This study was financially supported by the MH21 Research Consortium for Methane Hydrate Resources in Japan and the National Methane Hydrate Exploitation Program by the Ministry of Economy, Trade, and Industry. The authors would like to thank T. Maekawa and S. Goto for their assistance with the experiments.
Reprinted figures with permission from (Muraoka, M., Susuki, N., Yamaguchi, H., Tsuji, T., Yamamoto, Y., Energy Fuels, 29(3), 2015, 1345-1351., 2015, DOI: 10.1021/ef502350n). Copyright (2015) American Chemical Society.

Note: Please consult all relevant material safety data sheets as this study uses high-pressure flammable methane gas and a large high-pressure vessel. Wear a helmet, safety glasses, and safety boots. If the temperature control system stops, the pressure in the vessel increases with MH dissociation. To prevent accidents, the use of a safety valve system is strongly recommended to automatically release the methane gas to the atmosphere. The safety valve system can work without electrical power supply.
1. Preparation of the Sand-water-methane Gas Samples9
<ol>
	<li>Place the high-pressure vessel on the vibrating table.</li>
	<li>Pour 1.5 L of pure water in a water bottle and 4,000 g silica sand in a sand bottle. Accurately weigh the masses of sand and water in the sand and water bottles, respectively.</li>
	<li>Pour 1 L of pure water in the high-pressure vessel with an inner volume of 2,110 cm3 from a water bottle until the water fills half the inner vessel.</li>
	<li>Turn on the vibrating table to vibrate the entire vessel. Set the vibration rate and the power supply to 50 Hz and 220 W, respectively. Apply the vibration until the completion of step 1.5. Remove the residual air in the drain line and sintered metallic filter at the bottom of the vessel by vibrating the vessel.</li>
	<li>Pour 3,300 g silica sand from a sand bottle into the vessel at a constant rate of approximately 1 g sec&#8722;1 using a funnel held near the water surface while the entire vessel is vibrated to ensure uniform packing.</li>
	<li>Stop the vibration when the water reaches the rim of the vessel.</li>
	<li>Place a ring as a temporary wall on the rim of the vessel to prevent water from spilling.</li>
	<li>Vibrate the vessel again at 50 Hz and 220 W.</li>
	<li>When the sand reaches the rim of the vessel (height 140 mm), turn off the vibration.</li>
	<li>Remove the temporary wall and excess pore water using the drain line. Pour the excess pore water back into the water bottle.</li>
	<li>Pack the sand by vibrating the vessel once or twice at 50 Hz and 300 W for 1 sec and add more sand if necessary.</li>
	<li>Weigh the masses of sand and water in the sand and water bottles. Calculate the sand and water masses in the vessel from the mass differences in the sand and water bottles. In this experiment, the masses of sand and water in the vessel were 3,385 g and 823.6 g, respectively. The mass of water in the vessel is denoted as wtotal.</li>
	<li>Cover the high-pressure vessel with a stainless steel lid and tighten the bolts of diagonally opposite pairs in sequence.</li>
	<li>Move the high-pressure vessel from the vibrating table to the table intended for the experiment.</li>
	<li>Cover the high-pressure vessel with the heat insulator for controlling the temperature.</li>
	<li>Connect the high-pressure pipelines and the cooling water flow lines to the high-pressure vessel.</li>
	<li>Open the valves of the input and output gas pipelines. Ventilate 10 L methane at a rate of 800 ml min&#8722;1 until no excess water discharges into the trap under atmospheric pressure. The sand discharge is prevented by a sintered metallic filter fixed on the bottom of the vessel. The residual water remains on the sand surface because the hydrophilic silica sand adsorbs the water molecules.</li>
	<li>Weigh the mass of water in the trap, wtrap, to determine the gas volume in the vessel. Determine the mass of residual water, wres, in the vessel using the equation wres = wtotal &#8722; wtrap. In this case, wres and wtrap was 360.6 g and 463.0 g, respectively.</li>
	<li>Determine the sample porosity using the formula &#1136; = 1 - Vsand / Vcell, where Vsand is the volume of the sand determined by the ratio of sand mass to sand density (i.e., &#961;s = 2,630 kg m&#8722;3), and Vcell is the inner volume of the vessel. The porosity&#160;&#1136; of the sample was 0.39.</li>
	<li>Close the valve of the output gas line. Inject methane to increase the pore pressure of methane in the vessel to approximately 12.1 MPa at room temperature (i.e., 31.6 &#176;C).</li>
	<li>Close the valve of the input gas line.</li>
	<li>Start recording the pressure and temperature in the vessel during the experiment using the data logger. The data sampling interval is 5 sec. The total experimental time is approximately 3,000 min.</li>
</ol>
2. MH Synthesis and Thermal Properties&#39; Measurement of the Supercooled Sample9
<ol>
	<li>Turn on the chiller for cooling the vessel from room temperature to 2.0 &#176;C by circulating the coolant. Let the coolant circulate from the chiller to the bottom of the vessel, from there to the lid of the vessel, and finally back to the chiller. The temperature change rate in the vessel was approximately 0.001 &#176;C sec&#8722;1.</li>
	<li>Set the measurement parameters using the TPS analyzer software. Set the sensor type to sensor design #7577. Set the output power W0 to 30 mW and the measuring time to 5 sec. Note that the appropriate parameters should be changed if the sensor type or sample conditions change. Set the parameters to increase the temperature from 1 &#176;C to 1.5 &#176;C.</li>
	<li>Calculate the degree of supercooling, &#916;Tsup, with the following equation: 
	&#916;Tsup = Teq(P) &#8722; T. (3) 
	Teq(P) is the equilibrium temperature of MH as a function of pressure P. Teq(P) is calculated using the CSMGem software1.&#160; P and T are the pressure and temperature in the vessel measured by using pressure and temperature gauges, respectively.</li>
	<li>Simultaneously measure the thermal conductivity, thermal diffusivity, and volumetric specific heat using the TPS analyzer after &#916;Tsup is greater than 2 &#176;C.</li>
	<li>Switch the TPS probe connected to the thermal properties analyzer after each measurement. Switch the cables between the TPS probes and the analyzer manually during the experiment9. The connection diagram is shown in Figure S2 in reference9. The switching sequence for each sensor is no. 6 &#8594; 2 &#8594; 7 &#8594; 5 &#8594; 1 &#8594; 9 &#8594; 4 &#8594; 3 &#8594; 8 &#8594; 6&#8230;. The sequence is based on the distance between the sensors, which is set as far as possible to prevent the residual heat from affecting the measurements. Collect data every 3-5 min.</li>
	<li>Repeat the measurements until &#916;Tsup reaches 2 &#176;C again. In this experiment, &#916;Tsup initially increases with time. After &#916;Tsup reaches the maximum value, &#916;Tsup gradually decreases to 0 &#176;C because the pressure decreases with the formation of MH. Check if &#916;Tsup is greater than 2 &#176;C prior to the TPS measurements using equation 3.</li>
	<li>Ensure that the temperature profile is not affected by MH melting. If MH melts during the measurements, the temperature will not increase because melting of MH is an endothermic reaction. Check the temperature profile during the measurements, and is discussed in the results section.</li>
	<li>Perform the thermal properties&#39; analysis for all temperature profile data using the TPS technique.</li>
</ol>
3. Calculation of the Saturation Change of the Sample9,11
Note: The degree of saturation for MH, water, and gas in the sample as a function of time t is calculated using the equation of state of the gas. The calculation details and equations used are previously described11.
<ol>
	<li>Calculate the methane gas volume Vgas,t at time t 
	<img alt="Equation 4" src="/files/ftp_upload/53956/53956eq4.jpg" /> 
	where Q is the initial volume of gas in the vessel, VMH,t &#8722; 1 is the volume of MH at time t &#8722; 1, and RVhw is the volume ratio of water and MH. 
	<img alt="Equation 5" src="/files/ftp_upload/53956/53956eq5.jpg" /> 
	In Equation 5, n is the hydration number of MH (~6), &#961;MH and &#961;water correspond to the density of MH and water, respectively, and wMH and wwater denote the molecular mass of MH and water, respectively.</li>
	<li>Calculate the amount &#916;Mt (mol) of MH formed from t &#8722; 1 to t 
	<img alt="Equation 6" src="/files/ftp_upload/53956/53956eq6.jpg" /> 
	where R is the gas constant, P is the pressure of the methane gas, and Zt (Tgas,t, Pgas,t) is the compression coefficient of methane at time t. We9 and Sakamoto et al.11 have used the Benedict&#8211;Webb&#8211;Rubin (BWR) equation, as modified by Lee and Kesler, for calculating Zt12,13. For this calculation, the formulas (3&#8211;7.1)&#8211;(3&#8211;7.4) of the BWR equation13 and the Lee&#8211;Kesler constants are used in Tables 3&#8211;7 of reference13.</li>
	<li>Calculate the volume change &#916;VMH,t of MH from t &#8722; 1 to t 
	<img alt="Equation 7" src="/files/ftp_upload/53956/53956eq7.jpg" /> 
	where Ps is the reference pressure of 101325 Pa, Ts is the reference temperature of 273.15 K, Zs is the compression coefficient at Ps and Ts (Zs ~1), and VCH4 is the ratio of the methane gas volume in the unit volume of MH [Nm3 m&#8722;3]. Use a VCH4 value of 165.99 [Nm3 m&#8722;3].</li>
	<li>Calculate the volume VMH,t of MH at time t 
	<img alt="Equation 8" src="/files/ftp_upload/53956/53956eq8.jpg" /></li>
	<li>Calculate the volume of water Vwater,t in the pressure vessel at time t 
	<img alt="Equation 9" src="/files/ftp_upload/53956/53956eq9.jpg" /> 
	where Vwater,1 is the initial volume of water.</li>
	<li>Repeat the calculations using Equations. 4&#8211;9 at time t = 2, 3, &#8230; to determine the change in the saturation of water, methane, and MH11. The initial condition is t = 1, i.e., Vgas,1 = Q. The P and T at time t are taken from the data logs9. The calculation results are shown in the following section.</li>
</ol>

<ol>
	<li>Sloan, E. D., Koh, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Clathrate Hydrates of Natural Gases, 3rd ed. , (2007).</li><li>Hatzikiriakos, S. G., Englezos, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+relationship+between+global+warming+and+methane+gas+hydrates+in+the+earth.">The relationship between global warming and methane gas hydrates in the earth.</a> Chem. Eng. Sci. 48 (23), 3963-3969 (1993).</li><li>Yamamoto, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overview+and+introduction:+pressure+core-sampling+and+analyses+in+the+2012-2013+MH21+offshore+test+of+gas+production+from+methane+hydrates+in+the+eastern+Nankai+Trough.">Overview and introduction: pressure core-sampling and analyses in the 2012-2013 MH21 offshore test of gas production from methane hydrates in the eastern Nankai Trough.</a> Mar. Petrol. Geol. 66 (Pt 2), 296 (2015).</li><li>Fujii, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Geological+setting+and+characterization+of+a+methane+hydrate+reservoir+distributed+at+the+first+offshore+production+test+site+on+the+Daini-Atsumi+Knoll+in+the+eastern+Nankai+Trough,+Japan.">Geological setting and characterization of a methane hydrate reservoir distributed at the first offshore production test site on the Daini-Atsumi Knoll in the eastern Nankai Trough, Japan.</a> Mar. Petrol. Geol. 66 (Pt 2), 310 (2015).</li><li>Mao, W. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hydrogen+clusters+in+clathrate+hydrate.">Hydrogen clusters in clathrate hydrate.</a> Science. 297 (5590), 2247-2249 (2002).</li><li>Lee, S., Liang, L., Riestenberg, D., West, O. R., Tsouris, C., Adams, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CO2+hydrate+composite+for+ocean+carbon+sequestration.">CO2 hydrate composite for ocean carbon sequestration.</a> Environ. Sci. Technol. 37 (16), 3701-3708 (2003).</li><li>Muromachi, S., Ohmura, R., Takeya, S., Mori, H. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clathrate+Hydrates+for+Ozone+Preservation.">Clathrate Hydrates for Ozone Preservation.</a> J. Phys. Chem. B. 114, 11430-11435 (2010).</li><li>Waite, W. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physical+properties+of+hydrate-bearing+sediments.">Physical properties of hydrate-bearing sediments.</a> Rev. Geophys. 47 (4), (2009).</li><li>Muraoka, M., Susuki, N., Yamaguchi, H., Tsuji, T., Yamamoto, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermal+properties+of+a+supercooled+synthetic+sand-water-gas-methane+hydrate+sample.">Thermal properties of a supercooled synthetic sand-water-gas-methane hydrate sample.</a> Energy Fuels. 29 (3), 1345-1351 (2015).</li><li>Gustafsson, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transient+plane+source+techniques+for+thermal+conductivity+and+thermal+diffusivity+measurements+of+solid+materials.">Transient plane source techniques for thermal conductivity and thermal diffusivity measurements of solid materials.</a> Rev. Sci. Instrum. 62 (3), 797-804 (1991).</li><li>Sakamoto, Y., Haneda, H., Kawamura, T., Aoki, K., Komai, T., Yamaguchi, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+Study+on+a+New+Enhanced+Gas+Recovery+Method+by+Nitrogen+Injection+from+a+Methane+Hydrate+Reservoir.">Experimental Study on a New Enhanced Gas Recovery Method by Nitrogen Injection from a Methane Hydrate Reservoir.</a> J. MMIJ. 123 (8), 386-393 (2007).</li><li>Lee, B. I., Kesler, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+generalized+thermodynamic+correlation+based+on+three-parameter+corresponding+states.">A generalized thermodynamic correlation based on three-parameter corresponding states.</a> AIChE J. 21 (3), 510-527 (1975).</li><li>Reid, R. C., Prausnitz, J. M., Poling, B. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+3,+Unit+3,+7.">Chapter 3, Unit 3, 7.</a> The properties of gases and liquids. , 47-49 (1987).</li><li>Anderson, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enthalpy+of+dissociation+and+hydration+number+of+methane+hydrate+from+the+Clapeyron+equation.">Enthalpy of dissociation and hydration number of methane hydrate from the Clapeyron equation.</a> J. Chem. Thermodyn. 36 (12), 1119-1127 (2004).</li><li>Waite, W. F., deMartin, B. J., Kirby, S. H., Pinkston, J., Ruppel, C. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermal+conductivity+measurements+in+porous+mixtures+of+methane+hydrate+and+quartz+sand.">Thermal conductivity measurements in porous mixtures of methane hydrate and quartz sand.</a> Geophys. Res. Lett. 29 (24), 82-1-82-4 (2002).</li><li>Kumar, P., Turner, D., Sloan, E. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermal+diffusivity+measurements+of+porous+methane+hydrate+and+hydrate-sediment+mixtures.">Thermal diffusivity measurements of porous methane hydrate and hydrate-sediment mixtures.</a> J. Geophys. Res. 109 (B1), (2004).</li><li>Huang, D., Fan, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+and+modeling+thermal+conductivity+of+gas+hydrate-bearing+sand.">Measuring and modeling thermal conductivity of gas hydrate-bearing sand.</a> J. Geophys. Res. 110 (B1), (2005).</li></ol>

The authors have nothing to disclose.

The effect of the formation heat of MH on measurement was estimated. The formation heat of MH was estimated from products of change rate of Sh as shown in Figure 3b and the enthalpy of formation H = 52.9 kJ mol&#8722;1 for MH14. Consequently, the maximum temperature change was 0.00081 &#176;C sec&#8722;1. This was much lower than the temperature increase &#916;Tc of the TPS sensor between 1 &#176;C and 1.5 &#176;C during th...

Gas hydrates are crystalline compounds that comprise cage structures of hydrogen-bonded water molecules containing guest molecules in the cage1. Large amounts of methane hydrates (MHs) in the ocean floor and permafrost regions are interesting future energy resources but may affect global climate conditions2.
In March 2013, the Japan Oil, Gas, and Metals National Corporation conducted the world&#39;s first offshore production test to extract gas from natural MH-bearing sediments in the eastern Nankai Trough using the &#34;depressurization method&#34; 3,4.
Gas hydrates can store gases such as methane1, hydrogen5, CO21,6, and ozone7. Hence, methane and hydrogen hydrates are studied as potential energy storage and transportation media. To reduce the CO2 emissions released into the atmosphere, CO2 sequestration using CO2 hydrates in deep-ocean sediments have been studied6. Ozone is currently used in water purification and food sterilization. Studies of ozone preservation technology have been conducted because it is chemically unstable7. The ozone concentration in hydrates is much higher than that in ozonized water or ice7.
To develop gas production from natural MH-bearing sediments and hydrate-based technologies, it is imperative to understand the thermal properties of gas hydrates. However, the thermal properties data and model studies of gas hydrate-bearing sediments are scarce8.
The &#34;depressurization method&#34; can be used to dissociate MH in the sediment pore space by decreasing the pore pressure below the hydrate stability. In this process, the sediment pore space components change from water and from MH to water, MH, and gas. The thermal properties&#39; measurement of the latter condition is difficult because the melting heat of MH may affect the measurements. To solve this problem, Muraoka et al. performed the thermal properties&#39; measurement at supercooled conditions during MH formation9.
With this video protocol, we explain the measuring method of supercooled synthetic sand-water-gas-MH sample.
Figure 1 shows the experimental setup for measuring the thermal properties of the artificial methane hydrate-bearing sediment. The setup is the same as shown in reference9. The system mainly comprises a high-pressure vessel, pressure and temperature control, and thermal properties of the measurement system. The high-pressure vessel is composed of cylindrical stainless steel with an internal diameter of 140 mm and a height of 140 mm; its inner volume with the dead volume removed is 2,110 cm3, and its pressure limit is 15 MPa. The transient plane source (TPS) technique is used to measure the thermal properties10. Nine TPS probes with individual radii of 2.001 mm are placed inside the vessel. The layout of the nine probes9 is shown in Figure 2 in reference9. The TPS probes are connected to the thermal properties&#39; analyzer with a cable and switched manually during the experiment. The details of the TPS sensor, connection diagram, and setup in the vessel are shown in Figures S1, 2, and 3 of the supporting information in reference9.
<img alt="Figure 1" src="/files/ftp_upload/53956/53956fig1.jpg" /> 
Figure 1: The experimental setup for measuring the thermal properties of the artificial methane hydrate-bearing sediment. The figure is modified from&#160;reference9. <a href="https://www.jove.com/files/ftp_upload/53956/53956fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The TPS method was used to measure the thermal properties of each sample. The method principles are described in reference10. In this method, the time-dependent temperature increase, &#916;Tave, is
<img alt="Equation 1" src="/files/ftp_upload/53956/53956eq1.jpg" />
where
<img alt="Equation 2" src="/files/ftp_upload/53956/53956eq2.jpg" />
In Equation 1, W0 is the output power from the sensor, r is the radius of the sensor probe, &#955; is the thermal conductivity of the sample, &#945; is the thermal diffusivity, and t is the time from the start of the power supply to the sensor probe. D(&#964;) is a dimensionless time dependent function. &#964; is given by (&#945;t/r)1/2. In Equation 2, m is the number of concentric rings of the TPS probe and I0 is a modified Bessel function. The thermal conductivity, thermal diffusivity, and specific heat of the sample are simultaneously determined by inversion analysis applied to the temperature increase as power is supplied to the sensor probe.

<table border="0" cellpadding="0" cellspacing="0" width="1353">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">TPS thermal probe, Hot disk sensor</td>
			<td style="width:251px;">Hot Disk AB Co., Sweden</td>
			<td style="width:267px;">#7577</td>
			<td style="width:392px;">Kapton sensor type, sensor radius 2.001 mm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Hot disk thermal properties analyzer</td>
			<td>Hot Disk AB Co., Sweden</td>
			<td style="width:267px;">TPS 2500&#160;</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:444px;">Toyoura standard silica sand</td>
			<td style="width:251px;">Toyoura Keiseki Kogyo Co., Ltd., Japan</td>
			<td style="width:267px;">N/A</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:444px;">Methane gas ,99.9999%</td>
			<td style="width:251px;">Tokyo Gas Chemicals Co., Ltd., Japan</td>
			<td style="width:267px;">N/A</td>
			<td>Grade 6N, Volume 47L, Charging pressure 14.7MPa</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Water Purification System,Elix Advantage 3&#160;</td>
			<td style="width:251px;">Merck Millipore., U.S.</td>
			<td style="width:267px;">N/A</td>
			<td>5 M&#937; cm (at 25&#176;C) resistivity</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Vibrating table, Vivratory packer</td>
			<td style="width:251px;">Sinfonia Technology Co. Ltd., Japan</td>
			<td style="width:267px;">VGP-60</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Chiller, Thermostatic Bath Circulator&#160;</td>
			<td style="width:251px;">THOMAS KAGAKU Co., Ltd., Japan</td>
			<td style="width:267px;">TRL-40SP</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Coorant, Aurora brine</td>
			<td style="width:251px;">Tokyo Fine Chemical Co.,Ltd., Japan</td>
			<td style="width:267px;">N/A</td>
			<td>ethylene glycol 71wt%</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Temparature gage</td>
			<td style="width:251px;">Nitto Kouatsu., Japan</td>
			<td style="width:267px;">N/A</td>
			<td>Pt 100, sheath-type platinum resistance temperature detector</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:444px;">Pressure gage</td>
			<td style="width:251px;">Kyowa Electronic Instruments., Japan</td>
			<td style="width:267px;">PG-200 KU</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Data logger</td>
			<td style="width:251px;">KEYENCE., Japan</td>
			<td style="width:267px;">NR-500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:444px;">Mass flow controller</td>
			<td style="width:251px;">OVAL Co., Japan</td>
			<td style="width:267px;">F-221S-A-11-11A</td>
			<td>Maximum flow 2000 Nml/M, maximum design pressure 19.6 MPa</td>
		</tr>
	</tbody>
</table>

protocol for measuring the thermal properties of a supercooled synthetic sand-water-gas-methane hydrate sample

Methane hydrates (MHs) are present in large amounts in the ocean floor and permafrost regions. Methane and hydrogen hydrates are being studied as future energy resources and energy storage media. To develop a method for gas production from natural MH-bearing sediments and hydrate-based technologies, it is imperative to understand the thermal properties of gas hydrates.
The thermal properties' measurements of samples comprising sand, water, methane, and MH are difficult because the melting heat of MH may affect the measurements. To solve this problem, we performed thermal properties' measurements at supercooled conditions during MH formation. The measurement protocol, calculation method of the saturation change, and tips for thermal constants' analysis of the sample using transient plane source techniques are described here.
The effect of the formation heat of MH on measurement is very small because the gas hydrate formation rate is very slow. This measurement method can be applied to the thermal properties of the gas hydrate-water-guest gas system, which contains hydrogen, CO2, and ozone hydrates, because the characteristic low formation rate of gas hydrate is not unique to MH. The key point of this method is the low rate of phase transition of the target material. Hence, this method may be applied to other materials having low phase-transition rates.

Figure 2a shows the temperature profile that is not affected by MH melting. &#916;Tc is the temperature change due to thermal constants&#39; measurement. Figure 2b shows the temperature profile that is affected by MH melting. The profile in Figure 2b cannot be analyzed through Equations 1 and 2 because these equations are derived by assuming stable sample conditions.
<p class="jove_content" fo:keep-together.within-...

Watch this Scientific Journal Video about Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample at JoVE.com

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

We present a protocol for measuring the thermal properties of synthetic hydrate-bearing sediment samples comprising sand, water, methane, and methane hydrate.

Methane hydrates (MHs) are present in large amounts in the ocean floor and permafrost regions. Methane and hydrogen hydrates are being studied as future ...

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JoVE Journal

Environment

8.8K Views.  National Institute of Advanced Industrial Science and Technology (AIST). We present a protocol for measuring the thermal properties of synthetic hydrate-bearing sediment samples comprising sand, water, methane, and methane hydrate.

Video: Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa1,2, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electron microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol 3 . Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high&#8208;resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography4,5. Moreover, OpNS can be a high&#8208;throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples 6. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.

More than half of proteins are small proteins (molecular mass &#60;200 kDa) that are challenging for both electron microscope imaging and three-dimensional reconstructions. Optimized negative staining is a robust and high-throughput protocol to obtain high contrast and relatively high resolution (~1 nm) images of small asymmetric proteins or complexes under different physiological conditions.

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of ...

Transient Gene Expression in Tobacco using Gibson Assembly and the Gene Gun

In order to target a single protein to multiple subcellular organelles, plants typically duplicate the relevant genes, and express each gene separately using complex regulatory strategies including differential promoters and/or signal sequences. Metabolic engineers and synthetic biologists interested in targeting enzymes to a particular organelle are faced with a challenge: For a protein that is to be localized to more than one organelle, the engineer must clone the same gene multiple times. This work presents a solution to this strategy: harnessing alternative splicing of mRNA. This technology takes advantage of established chloroplast and peroxisome targeting sequences and combines them into a single mRNA that is alternatively spliced. Some splice variants are sent to the chloroplast, some to the peroxisome, and some to the cytosol. Here the system is designed for multiple-organelle targeting with alternative splicing. In this work, GFP was expected to be expressed in the chloroplast, cytosol, and peroxisome by a series of rationally designed 5&#8217; mRNA tags. These tags have the potential to reduce the amount of cloning required when heterologous genes need to be expressed in multiple subcellular organelles. The constructs were designed in previous work11, and were cloned using Gibson assembly, a ligation independent cloning method that does not require restriction enzymes. The resultant plasmids were introduced into Nicotiana benthamiana epidermal leaf cells with a modified Gene Gun protocol. Finally, transformed leaves were observed with confocal microscopy.

This work describes a novel method for selectively targeting subcellular organelles in plants, assayed using the BioRad Gene Gun.

In order to target a single protein to multiple subcellular organelles, plants typically duplicate the relevant genes, and express each gene separately ...

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community&#8217;s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as ...

An Optimized Enrichment Technique for the Isolation of Arthrobacter Bacteriophage Species from Soil Sample Isolates

Bacteriophage isolation from environmental samples has been performed for decades using principles set forth by pioneers in microbiology. The isolation of phages infecting Arthrobacter hosts has been limited, perhaps due to the low success rate of many previous isolation techniques, resulting in an underrepresented group of Arthrobacter phages available for study. The enrichment technique described here, unlike many others, uses a filtered extract free of contaminating bacteria as the base for indicator bacteria growth, Arthrobactersp. KY3901, specifically. By first removing soil bacteria the target phages are not hindered by competition with native soil bacteria present in initial soil samples. This enrichment method has resulted in dozens of unique phages from several different soil types and even produced different types of phages from the same enriched soil sample isolate. The use of this procedure can be expanded to most nutrient rich aerobic media for the isolation of phages in a vast diversity of interesting host bacteria.

An Optimized Enrichment Technique for the Isolation of Arthrobacter Bacteriophage Species from Soil Sample Isolates

We present an enrichment protocol for the isolation of bacteriophages infecting bacteria in the Arthrobacter genus. This enrichment protocol produces fast and reproducible results for the isolation and amplification of Arthrobacter phages from soil isolates.

Bacteriophage isolation from environmental samples has been performed for decades using principles set forth by pioneers in microbiology. The isolation of ...

A New Application of the Electrical Penetration Graph (EPG) for Acquiring and Measuring Electrical Signals in Phloem Sieve Elements

Electrophysiological properties of cells are often studied in vitro, after dissociating them from their native environments. However, the study of electrical transmission between distant cells in an organism requires in vivo, artifact-free recordings of cells embedded within their native environment. The transmission of electrical signals from wounded to unwounded areas in a plant has since long piqued the interest of botanists. The phloem, the living part of the plant vasculature that is spread throughout the plant, has been postulated as a major tissue in electrical transmission in plants. The lack of suitable electrophysiological methods poses many challenges for the study of the electrical properties of the phloem cells in vivo. Here we present a novel approach for intracellular electrophysiology of sieve elements (SEs) that uses living aphids, or other phloem-feeding hemipteran insects, integrated in the electrical penetration graph (EPG) circuit. The versatility, robustness, and accuracy of this method made it possible to record and study in detail the wound-induced electrical signals in SEs of central veins of the model plant Arabidopsis thaliana1. Here we show that EPG-electrodes can be easily implemented for intracellular electrophysiological recordings of SEs in marginal veins, as well as to study the capacity of SEs to respond with electrical signals to several external stimuli. The EPG approach applied to intracellular electrophysiology of SEs can be implemented to a wide variety of plant species, in a large number of plant/insect combinations, and for many research aims.

A New Application of the Electrical Penetration Graph EPG for Acquiring and Measuring Electrical Signals in Phloem Sieve Elements

Electrical Penetration Graph (EPG) is a well-established technique for studying the feeding behavior of stylet-bearing insects. Here we show a new application of EPG as a non-invasive tool for the acquisition of intracellular electrophysiology recordings of sieve elements (SEs), the cells that form the phloem vasculature in plants.

Electrophysiological properties of cells are often studied in vitro, after dissociating them from their native environments. However, the study of ...

A Protocol for Collecting and Constructing Soil Core Lysimeters

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the landscape has complex and varied soil morphology, an accompanying disparity in flow paths for leachate through the soil macropore and matrix structure is present. The rate of flow through these paths is further affected by antecedent soil moisture. Lysimeters are used to quantify flow rate, volume of water and concentration of nutrients leaching downward through soils. While many lysimeter designs exist, accurately determining the volume of water and mass balance of nutrients is best accomplished with bounded lysimeters that leave the natural soil structure intact. 
Here we present a detailed method for the extraction and construction of soil core lysimeters equipped with soil moisture sensors at 5 cm and 25 cm depths. Lysimeters from four different Coastal Plain soils (Bojac, Evesboro, Quindocqua and Sassafras) were collected on the Delmarva Peninsula and moved to an indoor climate controlled facility. Soils were irrigated once weekly with the equivalent of 2 cm of rainfall to draw down soil nitrate-N concentrations. At the end of the draw down period, poultry litter was applied (162 kg TN ha-1) and leaching was resumed for an additional five weeks. Total recovery of applied irrigation water varied from 71% to 85%. Nitrate-N concentration varied over the course of the study from an average of 27.1 mg L-1 before litter application to 40.3 mg L-1 following litter application. While greatest flux of nutrients was measured in soils dominated by coarse sand (Sassafras) the greatest immediate flux occurred from the finest textured soil with pronounced macropore development (Quindocqua).

A detailed method for extraction and assembly of intact soil core lysimeters and their use for study of leachate and associated loss of nutrients from surface applied poultry litter is demonstrated.

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the ...

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of scientific publications address microplastic pollution of the sea surface. The protocol below describes the methodology for sampling, sample preparation, separation and chemical identification of microplastic particles. A manta net fixed on an &#187;A frame&#171; attached to the side of the vessel was used for sampling. Microplastic particles caught in the cod end of the net were separated from samples by visual identification and use of stereomicroscopes. Particles were analyzed for their size using an image analysis program and for their chemical structure using ATR-FTIR and micro FTIR spectroscopy. The described protocol is in line with recommendations for microplastics monitoring published by the Marine Strategy Framework Directive (MSFD) Technical Subgroup on Marine Litter. This written protocol with video guide will support the work of researchers that deal with microplastics monitoring all over the world.

The protocol below describes the methodology for: microplastics sampling on the sea surface, separation of microplastic and chemical identification of particles. This protocol is in line with the recommendations for microplastics monitoring published by the MSFD Technical Subgroup on Marine Litter.

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of ...

Thermal Scanning Conductometry (TSC) as a General Method for Studying and Controlling the Phase Behavior of Conductive Physical Gels

The thermal scanning conductometry protocol is a new approach in studying ionic gels based on low molecular weight gelators. The method is designed to follow the dynamically changing state of the ionogels, and to deliver more information and details about the subtle change of conductive properties with an increase or decrease in the temperature. Moreover, the method allows the performance of long term (i.e. days, weeks) measurements at a constant temperature to investigate the stability and durability of the system and the aging effects. The main advantage of the TSC method over classical conductometry is the ability to perform measurements during the gelation process, which was impossible with the classical method due to temperature stabilization, which usually takes a long time before the individual measurement. It is a well-known fact that to obtain the physical gel phase, the cooling stage must be fast; moreover, depending on the cooling rate, different microstructures can be achieved. The TSC method can be performed with any cooling/heating rate that can be assured by the external temperature system. In our case, we can achieve linear temperature change rates between 0.1 and approximately 10 &#176;C/min. The thermal scanning conductometry is designed to work in cycles, continuously changing between heating and cooling stages. Such an approach allows study of the reproducibility of the thermally reversible gel-sol phase transition. Moreover, it allows the performance of different experimental protocols on the same sample, which can be refreshed to initial state (if necessary) without removal from the measuring cell. Therefore, the measurements can be performed faster, in a more efficient way, and with much higher reproducibility and accuracy. Additionally, the TSC method can be also used as a tool to manufacture the ionogels with targeted properties, like microstructure, with an instant characterization of conductive properties.

Thermal Scanning Conductometry TSC as a General Method for Studying and Controlling the Phase Behavior of Conductive Physical Gels

The kinetics of the cooling process defines the properties of ionic gels based on low molecular weight gelators. This manuscript describes the usage of thermal scanning conductometry (TSC), which obtains full control over the gelation process, along with in situ measurements of the samples' temperature and conductivity.

The thermal scanning conductometry protocol is a new approach in studying ionic gels based on low molecular weight gelators. The method is designed to ...

The Hawaii Protocol for Scientific Monitoring of Coffee Berry Borer: a Model for Coffee Agroecosystems Worldwide

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at capturing and quantifying the dynamics and impact of this invasive insect pest as well as the development of its host plant across a heterogeneous landscape. The cornerstone of this comprehensive monitoring system is timely georeferenced data collection on CBB movement, coffee berry infestation, mortality by the fungus Beauveria bassiana, and coffee plant phenology via a mobile electronic data recording application. This electronic data collection system allows field records to be georeferenced through built-in global positioning systems, and is backed by a network of weather stations and records of farm management practices. Comprehensive monitoring of CBB and host plant dynamics is an essential part of an area-wide project in Hawaii to aggregate landscape-level data for research to improve management practices. Coffee agroecosystems in other parts of the world that experience highly variable environmental and socioeconomic factors will also benefit from implementing this protocol, in that it will drive the development of customized integrated pest management (IPM) to manage CBB populations.

Comprehensive monitoring of coffee berry borer and host plant dynamics is essential for aggregating landscape-level data to improve management of this invasive pest. Here, we present a protocol for scientific monitoring of coffee berry borer movement, infestation, mortality, coffee plant phenology, weather, and farm management via a mobile electronic data recording application.

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at ...

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (Zea mays L.)

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole grain composition and processing characteristics vary among maize hybrids and can impact the quality of the final processed product. Therefore, in order to produce healthier processed food products from maize, it is necessary to know how to optimize processing parameters for particular sets of germplasm to account for these differences in grain composition and processing characteristics. This includes a better understanding of how current processing techniques impact the nutritional quality of the final processed food product. Here, we describe a microscale protocol that both simulates the processing pipeline to produce cornflakes from large flaking grits and allows for the processing of multiple grain samples simultaneously. The flaking grits, the intermediate processed products, or final processed product, as well as the corn grain itself, can be analyzed for nutritional content as part of a high-throughput analytical pipeline. This procedure was developed specifically for incorporation into a maize breeding research program, and it can be modified for other grain crops. We provide an example of the analysis of insoluble-bound ferulic acid and p-coumaric acid content in maize. Samples were taken at five different processing stages. We demonstrate that sampling can take place at multiple stages during microscale processing, that the processing technique can be utilized in the context of a specialized maize breeding program, and that, in our example, most of the nutritional content was lost during food product processing.

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Here, we present a microscale protocol for processing grain samples and for incorporating this microscale approach into a high-throughput analytical pipeline. This is a higher throughput adaptation of currently available protocols.

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole ...