There have been quite a lot of NMR studies centered around apple cider (non-alcoholic) and apple cider vinegar. However a search of the literature turns up no reference for NMR analysis of hard apple cider. This effort was undertaken to analyse the alcohol content of the ciders and to determine the malic and acetic acid content. Ciders were produced by Dr Tim McMahon of Orange Community College, NY….for his own consumption.

Below are the NMR spectra obtained by regular 1H acquisition and with BINOM solvent suppression.

Data was obtained on our Varian 300 MHz spectrometer. Samples were prepared by degassing followed by addition of 1 drop of D2O as lock solvent.

Process NMR Associates, LLC (Danbury CT) and Active Spectrum, Inc (San Carlos CA) are collaborating in the application of micro-ESR technology to petroleum applications. The initial work has focussed on crude oils but will soon be expanded to residues and cracker feedstocks.

Five samples of crude oil were tested by Micro-ESR spectrometry. The samples were:

1. Vasconia, Magdalena Basin, Columbia (V=39 ppm)
2. Merey, Eastern Venezuela Basin, Venezuela (V=303 ppm)
3. Oriente, Oriente Basin, Ecuador (V=65 ppm)
4. Qua Iboe, Agbada Formation, Niger Delta (V=2 ppm)
5. Basrah Light, Zubair Zone, Iraq (V=29 ppm)

The following spectra were observed:

Figure 1: Micro-ESR Spectra of Crude Oil

The central peak is a combination of a persistent carbon-centered organic radical (g = 2.003) found in asphaltenes, and a vanadyl (VO2+) peak. The additional smaller peaks are associated with vanadyl only.

For producers, the technique could be used to rapidly measure asphaltene concentration on-line. The spin density of the organic radical is a function of the maturity of the oil and will of course vary between deposits. Notwithstanding, rapid electronic measurement of asphaltenes remains a topic of great interest. Similar techniques have also been used to assess the quality of coals. For refiners, vanadium is a contaminant that poisons the refinery catalyst. ESR has been used by refiners since 1962 to rapidly measure vanadium content in crude oil feedstocks both on-line and in laboratories. Active Spectrum Inc.’s Micro-ESR is shown below. It is 2.25″ in diameter by 2.5″ high. Power input is 12-30VDC, and the data interface is USB. The device is available as either an on-line sensor or as a benchtop unit.

Figure 2: Micro-ESR Sensor

Figure 3: Higher Homogeneity Spectrum of Merey Crude

Micro-ESR is complimentary to NMR in that it observes paramagnetic metals and organic radicals which are unobservable by NMR. The stable free radical signal is indicative and quantitative to the amount of asphaltenes in the crude oil sample and vanadium metal content is an important processing parameter for cracking processes as it is active in the passivation of catalysts. NMR on the other hand observed the detailed hydrocarbon chemistry of the sample and yields chemico-physical parameters such as aromaticity, paraffinicity, naphthenicity, distillation, density, PAH distribution. In combination these two technologies yield a detailed picture of the petroleum materials before and during the refining process.

Samples provided by John Edwards of Process NMR Associates, LLC. Micro-ESR analysis provided by James White of Active Spectrum, Inc,

Active Spectrum, Inc. 110 Glenn Way #15, San Carlos, CA 94070 650-610-0720 | 626-628-1970 f | activespectrum.com

Process NMR Associates, LLC. 87A Sand Pit Rd, Danbury, CT 06810 203-744-5905 | 203-743-9297 f | process-nmr.com

PDF Version of Application Note

For more information contact John Edwards (203) 744-5905

Current Technique for Feedstream Analysis:
Analysis Performed – Refractive Index, Distillation, Specific Gravity
Calculation Obtained – Watson K-Factor
Outcome: aromatic carbon number, aromatic hydrogen number, total hydrogen content
Proposition: Detailed hydrocarbon analysis for kinetic model development.

Our experience is that an improved and useful analysis can be obtained from NMR
analysis. There are several ways to approach the NMR analysis and the
chemometric approach to correlating NMR data to physico-chemical parameters of
use to process control.

RCC Feedstream Analysis by 1H and 13C NMR: Multivariate Prediction of Chemical and Physical Properties

Presented at the 236th ACS National Meeting, Philadelphia PA, August 17-21, 2008

John C. Edwards Ph.D.
Process NMR Associates LLC
87A Sand Pit Rd, Danbury, CT 06810

Jincheol Kim,
SK Energy Co., Ltd, SK Energy Technology Center,
140-1, Wonchon-dong, Yuseong-gu, Daejeon 305-712, Korea

Summary of Slides

1) 60 MHz process NMR data available from online NMR unit.

2) 300 MHz 1H NMR data available from standard NMR experiments on laboratory NMR system at Process NMR Associates

3) Expansions of 1H NMR data on RCC Feeds

4) Calculated 1H NMR Parameters Represented as an alternative “spectrum” for use in chemometric modeling and linear regression.

5) 13C NMR Data obtained on RCC Feeds

6) Expansions of 13C NMR Data

7) 13C NMR and Average Molecule Parameters Calculated from 13C Spectrum

Calculated 13C NMR Parameters Represented as an alternative “spectrum” for use in chemometric modeling and linear regression.

9) Correlations of Spectra and Calculated Parameters to Physico-Chemical properties of RCC Feeds

10) Correlation of Spectra and Calculated Parameters to Density

11) Variable Selection for Linear Correlation of Calculated NMR Parameters to Physico-Chemical Properties of RCC Feeds.

12) Correlation of Calculated 13C NMR Parameters (C-Type and Average Molecule) with both high resolution 1H and 13C NMR spectra. Models created can be utilized by personnel with no NMR experience to calculate NMR parameters directly from the spectrum without any prior knowledge of integrations or calculations to be performed.

Summary
Chemical and Physical Properties of RCC Feedstreams can be determined
by 1H NMR (at 60 and 300 MHz) and by 13C NMR
H-Type and C-Type Parameters do not provide as good a correlation as is observed
by full spectrum regression. This is due to loss of resolved chemical shift information
when the spectrum is reduced to larger integral areas.
1H NMR can be combined with PLS regression modeling to provide detailed carbon
type analysis for RCC Feeds
Regression analysis of 13C NMR data can be utilized to fully automate the prediction
of 13C NMR type analysis : reducing the necessity for considerable knowledge and
analysis time on the part of the analyst.

For further Detail Contact John Edwards