An instrument for quantifying heterogeneous ice nucleation in multiwell 1 plates using infrared emissions to detect freezing 2

9 Low concentrations of ice nucleating particles (INPs) are thought to be important for the properties of mixed- 10 phase clouds, but their detection is challenging. While instruments to quantify INPs online can provide relatively 11 high time resolution data, they typically cannot quantify very low INP concentrations. Furthermore, typical online 12 instruments tend to report data at a single defined set of conditions. Hence, there is a need for instruments where 13 INP concentrations of less than 0.01 L -1 can be routinely and efficiently determined. The use of larger volumes of 14 suspension in drop assays increases the sensitivity of an experiment to rarer INPs or rarer active sites due to the 15 increase in aerosol or surface area of particulates per droplet . Here we describe and characterise the InfraRed- 16 Nucleation by Immersed Particles Instrument (IR-NIPI), a new immersion freezing assay that makes use of IR 17 emissions to determine the freezing temperature of individual 50μL droplets each contained in a well of a 96-well 18 plate. Using an IR camera allows the temperature of individual aliquots to be monitored. Freezing temperatures 19 are determined by detecting the sharp rise in well temperature associated with the release of heat caused by 20 freezing. In this paper we first present the calibration of the IR temperature measurement, which makes use of the 21 freezing period after initial nucleation when wells warm and their temperature is determined by the ice-liquid 22 equilibrium temperature, i.e. 0°C when the water activity is ~1. We then tested the temperature calibration using 23 ~100 µm chips of K-feldspar, by immersing these chips in 1 µL droplets on an established cold stage (µL-NIPI) 24 as well as in 50 µL droplets on IR-NIPI; the results were consistent with one another indicating no bias in the 25 reported freezing temperature. In addition we present measurements of the efficiency of the mineral dust NX-illite 26 and a sample of atmospheric aerosol collected on a filter in the city of Leeds. NX-illite results are consistent with 27 To further test the temperature readings from the IR-NIPI instrument a set of experiments was performed where 224 each droplet contained a single ~100 µm sized grain of K-feldspar, a mineral known to exhibit excellent ice- 225 nucleating properties (Atkinson et al., 2013; Harrison et al., 2016). This experiment was adapted from the 226


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Online instruments, such as CFDCs, do precisely this, but their detection limit is limited to ~10 -1 L -1 (Eidhammer 60 et al., 2010). This can be improved with aerosol concentrators, but is still above the INP concentrations models in the past e.g. (Vali, 1971;Bigg, 1953), and has been the strategy employed in the development of some recent

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Here we propose a new technique, the IR Nucleation by Immersed Particle Instrument (IR-NIPI), for the detection 72 of INPs using large volumes of sample in the immersion mode. This instrument is part of the NIPI suite of 73 instruments that includes the µL-NIPI and when used together these devices allow measurements to be taken over 74 a very wide range of INP concentrations. The use of an infrared camera allows temperature measurements to be 75 made for individual droplets which helps reduce errors from horizontal gradients across the array of droplets and 76 the effect of heat release on the temperature of neighbouring wells. The unique design, in combination with a

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Stirling engine chiller, is also compact making it ideal for field-based measurements and the use of multiwell 78 plates lends itself to future automation.  concentrations can be derived (Vali et al., 2015).

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If the surface area of nucleant per droplet is known then it is common to express the nucleating ability of a material 94 as the density of active sites per unit surface area of nucleator, ns(T) (Connolly et al., 2009;DeMott, 1995 (1)

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Where n(T) is the number of droplets frozen at a given temperature and N is the total number of droplets. A is the 100 surface area of nucleator within each droplet. Nucleation is a time-dependent stochastic process, but in 101 determining ns(T) the time dependence is neglected. This assumption is justified for many materials because the 102 diversity in activity of active sites leads to a much greater spread in freezing temperatures than the shift in freezing 103 temperatures associated with changes in cooling rate (Vali, 2008;Herbert et al., 2014).

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In brief an aqueous suspension is prepared and aliquots pipetted into the wells of a 96 multiwell plate which is The IR-NIPI has been designed around an Asymptote Ltd. VIA Freeze TM stirling cryocooler (Figure 1). The VIA

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Freeze uses a Stirling engine to provide a convenient means of cooling without refrigerants or circulating liquids

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and was primarily designed for use in cryopreservation applications. This chiller can achieve temperatures of -

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90°C, hence it has more than enough cooling capacity for our application, and has sufficiently low power 115 requirements that allow it to be run from an automotive 12 V inverter. It also features an onboard datalogger and

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IR camera used here is a Fluke Ti9 Thermal Imager with 160 x 120 pixels. The Stirling engine is then set to cool 130 down at 1.3°C min -1 which corresponds to 1°C min -1 ± 0.06°C in the wells due to a measured offset between the 131 plate and aliquot temperatures. This ramp rate was selected based on preliminary runs and justification for this 132 cooling rate being equivalent to 1°C min -1 can be seen in the well temperatures over time ( Figure 2b). Once the 133 system has initially cooled to 5°C the temperature is held for 5 min to allow time for the system to equilibrate.

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Following this the system continues to ramp down in temperature while recording IR heat maps of the multiwell 135 plate.

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In order to determine the temperature of individual wells, the analysis code locates a pixel centred in the middle

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The whole process from sample preparation to final analysis takes approximately 1 hour. In order to achieve where the temperature is recorded, for example when employing a cold stage housing an embedded thermocouple 157 whose reading is assumed to be representative for all droplets. We note that in our system there was a lateral 158 gradient across the entire multiwell plate in the IR-NIPI of up to 6°C (in extreme cases). This is likely due to there 159 not being an even thermal contact of the multiwell plate with the underlying cold plate. The typical gradient was 160 4°C, hence temperature measurements of the individual wells was necessary.

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Our calibration is based on the fact that when an aliquot of water in a multiwell plate freezes, the released latent 163 heat raises the temperature of the aliquot to the ice-water equilibrium temperature (0°C when the water activity 164 of the sample is ~1, as it is in these experiments). This is illustrated in Figure 2c which shows the phases of 165 crystallisation that the aliquots go through. Initially, the crystal growth is rapid with a rapid release of latent heat

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Once all of the water has frozen the temperature of the aliquot decreases rapidly back to that of the multiwell plate 175 within 20-40 s. The fact that the aliquots spend 10s of seconds at 0°C provides a very useful calibration point for 176 each individual well. In the following we describe a novel method for calibrating the IR temperature measurements 177 that takes advantage of this process and proceed to justify this approach.

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Using the analysis code, when an event is identified it uses the recorded temperature of the frame after the initial 179 event and calculates the difference of this value compared to 0°C to give an offset correction value. This offset 180 value is then subtracted from the temperature recordings for that specific well. The average correction value 181 calculated for the IR camera via this method is -1.9°C with a standard deviation 0.5°C.

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We performed a number of experiments to test the IR temperature measurement calibrated using the above

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We also tested the IR temperature measurement using T type thermocouples distributed in specific wells of a   preparing a known mass of a sample in a known mass of water) rather than diluting a bulk stock suspension.

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Further to this great care was taken when sampling from the bulk NX-illite sample as to make sure no bias was

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Where NU(T) is the number of unfrozen droplets at a given temperature, N is the total number of droplets, Vw is 305 the volume of wash water, Va is the volume of an aliquot and Vs is the volume of air sampled.

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The resulting INP concentrations from the combination of these two instruments spanned four orders of magnitude 307 and covered a temperature range of 20°C (see Figure 9). The data from both instruments was in good agreement The IR-NIPI technique is a novel approach to measuring freezing events in immersion mode nucleation studies.

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We demonstrate that IR thermometry is a sound method for determining the freezing temperature of 50 µL water   with thermocouples. It should be noted that one of the four surrounding IR well temperature readings was discarded from each experiment as 544 the thermocouple wire impeded the temperature measurement (b) Plot of the difference in temperature between the thermocouple readings for 545 two wells and six corresponding wells measured with the IR camera. The calculated error in temperature for the IR camera is shown in dashed 546 lines (±0.9°C). The range of freezing is highlighted in blue as this is where the thermal properties of ice and the initiation of heat release will 547 affect the temperature readings. Highlighted in red is the section of data before the well had equilibrated and so the IR camera was likely 548 reading a warmer surface temperature than the thermocouple.