It goes without saying that in any manufacturing environment no one sets out to design an unsafe process. However, it is not enough to ensure a process will be safe under normal operating conditions. Deviations from normal operating conditions must be considered at every step.
Integration of risk analysis into process design at an early development stage helps provide the opportunity to design an inherently safe process, taking into account the question, “What if…?” Used correctly, this early-stage risk analysis becomes an iterative procedure that accompanies process development.
The rules for improving process safety through appropriate design may almost appear trivial: everything from “know your chemistry” and avoid unnecessary accumulation of exothermally reacting compounds to maximize heat transfer per reactor volume unit and avoid external runaway triggers. However, the nature of batch and semibatch reactions— frequently relied upon in the areas of pharmaceutical and chemical manufacturing—establishes additional variables that should be taken into account when designing processes to be intrinsically safe.
Batch mode is acceptable (and cost-effective) for nonhazardous reactions. However, if there is more than a moderate adiabatic temperature increase and exothermic decomposition at maximum reaction temperatures, it is preferable to run a semibatch process where addition of one or more reagents is controlled. Classic defensive safety measures (e.g., emergency/evaporative cooling, quenching, and pressure relief) should never be ignored.
What does it mean to adequately determine thermal risk and prevent unsafe conditions in the case of either batch or semibatch processing where steady state is never reached? This article focuses on obtaining the data needed to develop processes that will help ensure that classic defensive measures are never required, while also improving processes with regard to cost-effectiveness and time-to-reaction.
Ascertaining thermal risk
Chemical process risk and hazard potential are affected by a number of parameters. These include heat transfer, mixing effects, kinetics, heat generation rate, overall heat balance, heat-removal capacity of the reactor, accumulation of reagents/energy, and physical properties such as reagent stability and reaction mass.
Figure 1 – Heat balance diagram. A typical semibatch is run at the unstable operating point.
Thermal runaway scenarios in a chemical plant are ultimately tied to a condition in which an ongoing reaction’s heat generation has exceeded the heat dissipation capacity of the process equipment—for example, reactant (heat) accumulation during a simultaneous cooling system failure when energy potential is released adiabatically. The predominant hazard in the manufacturing process, however, is the loss of control of a desired reaction due to reactant accumulation, high sensitivity to impurities, initiation problems (long induction time), wrong kinetic assumptions, or other variables.
The energy balance is dominated by a low heat dissipation capacity and subsequent energy accumulation. In a case such as this, even very weak undesired reactions can run away. Undesired operational conditions may lead to insufficient mixing, wrong feed rates/temperatures, etc., that contribute to runaway scenarios, or vice versa. As noted, either scenario can be bad for production and potentially unsafe.
Figure 2 – Runaway graph from iC Safety software (METTLER TOLEDO, Schwerzenbach, Switzerland).
For these reasons, it is critical to gain an understanding of MTSR, the maximum temperature of the synthesis reaction, based on the amount of accumulated reagent, or MAT, the maximum achievable temperature in the worst-case scenario assuming 100% reagent accumulation. Starting from MTSR, further events—particularly decomposition reactions—can be triggered that may ultimately lead to an explosion. These events need to be defined and explored if intrinsic safety is to be reached (see Figure 1).
Understanding runaway potential
To prevent unsafe operating conditions based on runaway scenarios, data are required to predict runaway scenarios. Because it is not feasible to model the reaction completely in practice, the analysis of thermodynamics and kinetics of the reacting system can be reduced to a number of basic properties and relatively easy-to-obtain data. Based on these data, risk can be presented as a runaway graph (see Figure 2).
Figure 3 – Diagram of the high-performance Thermostat RC1e, which enables fast, precise heating and cooling.
Data used to create the graph are determined by answering the following questions:
- What is the heat evolution rate of the process as a function of time [qR(t)] that the equipment must handle?
- What temperature will be reached with the desired process running away, assuming an adiabatic condition for cooling failure (MTSR or MAT)?
- When is MTSR maximal (the most critical instance for cooling failure)?
- In what time ΔtDEC(T0) will a runaway decomposition reaction develop, given the initial temperature T0 (with T0 typically being equal to MTSR)?
- In what time, at ΔtR(Tp), will MTSR be reached?
- What is the order of magnitude of an adiabatic temperature increase (ΔTad, Dec) caused by the runaway of the secondary reactions (decomposition reaction) and what are the consequences?
To answer these questions adequately, data related to reaction mass energy potential, as well as data related to reactant accumulation and heat evolution, need to be determined. A reaction calorimeter, such as the industry-standard RC1e® from METTLER TOLEDO, is required. A reaction calorimeter such as this allows chemical reactions to be run under conditions that represent a specific process at scale (see Figure 3).
Figure 4 – Criticality graph from iC Safety software.
In these reactions, measurement of heat flow serves as a direct reaction-rate indicator, providing required basis data [qR(t), ΔtR(Tp)]. Accumulation of reactants is calculated from the addition and conversion as a function of time. Energy accumulation is obtained by integrating the heat flow curve from which ΔTad, MTSR, and MAT can be derived.
The energy potential of the reaction mass can be determined by microthermal analysis (e.g., differential scanning calorimetry, or DSC), where mixtures of starting materials and intermediate process phase samples are investigated. A comparative results evaluation indicates which signals correspond to desired and undesired reactions.
Secondary reaction heat evolution dynamics can be obtained from isothermally or dynamically measured heat evolution rates, typically using DSC techniques or adiabatic calorimetry. (Adiabatic techniques require careful experiment selection and are less adequate for reactions with complex kinetics.)
Physical properties such as boiling points, vapor heat/pressure, and data related to process equipment are then explored to adequately assess thermal runaway consequences.
Evaluating process risk and criticality
Process risk depends on the severity and probability of occurrence. Process criticality, therefore, can be evaluated using relative levels of different temperatures attained if the desired reaction and decomposition reactions proceed under adiabatic conditions. Probability can be estimated using a time scale: If there is enough time left to take emergency measures before the runaway becomes too fast after cooling failure, runaway probability will remain low.
The criticality of a reaction presenting thermal potential overall can be estimated by looking at process temperature (Tp), MTSR, TD24 (time at which time-to-maximum rate, or TMR, is 24 hr), and MTT (maximum technical temperature, e.g., boiling point, maximum allowable pressure material, etc.). A graphical representation of these temperatures (see Figure 4) allows process classification from noncritical to highly critical.
Depending on the allocated criticality class, a process might be safe and not require any modifications at all. Higher criticality processes may require considerable modification or a rework of the entire process.
Arriving at intrinsic safety
Data obtained while running the smaller-scale experiments to answer the questions that determine runaway potential (above) can then be used to guide necessary redesign, including changing reaction media, reordering additions, or making systematic variations of concentration, temperature, or feed profiles. Any changes undertaken will give rise to a new process with distinctly different hazard potential that will also need to be addressed with their own sets of experiments. In each case, arriving at a safe and optimized process requires the utmost attention to all sources of available information describing the process from raw materials to intermediates to final products.
Figure 5 – RC1e Reaction Calorimeter and iC Safety software.
While modeling runaway scenarios, using tools such as the RC1e reaction calorimeter along with appropriate software (see Figure 5) involves additional experiment steps. These actions help provide information to create not just an intrinsically safe process, but one that is ideal in terms of raw materials use, time-to-reaction, and overall manufacturing costs.
Urs Groth is Product Manager, Reaction Calorimetry, and Market Manager, Reaction Engineering, METTLER-TOLEDO AG, Business Unit AutoChem, Sonnenbergstrasse 74 8603 Schwerzenbach, Switzerland; tel.: +41-44-806 7379; e-mail: firstname.lastname@example.org ; www.mt.com