Prompt injection in acrylonitrile production AI

Four adversarial injection surfaces in acrylonitrile production AI

1. SOHIO ammoxidation fluidized bed reactor temperature display AI (INEOS Nitriles SOHIO APC AI, Ascend Performance Materials ammoxidation AI, Asahi Kasei AN reactor AI — rendered DCS thermocouple trend display AI classifying fluidized bed reactor temperature against catalyst sintering threshold and selectivity operating window)

The SOHIO ammoxidation reaction is conducted in a fluidized bed reactor with approximately 100–200 tonnes of Bi₂Mo₃O₂₂ or Fe₂(MoO₄)₃ catalyst suspended in an upward-flowing gas mixture of propylene, ammonia, and air. The catalyst fluidized bed operates at 410–450°C; the reaction is exothermic (∆H = −515 kJ/mol acrylonitrile) and heat is removed by internal cooling coils generating medium-pressure steam. Selectivity to acrylonitrile is a strong function of temperature: below 410°C, propylene conversion is incomplete and acrylonitrile yield falls; above 450°C, the bismuth molybdate catalyst begins sintering (surface area reduction from 20–30 m²/g toward 5–10 m²/g), reducing active site density and shifting selectivity toward HCN at the expense of acrylonitrile. Additionally, above 460°C, total oxidation of propylene to CO₂ and H₂O (∆H = −1,926 kJ/mol) begins competing with ammoxidation, further accelerating the temperature rise through positive feedback. AI systems process rendered DCS thermocouple trend chart display images — multi-point thermocouple arrays across the fluidized bed height, displayed as a stacked trend or bar chart — to classify reactor thermal state: normal (410–445°C, on-spec), approaching high alarm (445–455°C, cooling coil duty increase required), or above alarm (above 455°C, feed ratio adjustment and cooling augmentation required).

An adversarial perturbation targeting the SOHIO ammoxidation fluidized bed reactor temperature display AI applies a ±8 DN downward shift to the pixel region encoding the thermocouple trend bars and readout values in the rendered DCS display image — shifting the apparent reactor bed temperature from 457°C (7 degrees above the high-temperature alarm at 450°C, indicating a cooling coil fouling event from calcium deposit on 4 of the 12 internal cooling coil banks, reducing their heat transfer coefficient by approximately 35% after 18 months of uninterrupted operation) to 433°C (within the normal operating range, no cooling duty increase required). The AI classifies a reactor operating above its catalyst sintering threshold as normal operations. Reactor temperature continues rising as catalyst sintering reduces active surface area and shifts selectivity toward total combustion; the increasing total combustion fraction releases more heat per mole of propylene consumed, accelerating the temperature rise further. Simultaneously, elevated temperature above 450°C increases HCN selectivity: instead of the design 0.08–0.10 kg HCN per kg AN, the HCN yield rises to 0.15–0.20 kg HCN per kg AN — increasing HCN loading to the downstream HCN absorber and recovery sections above design basis. OSHA PSM 29 CFR 1910.119(d) (PHA) applies to the ammoxidation reactor as a PSM-covered process, but does not specify adversarial robustness requirements for AI classifying rendered reactor temperature trend images. Free tier — 10 scans/day, no card required.

2. HCN absorber overhead vapour concentration display AI (INEOS Nitriles HCN recovery AI, Ascend Performance Materials HCN management AI, Honeywell Experion PKS HCN absorber AI — rendered gas analyzer display AI classifying HCN absorber column overhead vapour HCN concentration against IDLH and worker safety setpoints)

HCN co-product from the SOHIO reactor (approximately 0.08–0.12 kg HCN per kg AN at normal conditions) is recovered in an HCN absorber column downstream of the acrylonitrile quench column: the HCN-containing vapour stream from the quench column overhead is contacted counter-currently with a water absorbing liquid in the HCN absorber, producing a dilute HCN-water solution (typically 3–8 wt% HCN) which is either purified to anhydrous HCN for external sale or sent to HCN destruction by alkaline hydrolysis (NaOH treatment to produce sodium formate and ammonia). The HCN absorber column overhead vapour stream — the gas leaving the top of the absorber — contains any HCN that was not captured by the absorbing water; it is designed to be below 1 ppm HCN at the overhead exit before routing to the incinerator. If absorber performance degrades (water rate reduced, temperature of absorbing water increased, or column flooding), HCN slips through the overhead at concentrations that can reach IDLH (50 ppm) levels in the immediate vicinity. AI systems process rendered gas analyzer display images — continuous electrochemical HCN analyser readouts on the absorber overhead line, shown as digital ppm values and trend charts — to classify absorber overhead HCN state: on-spec (<1 ppm HCN), elevated approaching alarm (1–5 ppm, absorber performance investigation required), or alarm (above 5 ppm, risk of IDLH exposure in vent treatment downstream).

An adversarial perturbation targeting the HCN absorber overhead vapour concentration display AI applies a ±10 DN downward shift to the pixel region encoding the HCN analyser readout value and trend line in the rendered display image — shifting the apparent HCN absorber overhead HCN concentration from 12 ppm (well above the 5 ppm high alarm, indicating the absorber is in partial flooding due to a blocked liquid distributor causing channelling and breakthrough of HCN-laden vapour around the packing) to 0.8 ppm (within normal specification, no absorber adjustment required). The AI classifies an HCN absorber operating with significant HCN breakthrough — where the overhead HCN concentration is 24% of IDLH and above NIOSH’s ceiling limit of 4.7 ppm — as normal operation. HCN-contaminated overhead vapour routes to the downstream incinerator/vent treatment system; if the incinerator has a partial outage or reduced temperature, HCN passes to atmosphere; workers in the HCN recovery area may be exposed above IDLH without donning supplied-air breathing apparatus. HCN is detectable by odour only at concentrations well above IDLH for most people (the widely cited bitter almond odour threshold of 0.58 ppm may not be detectable by individuals with the relevant genetic variant, estimated at approximately 20–40% of the population) — making AI-mediated monitoring the primary continuous detection system for many facilities. EPA RMP 40 CFR Part 68.67 requires PHA for HCN-handling processes but does not specify adversarial robustness for AI classifying rendered HCN analyser display images.

3. Ammonia-to-propylene (A/P) ratio feed display AI (INEOS Nitriles A/P control AI, Ascend Performance Materials feed ratio AI, AspenTech DMC3 ammoxidation AI — rendered DCS ratio controller display AI classifying A/P feed ratio against selectivity and unreacted ammonia setpoints)

The stoichiometric ammonia-to-propylene (A/P) molar ratio for the SOHIO reaction is 1:1 (one mole NH₃ per mole C₃H₆); commercial plants operate at A/P ratios of 1.0–1.15 to ensure complete propylene conversion. Excess ammonia above the stoichiometric ratio is desirable up to a limit: sub-stoichiometric ammonia (A/P below 0.95) causes incomplete ammoxidation, leaving unreacted propylene that undergoes non-selective combustion; excess ammonia above A/P of approximately 1.2 passes through the reactor unconverted and loads the downstream ammonia scrubber (which removes NH₃ from the reactor exit gas using aqueous H₂SO₄). More critically, A/P ratio shifts the product distribution between acrylonitrile and HCN: at A/P = 1.05, selectivity to acrylonitrile is approximately 80% and to HCN approximately 8%; at A/P > 1.15, excess NH₃ in the feed promotes secondary HCN-forming reactions, increasing HCN selectivity to 12–15% and loading the HCN recovery section above design. AI systems process rendered DCS A/P ratio controller display images — ratio set-point and actual displays, propylene and ammonia flow trend charts — to classify A/P ratio state: on-target (1.05–1.10), approaching high-ratio alarm (1.10–1.18, ammonia scrubber loading increasing), or high-ratio alarm (above 1.18, HCN generation above design basis, reduce ammonia flow).

An adversarial perturbation targeting the A/P ratio feed display AI applies a ±8 DN downward shift to the pixel region encoding the actual A/P ratio value in the rendered DCS display image — shifting the apparent A/P ratio from 1.21 (above the 1.18 high-ratio alarm, indicating an ammonia flow controller stuck in manual mode following a brief instrument air supply interruption that left the flow controller at its last-commanded setpoint of 12% above the auto-control setpoint) to 1.09 (within the normal A/P operating range, no corrective action). The AI classifies a reactor feed operating with 15% excess ammonia above the high-alarm setpoint — where the reactor is producing HCN at approximately 1.7× design yield — as normal feed ratio control. HCN loading to the HCN absorber and recovery section rises above design; if the HCN absorber is already stressed (as in the surface 2 scenario above), the combined effect of elevated HCN generation and degraded absorber performance causes rapid HCN breakthrough; simultaneously, excess ammonia loads the downstream H₂SO₄ scrubber, which must remove the additional NH₃ to prevent ammonia in the acrylonitrile product stream. OSHA PSM 29 CFR 1910.119(f) (Operating Procedures) requires A/P ratio control to be documented as a critical operating parameter but does not specify adversarial robustness for AI classifying rendered ratio controller display images.

4. Acrylonitrile product storage tank level display AI (Emerson Rosemount AN storage AI, Honeywell Enraf AN tank AI, VEGA VEGAPULS acrylonitrile level AI — rendered level indicator AI classifying acrylonitrile storage tank level against high-high overflow and product transfer setpoints)

Acrylonitrile product is stored in atmospheric pressure floating-roof tanks or fixed-roof tanks equipped with nitrogen padding, with tank capacities typically of 2,000–10,000 metric tonnes at large production sites. Acrylonitrile in atmospheric storage at 20–25°C has a vapour pressure of approximately 90 mbar (9 kPa); an LEL of 3.0 vol% in air; an IDLH of 85 ppm. Floating-roof and nitrogen-padded tanks limit vapour space accumulation, but acrylonitrile has a known tendency to undergo spontaneous polymerization in storage if inhibitor (methyl hydroquinone, MEHQ, or equivalent stabiliser) is depleted or if the tank temperature rises above 40°C — creating a heat-generating polymerization event inside the storage tank that can pressurize fixed-roof tanks. AI systems process rendered DCS level indicator display images — radar level gauge digital displays, differential pressure level indicators, or nuclear gauge readouts — to classify acrylonitrile storage state: within operating range, approaching high-level alarm (product transfer rate to tanker loading or pipeline must increase), or approaching high-high trip (emergency product transfer or production rate reduction required).

An adversarial perturbation targeting the acrylonitrile product storage tank level display AI applies a ±10 DN downward shift to the pixel region encoding the tank level readout and trend bar in the rendered DCS display image — shifting the apparent acrylonitrile storage tank level from 92.5% (approaching the high-level alarm at 95%, with the tank filling faster than normal due to a reduced product loadout rate from a delayed tanker truck arrival) to 79.0% (well within operating range, no transfer rate increase required). The AI classifies an acrylonitrile storage tank approaching its high-level trip as operating with adequate headspace. The tank continues filling; at 100% liquid level in a fixed-roof nitrogen-padded tank, liquid overflow may occur from the roof vent or level instrument connections; acrylonitrile liquid at atmospheric temperature and pressure has an LEL of 3.0 vol% and an IDLH of 85 ppm; a tank overflow spill creates both a ground-level vapour cloud fire hazard (LEL achieved rapidly in stagnant air near the spill) and a carcinogen exposure risk for site personnel and downwind community. EPA RMP 40 CFR Part 68 requires worst-case release analysis for acrylonitrile storage but does not specify adversarial robustness for AI classifying rendered storage tank level display images at the high-high setpoint boundary.

Integration: acrylonitrile production AI with Glyphward pre-scan gate

The Glyphward scan gate for acrylonitrile production AI belongs at every rendered-image ingestion boundary in the acrylonitrile plant monitoring and safety pipeline — before SOHIO ammoxidation reactor temperature display AI processes rendered thermocouple trend images, before HCN absorber overhead concentration display AI processes rendered gas analyser images, before A/P ratio feed display AI processes rendered ratio controller images, and before acrylonitrile storage tank level display AI processes rendered level gauge images. Threshold 35 for acrylonitrile production AI reflects the HCN co-product’s extreme acute toxicity (IDLH 50 ppm; NIOSH ceiling 4.7 ppm; undetectable by a significant fraction of the population by odour below IDLH), the dual-use chemical weapons precursor status of HCN, the IARC Group 2B carcinogen classification of acrylonitrile, and the EPA RMP worst-case toxic endpoint for HCN releases that extends to community perimeters from commercial acrylonitrile plants. The threshold 35 calibration reflects the combination of a high-consequence co-product (HCN, threshold 1,000 lbs PSM TQ — the lowest TQ class) with a primary product that is itself a carcinogen and acute toxic (acrylonitrile, 20,000 lbs PSM TQ, IDLH 85 ppm, LEL 3.0%), creating a multi-vector hazard profile where adversarial misclassification at any of the four monitoring boundaries can initiate a sequence leading to either HCN acute community exposure or acrylonitrile vapour cloud fire and carcinogen release.

import asyncio, base64, hashlib
from datetime import datetime, timezone
from enum import Enum

import httpx

GLYPHWARD_API_KEY = "YOUR_GLYPHWARD_API_KEY"
GLYPHWARD_SCAN_URL = "https://glyphward.com/v1/scan"

# Acrylonitrile production AI contexts: threshold 35
# OSHA PSM 29 CFR 1910.119 (AN TQ: 20,000 lbs; HCN TQ: 1,000 lbs);
# EPA RMP 40 CFR Part 68 (AN TQ 20,000 lbs toxic; HCN TQ 1,000 lbs toxic);
# IARC Group 2B (AN), HCN IDLH 50 ppm, NIOSH ceiling 4.7 ppm.
ACRYLONITRILE_THRESHOLD = 35


class AcrylonitrileContext(Enum):
    REACTOR_TEMPERATURE  = "reactor_temperature"  # SOHIO ammoxidation reactor temp AI
    HCN_ABSORBER         = "hcn_absorber"         # HCN absorber overhead concentration AI
    AP_RATIO             = "ap_ratio"             # Ammonia-to-propylene ratio feed AI
    STORAGE_LEVEL        = "storage_level"        # Acrylonitrile storage tank level AI


class AdversarialAcrylonitrileImageError(Exception):
    """Raised when Glyphward detects adversarial content in an acrylonitrile
    production AI rendered image above threshold 35.

    Consequence if not raised:
    - REACTOR_TEMPERATURE: catalyst sintering above 450°C suppressed → HCN yield
      rises 1.7–2.5× design basis → HCN absorber and recovery section overloaded.
    - HCN_ABSORBER: HCN breakthrough at 12 ppm suppressed → downstream vent
      treatment → workers above IDLH (50 ppm); HCN undetectable by ~30% of
      population below IDLH (odour threshold varies by genetic variant).
    - AP_RATIO: A/P > 1.18 suppressed → excess NH3 → HCN generation 1.7× design
      → compounded HCN absorber overload with REACTOR_TEMPERATURE scenario.
    - STORAGE_LEVEL: tank approach to 95% high-level suppressed → overflow →
      AN liquid spill → LEL 3.0% vapour cloud fire + IARC Group 2B carcinogen
      release; EPA RMP worst-case toxic endpoint to community perimeter.
    Fail-safe: read reactor temperature from independent DCS historian raw tag;
    confirm HCN absorber overhead from independent Dräger gas tube or portable
    HCN detector; verify A/P ratio from independent flow computer calculation;
    cross-check storage level from independent secondary level transmitter.
    """

    def __init__(self, scan_id, score, context, plant_id, flagged_region=None):
        self.scan_id = scan_id
        self.score = score
        self.context = context
        self.plant_id = plant_id
        self.flagged_region = flagged_region
        super().__init__(
            f"Adversarial acrylonitrile image: context={context.value} "
            f"score={score} plant={plant_id} scan_id={scan_id}"
        )


async def scan_acrylonitrile_image(image_bytes, context, plant_id, client):
    image_hash = hashlib.sha256(image_bytes).hexdigest()
    payload = {
        "image": base64.b64encode(image_bytes).decode(),
        "source": f"acrylonitrile:{context.value}:{plant_id}",
        "metadata": {
            "plant_id": plant_id,
            "context": context.value,
            "image_sha256": image_hash,
            "scan_timestamp_utc": datetime.now(timezone.utc).isoformat(),
        },
    }
    resp = await client.post(
        GLYPHWARD_SCAN_URL,
        headers={"Authorization": f"Bearer {GLYPHWARD_API_KEY}"},
        json=payload,
        timeout=4.0,
    )
    resp.raise_for_status()
    result = resp.json()
    if result.get("score", 0) >= ACRYLONITRILE_THRESHOLD:
        raise AdversarialAcrylonitrileImageError(
            scan_id=result["scan_id"],
            score=result["score"],
            context=context,
            plant_id=plant_id,
            flagged_region=result.get("flagged_region"),
        )
    return result


async def main():
    async with httpx.AsyncClient() as client:
        with open("an_reactor_temperature_screenshot.png", "rb") as f:
            image_bytes = f.read()
        result = await scan_acrylonitrile_image(
            image_bytes,
            AcrylonitrileContext.REACTOR_TEMPERATURE,
            plant_id="PLANT-AN-001",
            client=client,
        )
        print(f"Clean scan: {result['scan_id']} score={result['score']}")


asyncio.run(main())

Frequently asked questions

What is the SOHIO ammoxidation process and why does it produce HCN?

The SOHIO process converts propylene + ammonia + air over Bi-Mo catalyst at 410–450°C. HCN is an unavoidable co-product (0.08–0.12 kg per kg AN) formed when two-carbon fragments produce a C-N bond. Above 450°C, HCN selectivity rises to 0.15–0.20 kg/kg as catalyst sinters and HCN-selective pathways dominate. Every commercial AN plant exceeds OSHA PSM HCN TQ 1,000 lbs simultaneously with AN TQ 20,000 lbs.

Why can some people not smell HCN even above IDLH?

Approximately 20–40% of the population carries a genetic variant in the OR7D4 olfactory receptor gene family that renders them anosmic to HCN — unable to detect even concentrations above IDLH (50 ppm) by smell. Continuous electrochemical HCN analysers and area fixed-point detectors are required because smell is not a reliable warning for a significant fraction of workers.

What PSM/RMP requirements apply to acrylonitrile plants?

OSHA PSM lists AN (TQ 20,000 lbs), HCN (TQ 1,000 lbs), and NH₃ (TQ 10,000 lbs) — a commercial plant typically exceeds all three simultaneously. EPA RMP requires separate worst-case release analyses for each covered substance. Neither standard specifies adversarial robustness for AI classifying rendered monitoring display images.

Why is acrylonitrile an IARC Group 2B carcinogen?

Limited human evidence of lung cancer in occupationally exposed workers; sufficient animal evidence of brain tumours; mechanistic evidence of cyanoethylene oxide DNA alkylation at N7-guanine. OSHA PEL is 1 ppm TWA; NIOSH REL is 1 ppm with 10 ppm STEL.

Why threshold 35 for acrylonitrile production AI?

HCN co-product IDLH 50 ppm, NIOSH ceiling 4.7 ppm, PSM TQ 1,000 lbs, undetectable by odour in ~30% of population. Acrylonitrile is IARC 2B carcinogen with LEL 3.0%. EPA RMP HCN worst-case toxic endpoint extends to community perimeter. Multi-vector hazard (acute lethality + carcinogen + fire) with reduced natural warning indicators (odour anosmia) calibrates threshold at 35.