. They are not the Group’s measurements of an OPAL device.
  • A disclaimer does not cure a statement that is misleading or that lacks reasonable grounds. Read Section 16 in full before relying on anything.

Section 02Executive summary

We are building a five-channel protonic computer that works with silicon. Silicon stays for speed. OPAL is intended for cheap, persistent, long-timescale learning — memory and compute in the same oxide — so that layer no longer has to buy a leading-edge GPU, a 120 kW rack, or a cooling tower.

OPAL™ (Oxide-Mediated Protonic Analogue Logic) is a proposed third computing substrate. After electrons and photons: protons. The working material, OPALBLACK, is nanoporous anodic aluminium oxide, grown in a bath rather than printed in a fab, and read electrically. The manufacturing route does not compete for a 2 nm wafer slot, a CoWoS package or an HBM allocation.

Nanoporous aluminium oxide substrate mounted beside a silicon processor
Plate I The third substrate: a protonic oxide module built from aluminium and water, sitting beside a silicon processor. Source image: opalblack.ai / VivoVac laboratory still.

Section 03The problem

Intelligence is being rationed by three meters: chips, watts and water. The AI era does not flatten this curve. It steepens it.

Screenshot of The Silicon Crisis page on protonicopal.com
Plate II Public narrative from protonicopal.com — The Silicon Crisis. Used as source material for this memorandum. Capture of https://protonicopal.com/silicon-crisis, 10 September 2026.

$30,000

Reported analyst estimate per 2 nm wafer, against roughly $18,000–22,000 for 3 nm. TSMC does not disclose list prices.

TrendForce / Silicon Analysts, 2025–26

2028

How far 2 nm capacity is reported booked. Access is allocated to lead customers, not purchased on an open market.

Supply commentary, public

945 TWh

Projected data-centre electricity in 2030, from 415 TWh in 2024 — slightly more than Japan consumes today.

IEA, Energy and AI, 2025 base case

222 bn L

Direct cooling water in 2025, heading for 644 billion litres by 2030 without efficiency gains.

Rystad Energy, 2026

About half of US electricity demand growth to 2030 comes from data centres. Unlike electric vehicles, data centres cluster, so the binding problem is grid integration in specific places. Direct cooling water is large. The larger figure almost nobody counts is indirect water at the power station — about 1.2 gallons per kilowatt-hour on a thermal grid (LBNL 2023). A watt not spent is paid twice where the grid is thermal.

Rows of liquid-cooled server racks
Plate III The hall this programme does not try to fill: high-density, liquid-cooled AI racks. Source image: opalblack.ai.

Section 04What we are building

A protonic oxide layer, made from aluminium and water, that sits beside a silicon processor. Silicon handles high-speed digital processing. The protonic layer is for low-cost, persistent, analogue, long-timescale learning — memory and compute in the same film, without a separate RAM bus.

Hero of protonicopal.com
Plate IV protonicopal.com — public technology site. Headline: we are building a five-channel protonic computer that works with silicon. Capture of https://protonicopal.com/, 10 September 2026.
Hero of opalblack.ai
Plate V opalblack.ai — compute ledger HG-OPAL-CBS-002. Same programme, stricter register: pair silicon with protons. Capture of https://opalblack.ai/, 10 September 2026.

Keep silicon for

  • Logic, arithmetic and control
  • The memory hierarchy the industry already has
  • Everything that needs a foundry’s precision
  • The processor a protonic layer still sits beside

Pair protons for

  • Holding analogue weights a short distance from the die
  • Work that should not join the wafer queue
  • A bath process on a seventy-year equipment base
  • One narrow job, done well, next to the chip

We do not dump silicon. We do not claim it is running out. We pair it with a proton-transport medium so that some of the work that currently competes for a 2 nm slot, a CoWoS slot and an HBM allocation can be done on an oxide grown in a bath.

Section 05OPALBLACK material

OPALBLACK is nanoporous anodic aluminium oxide, engineered as a proton-transport medium and read electrically.

Electron micrograph of hexagonal pores in anodic aluminium oxide
Plate VI Hexagonal pores and deep channels of anodic aluminium oxide. The material class is seventy years old. What is engineered is pore geometry, sealing state and zonal definition. Source image: opalblack.ai.

The material is seventy years old. Anodising grows a controlled porous oxide skin on aluminium by passing current through it in a bath. It is done at industrial scale, everywhere, today. Nothing about making the layer is exotic, and nothing about it requires a fab.

What is engineered is the pore structure. Pore geometry, sealing state and zonal definition across one part — so that different regions of the same oxide carry different function. That arrangement is what the Group has filed on. Filed, not granted, and not searched by an authority.

The carrier is a proton, not an electron. In porous anodic alumina, conduction runs by electron tunnelling when dry and protonically when humid. Settled physics, published in 1984 (Nahar, Khanna & Khokle). It is not the Group’s discovery and is never presented as one.

The same oxide, read at two depths. Read shallow, it reports what a surface has been exposed to — a different ledger, never sold to the same buyer. Read deep, it is a candidate for holding and modulating analogue state.

Nanoporous oxide sample and silicon processor under precision probes
Plate VII Laboratory still: oxide coupon and silicon processor under probes. This is a development image, not a shipped product. Source image: opalblack.ai.

Section 06Five channels

Public architecture on protonicopal.com describes five simultaneous physical channels in an Al / Al₂O₃ stack. This is the Group’s architectural filing position. Channel-level performance has not been demonstrated as a commercial computer.

Five-channel OPAL interface graphic
Plate VIII Five-channel Al / Al₂O₃ interface as presented on protonicopal.com/five-channels. Source graphic: protonicopal.com.
ChNameStated function
CH1Proton fluxPrimary information carrier. H⁺ transport via Grotthuss hopping. Analogue variable-weight logic.
CH2Impedance modulationMemory and compute in the same oxide layer — the stated attack on the von Neumann bus.
CH3Thermal gradientHeat from the aluminium–water chemistry; public site claims energy harvesting at node level.
CH4Acoustic emissionA parallel physical channel; timescales distinct from proton flux.
CH5Electrochemical potentialZonal electrochemical state across the same part.

Public site also cites patent-protected clock recovery (AU 2026902999, AU 2026903000) to synchronise channels that run on different timescales. Those numbers are provisional filings, not granted patents.

Proton transport through aluminium oxide lattice
Plate IX Public illustration of proton transport through the oxide lattice (Grotthuss hopping). Source graphic: protonicopal.com/what-is-opal.

Section 07Why pair, not replace

  1. Silicon logic is not the bottleneck. Moving weights is. Published protonic work targets analogue deep learning — programmable resistors as synaptic weights — not CPUs.
  2. The manufacturing route is the advantage. Anodising does not compete for wafer, CoWoS or HBM slots.
  3. Replacement has a certification clock measured in decades. Pairing inherits far less of silicon’s qualification burden.
  4. The energy argument only works at the margin, and the margin is enough. Data centres reach about 3% of global electricity by 2030. We use the concentration framing, never a planetary one.

The most advanced published protonic compute result (Onen et al., 2022, MIT / MIT-IBM Watson AI Lab) was engineered to be compatible with silicon, not to displace it: nanosecond protonic programmable resistors, 20× dynamic range, CMOS-native materials, for analogue deep learning. The pairing thesis is where the field already is.

Section 08The one-percent arithmetic

Not a revolution. One percent of the IEA 2030 data-centre load — the smallest number still worth the arithmetic. A device class that carries one narrow job only needs to be good at that job. The tariff below is a working assumption, not a sourced figure.

9.45 TWh

Electricity a year unspent if 1% of the 2030 IEA base case moves off the thermal path.

945 TWh × 1.00%

~43 bn L

Water left at the power station at 1.2 gal/kWh (US thermal average).

Derived from LBNL intensity

US$ 756 m

Illustrative annual electricity at US$0.08/kWh. Modelled — stated assumption.

Group working, not a forecast

6.7 ×

More water saved than taking the same 1% off direct cooling (~6.4 bn L).

Derived

Working: 945 TWh × 1.00% = 9.45 TWh. At 1.20 gal/kWh: 9.45 × 10⁹ kWh × 1.20 = 11.3 billion gallons ≈ 43 bn L. Direct cooling: 644 bn L × 1% ≈ 6.4 bn L. At 15% annual sector growth, 9.45 TWh is replaced in about twenty-four days. That is why efficiency has to come from a structurally different device, and why the manufacturing route matters as much as the physics. If E1 fails, the addressable share is zero and this claim collapses to the arithmetic alone.

Section 09Scientific lineage

Protonic computing is not a new idea, and that is the point. A proposal that needs new physics needs a miracle. This one does not. None of the rows below is the Group’s work.

1984

Protonic conduction in porous anodic alumina. Nahar, Khanna & Khokle, J. Phys. D 17, 2087. Anions from anodising act as proton donors.

1997–2004

Proton transport becomes measurable. H/D isotope effects; hydrogen isotope sensors on proton-conducting oxides.

2011

First solid-state protonic transistor (Rolandi, University of Washington). Proton mobility ~4.9×10⁻³ cm² V⁻¹ s⁻¹. IEEE Spectrum: first solid-state transistor to control protons.

2014

Reflectin protonic transistors ~7.3×10⁻³ cm² V⁻¹ s⁻¹, on/off ~1.6. Honest ceiling: slow and poorly switching at that geometry.

2022

Onen et al., MIT / MIT-IBM. Nanosecond protonic programmable resistors in Science. Room temperature, nanoscale channel, 20× dynamic range, silicon-compatible, for analogue deep learning.

Section 10Proven, claimed, not claimed

Three registers, kept separate on purpose. A claim without a stated falsifier is a slogan.

Already proven · Physics

Porous anodic alumina conducts protonically when humid, by a mechanism settled in 1984.

Falsifier: Not ours to falsify — the field’s result.

Already proven · Process

Anodising grows controlled porous oxide at industrial scale, on seventy-year-old equipment, with no fab.

Falsifier: Visit any anodising line.

Already proven · Demand

Data-centre electricity demand roughly doubles to ~945 TWh by 2030 on the IEA central scenario.

Falsifier: If the IEA revises, every TWh figure here falls in proportion.

What we claim · Hypothesis

The same oxide, read deep, is a candidate for holding and modulating analogue state.

Falsifier: E1: if species identification comes back negative, no computing claim is ever made — this row is deleted, not softened.

What we claim · Position

Pairing — not replacing — is the correct posture toward silicon.

Falsifier: If a protonic device ever beats silicon at logic, this row was still right when written.

What is not claimed

We do not claim silicon is running out; a granted patent; an authority search; or a working commercial device.

Falsifier: Filed, not granted. Three experiments stand between hypothesis and answer. They have not been run.

Section 11Intellectual property & corporate

IssuerVivoVac Pty Ltd (ACN 652 414 376)
RelatedHydroGien Pty Ltd
IP vestingOPAL™ and GALVANOXIDE™ trademarks. All IP exclusively vested in the HydroGien / VivoVac group, as stated on protonicopal.com.
StatusPatent pending: 70+ Australian provisional applications (public site). Filed, not granted, not searched by an authority.
Named filingsAU 2026902999, AU 2026903000 (clock recovery — public five-channel page).
LedgersCompute-and-storage (this IM, HG-OPAL-CBS-002) is never shown to a sensing counterparty.
Governing lawNew South Wales, Australia.

A published or provisional application is not a granted patent. A granted patent is not a product. Directors and employees publish only for the company; see Section 16 on personal liability.

Section 12Development programme

Three experiments stand between the hypothesis and an answer. They run on consumables and equipment the Group already owns. Under the standing rule, a negative E1 on species means no computing claim is ever made.

  1. E1 — Species. Identify the mobile carrier in the Group’s oxide under the intended read. If it is not protonic, the compute ledger stops.
  2. E2 — Local drive and read. Show that conduction can be driven and read locally, not only as a bulk humidity effect.
  3. E3 — Analogue state. Show that the same oxide, read deep, can hold and modulate analogue conductance on a useful timescale beside silicon.

No timeline in this memorandum is a commitment. No university, hyperscaler, miner or family office is a customer or partner unless named in a current authorised statement. None is named here.

Section 13Where OPAL sits

Honest comparison from the public site: no architecture wins at everything. OPAL is not faster silicon, not quantum, not neuromorphic. Worst stated job: running a general-purpose OS. Best stated job: analogue, multi-physics, persistent state beside a processor.

Compare systems page
Plate X protonicopal.com/compare — silicon, quantum, neuromorphic, photonic, OPAL. Capture of https://protonicopal.com/compare, 10 September 2026.
SiliconQuantumOPAL (stated)
CarrierElectronsQubitsProtons (H⁺)
Channels11–25 (architectural)
TemperatureAmbient / cooledCryogenicAmbient (claimed)
Fab$10–20B classSpecialisedAnodising bath
JobGeneral digitalNarrow quantumAnalogue state beside the die

Section 14Risk factors

  • E1–E3 may fail. If they do, there is no compute product.
  • Provisional patents may not grant, may be narrowed, or may be anticipated.
  • Public promotional copy (self-powered node, ~A$100 node, 10¹²⁰ identities) is not measured commercial performance.
  • Anodising scale-up, sealing, reliability and CMOS integration are unproven for this use.
  • Export controls (DSGL, EAR/ITAR) may restrict technical data.
  • Capital, talent and time may be insufficient relative to foundry incumbents.
  • Industry energy and water figures may be revised; the 1% arithmetic moves with them.
  • Confusion between sensing and compute ledgers would be a governance failure.

Section 15Sources

  • https://opalblack.ai/ — OPALBLACK compute ledger HG-OPAL-CBS-002 (primary disciplined source for this IM).
  • https://protonicopal.com/ — public technology site, five channels, crisis, compare, legal.
  • Nahar, Khanna & Khokle, J. Phys. D 17, 2087 (1984).
  • IEA, Energy and AI (2025) — 415 → 945 TWh data-centre path.
  • Rystad Energy (2026) — direct cooling water.
  • LBNL 2023 via IEEE Spectrum / EESI — indirect water ~1.2 gal/kWh.
  • Onen et al., Science / Nature Electronics line (2022) — nanosecond protonic resistors on silicon.
  • Rolandi group (2011); APL Materials reflectin transistors (2014).
  • TrendForce / Silicon Analysts — wafer price estimates. TSMC does not disclose list prices.