A new grant (#1541588) from the Instrumentation and Facilities program in the NSF Division of Earth Sciences (NSF-EAR/IF) has allowed us to acquire new thermal analysis instrumentation for increased capacity of characterization of organic matter in soils and sediments. In addition to our existing Netzsch STA409 instrument coupled to an LI-840A CO2 and H2O infrared gas analyzer, we now have a Netzsch STA499 F3 Jupiter with a robotic automatic sample changer. The new instrument is also coupled to its own LI-840A for CO2 and H2O evolved gas analysis.

double_the_STA_fun

Our new STA449 instrument (right) has an automatic sample changer, and substantially increases our sample throughput compared to our older STA409 instrument (left).

Thermal analysis techniques are increasingly used as part of a suite of methods to characterize organic matter stability and quality in soils, sediments, composts, biochars, and other environmental samples. Our previous equipment was a single-sample, manual-loading operation that could handle 3-4 samples per working day. That kind of sample throughput was unable to meet the geoscience research community’s demand for rapid and data-rich characterization of organic matter in soils and sediments. The new autosampler-equipped thermal analyzer will allow samples to be analyzed unsupervised around the clock, thus allowing its application in large, multidisciplinary projects such the cross-CZO characterization of controls on soil organic matter dynamics. Other research projects that will greatly benefit from the new instrumentation include correlation of thermal analysis results with conventional, analytical methods of characterizing SOM composition, simultaneous quantification of organic, inorganic and pyrogenic C in soils and sediments, and thermal fractionation as a preparatory step for radiocarbon analysis. At present, the feasibility of these large-scale, “big-data” styled research projects is severely limited by low sample throughput. The new instrument is part of an open multi-user facility that will be available for collaborators locally and worldwide. The relative ease and speed of analysis enables its use by undergraduate students, directly supporting undergraduate research and teaching tool in the Earth, environmental, and materials sciences. We are currently working on updating our data processing pipeline to allow users and collaborators to access raw data and process them using open and reproducible methods that can be accessed online.