CMI Technology

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CMI Technology studies CO2 storage in geological formations with a focus on understanding leakage risks associated with old oil and gas wells, and on modelling injection in unconventional reservoirs. A program on advanced batteries is developing new diagnostic methods. Other research focuses on incentivizing the decarbonisation of the transportation sector, with an emphasis on biofuel production combined with CO2 capture and storage.

Research Highlights – At a Glance

Michael Celia: In earlier work, the Celia group studied CO2 injection into depleted shale-gas systems and concluded that it was not feasible for most situations. That modeling work has now been extended to study the fate of fracking fluids in shale-gas systems. Modeling results indicate that the large amount of fracking fluids left underground is unlikely to pose any significant environmental risk.

Daniel Steingart: The misbehavior of batteries shows up in many ways and from a variety of root causes. The challenge is determining the where and what of the root causes. In 2017, the Princeton Lab for Electrochemical Engineering Systems Research made advances toward this understanding by studying the most fundamental electrochemical behaviors with novel electron microscopy. 

Eric Larson: The US transportation sector emits about a quarter of total US greenhouse gases. It may be the most challenging sector to decarbonize, given its heavy reliance on petroleum and millions of small emission sources. Biofuels are one of the few decarbonization options, especially for difficult-to-electrify modes. Moreover, deployment of biofuel production systems that incorporate CO2 capture and storage may be essential for achieving mid-century greenhouse gas emission reductions that limit global warming to 2oC. The required speed and scale of deployment of biomass supply infrastructure and conversion facilities to meet future biofuels targets that could mitigate significant transportation sector emissions have no historical precedents. Incentives stronger than those that drove the expansion of the US corn-ethanol industry will be needed for an advanced biofuel industry to contribute significant carbon mitigation by mid-century.

 


 

Fate of Fracking Fluids in Shale-Gas Systems
Principal Investigator: Michael Celia

At a Glance 

In earlier work, the Celia group studied CO2 injection into depleted shale-gas systems and concluded that it was not feasible for most situations. That modeling work has now been extended to study the fate of fracking fluids in shale-gas systems. Modeling results indicate that the large amount of fracking fluids left underground is unlikely to pose any significant environmental risk.

Research Highlight

Earlier Modeling Work: CO2 Sequestration in Shales

In earlier work on shale gas systems, the Celia group developed a model for CO2 injection into depleted shales and analyzed the feasibility of large-scale CO2 sequestration in shales. The model involved two-component (methane and CO2) single-phase (gas) flow in the shale rock, and included competitive sorption as well as pressure-dependent nonlinearities. While being a reduced-order model, the results obtained matched gas production data very well, which gave confidence that the two-component model was reasonable.

The overall finding was that large-scale injection of CO2 is not feasible because of the excessive number of wells required to inject significant quantities of CO2. For example, injection of emissions from just the four largest coal-fired power plants in southwest Pennsylvania requires many thousands of wells in the Marcellus Formation. Rather than inject captured CO2 into depleted shales, it makes more sense to build a larger pipeline to transport the CO2 to a more suitable injection location like the Illinois Basin.

New Modeling Work: Fate of Fracking Fluid

The earlier modeling work has been extended to focus on the fracturing (“fracking”) fluid. One of the persistent questions about hydraulic fracturing in shale systems is the ultimate fate of the injected fracking fluid. In many shale systems, most of the injected fracking fluid does not return to the surface. This has led to concern that the injected fluid might be available to migrate out of the formation and leak into other formations, and potentially into groundwater zones.

The Celia group extended their earlier modeling work and developed a two-phase model (aqueous-based liquid fracking fluid and resident natural gas) to simulate the time period immediately following the fracking, including the shut-in period, and the subsequent longer period associated with production of gas (Figure 2.1.1). This modeling is based on an open-source, full reservoir simulator (MRST), and includes all relevant fluid flow processes, including capillary hysteresis. Detailed water injection and production data were made available for several wells in the Horn River Formation in British Columbia, and those data were used to test the model. Results showed very good matches to the amount of water remaining underground as well as the timing of the water that does flow back to the surface. The two-phase model also produces excellent matches with gas production data. These comparisons between model and data give confidence that the model produces useful results.

2.1.1.png
Figure 2.1.1. Illustration of horizontal shale gas well (top) with the model representation below it. The model representation includes the dark gray inner region representing the propped fracture, which contributes to fracking fluid imbibition and subsequent gas flow, and the light gray unpropped region that opens during fracking fluid injection but closes afterward. The dashed orange box shows the numerical model domain. Red arrows denote gas flow and blue arrows denote fracking fluid flow. Not to scale2.

In terms of the fate of the fracking fluid that remains underground, simulation results show that very strong capillary imbibition into the shale rock matrix leads to large amounts of fracking fluid being imbibed into the rock (Figure 2.1.2). Capillary hysteresis enhances the strong underlying capillarity in the rock and leads to almost all of the imbibed liquid remaining in the rock matrix during the gas production process. This result appears to be robust across a range of parameters including different representations of the capillary pressure functions.

2.1.2.png
Figure 2.1.2. Water volume in the subsurface as a percentage of total volume injected. The graph shows total water (Sum) and the distribution of that total between the fractures and the matrix. The time period (2) is the shut-in period, and the later time (3) is the gas production period. Notice that even after gas production begins, water continues to imbibe from the fractures into the matrix2.

These overall results show that the large volume of fracking fluid that remains underground is imbibed strongly into the host rock and remains there in the long term, therefore posing very little risk in terms of migration out of the shale production zone.

References

1 Edwards, R.W.J. and M.A. Celia, 2018. Shale Gas Well, Hydraulic Fracturing, and Formation Data to Support Modeling of Gas and Water Flow in Shale Formations. Water Resources Research, in revision.

2 Edwards, R.W.J., F. Doster, M.A. Celia, and K.W. Bandilla, 2017. Numerical Modeling of Gas and Water Flow in Shale Gas Formations with a Focus on the Fate of Hydraulic Fracturing Fluids. Env. Sci. and Tech. 51(23): 13779-13787. doi: 10.1021/acs.est.7b03270.

 


 

Understanding Long-Term Battery Behavior Through Fundamental Crystal Growth
Principal Investigator: Daniel Steingart

At a Glance

The misbehavior of batteries shows up in many ways and from a variety of root causes. The challenge is determining the where and what of the root causes. In 2017, the Princeton Lab for Electrochemical Engineering Systems Research made advances toward this understanding by studying the most fundamental electrochemical behaviors with novel electron microscopy.

Research Highlight

In the second year working with the Carbon Mitigation Initiative, the Steingart group built upon their studies of dendrites by examining the nanoscale growth of metals, or the “birth of a dendrite.” Three recent publications in collaboration with the University of California Los Angeles, IBM, and the University of Pennsylvania explore different aspects of plate metal growth1,2,3.

The group’s first effort exploits a challenge of in situ electron microscopy: observing with electrons can alter electrochemical behavior. To understand how to tame this behavior, the team designed a system to purposefully allow the electron beam to “write” and “erase” crystals, thereby turning the problem into a solution (Figure 2.2.1). Postdoctoral researcher Jeung Hun Park showed that crystals can be grown at arbitrary locations by electron beam-induced reactions of metal ions to metals from solutions. This work is expected to be extended to understand multicomponent alloys and core-shell nanostructures for fundamental investigations in energy storage.

2.2.1.png
Figure 2.2.1. Progression in time of electron beam-driven gold nanoparticle growth in solution.

The second effort examines multicomponent behaviors of zinc and bismuth to control morphology, building upon earlier group work studying macroscale effects4. The simultaneous deposition of reactive and noble species allows for super structures to be created that can reversibly cycle to provide high energy density storage (Figure 2.2.2). The challenge to date is that the localization of the co-deposit within an electrode is uneven. The work this year explains in part the heterogeneity, and may enable us to tame this problem in coming years.

2.2.2.png
Figure 2.2.2. Examples of zinc only (left) and ZnBi codeposition (right) at the nanoscale.

Finally, the group completes this work by assisting researchers at the University of Pennsylvania with a comprehensive study of interfacial evolution at the nanoscale (Figure 2.2.3). This work provides new insight into the earliest stages of metal growth, and therefore the origins of uneven depositions that can create unwanted (or desired5) dendrites.

2.2.3.png
Figure 2.2.3. Growth of an interface with overlaid velocity mapping.

In the next year the team plans to apply their toolset to two new challenges: 1) the growth of plate lithium metal (the most reducing species currently known) and 2) extending our understanding of nanoscale behaviors to microscale and macroscale battery behaviors that are directly visible with lab-scale electrical and acoustic diagnostics.

References

1 J. H. Park, D. A. Steingart, S. Kodambaka, and F. M. Ross, “Electrochemical electron beam lithography: Write, read, and erase metallic nanocrystals on demand,” Sci Adv, vol. 3, no. 7, p. e1700234, Jul. 2017.

2 J. H. Park, N. M. Schneider, D. A. Steingart, H. Deligianni, S. Kodambaka, and F. M. Ross, “Control of Growth Front Evolution by Bi Additives during ZnAu Electrodeposition,” Nano Lett., Jan. 2018.

3 N. M. Schneider, J. H. Park, J. M. Grogan, D. A. Steingart, H. H. Bau, and F. M. Ross, “Nanoscale evolution of interface morphology during electrodeposition,” Nat. Commun., vol. 8, no. 1, p. 2174, Dec. 2017.

4 Gallaway, J.W., A.M. Gaikwad, B. Hertzberg, C.K. Erdonmez, Y.K Chen-Wiegart, L.A. Sviridov, K. Evans-Lutterodt, J. Wang, S. Banerjee, and D.A., Steingart, 2014. An In Situ Synchrotron Study of Zinc Anode Planarization by a Bismuth Additive. J. Electrochem. Soc. 161(3): A275–A284. doi: 10.1149/2.037403jes.

5 Chamoun, M., B.J. Hertzberg, T. Gupta, D. Davies, S. Bhadra, B, Van Tassel, C. Erdonmez, and D.A. Steingart, 2015. Hyper-dendritic nanoporous zinc foam anodes. NPG Asia Materials. 7(4): e178. doi: 10.1038/am.2015.32.

 


 

Mid-Century Advanced Biofuel Potential for the US: A Thought Experiment
Principal Investigator: Eric D. Larson *

At a Glance 

The US transportation sector emits about a quarter of total US greenhouse gases. It may be the most challenging sector to decarbonize, given its heavy reliance on petroleum and millions of small emission sources. Biofuels are one of the few decarbonization options, especially for difficult-to-electrify modes. Moreover, deployment of biofuel production systems that incorporate CO2 capture and storage may be essential for achieving mid-century greenhouse gas emission reductions that limit global warming to 2oC. The required speed and scale of deployment of biomass supply infrastructure and conversion facilities to meet future biofuels targets that could mitigate significant transportation sector emissions have no historical precedents, as illustrated here. Incentives stronger than those that drove the expansion of the US corn-ethanol industry will be needed for an advanced biofuel industry to contribute significant carbon mitigation by mid-century.

Research Highlight

Co-funded by CMI and Stanford’s Global Climate and Energy Project, the Energy Systems Analysis Group (ESAG) at Princeton University continued a collaboration with the University of Minnesota (UMN) and Colorado State University (CSU) to assess potential mid-century contributions from negative-emissions biomass-based transportation fuels. ESAG’s focus has been on understanding the prospective performance and economics of a range of conversion processes for making transportation fuels from lignocellulosic (plant dry matter) biomass while capturing CO2 for geologic storage. UMN and CSU are focusing on understanding biomass production for energy on abandoned croplands, where soil organic carbon storage provides a negative emissions opportunity.

By ESAG’s estimates, gasoline- and diesel-like fuels made from seven exajoules of lignocellulosic biomass grown sustainably in the US without displacing land for food production could make a substantial contribution to reducing transportation-sector emissions in the future. This would take on transport modes (air and long-haul trucks, trains, and ships) that are particularly resistant to electrification. As a thought experiment, we examine the plausibility of different scale-up rates for this industry and the resulting contributions that advanced biofuels might make by mid-century.

Prospective scale-up rates are compared with the most relevant historical precedent, the expansion of the US corn-ethanol industry. That industry grew slowly for about the first three decades, but more rapidly once significant incentives were introduced beginning in 1999 when California banned MTBE as a gasoline oxygenate, spurring increased demand for ethanol as a substitute (Figure 2.3.1a). Additional incentives followed, further accelerating growth, but subsequently slowed as total output approached the corn-ethanol supply limit under the RFS-2 legislation. The curve fit to the data in Figure 2.3.1a derives from the following equation:

2.3_equation.png

Where Pt is petajoules of feedstock processed in year t. Time zero (t0) is 1981, representing the start of the corn-ethanol industry. C1, C2, b, and tinfl are constants that have been tuned to achieve a visual best fit. In Figure 2.3.1a, C1 = 12.6/year, C2 = 1680 PJ/year, tinfl = 2009.5, and b = 0.6/year.

Eqn. 1 is a modified logistics function. (A pure logistics function includes only the second term on the right.) Logistics functions are used to describe growth processes (e.g., population expansion or infectious disease spread) that begin slowly, then accelerate exponentially before decelerating and eventually reach a saturation level. 

2.3.a.png
2.3.b.png
Figure 2.3.1 (a) Historical growth of US corn-ethanol industry (corn energy input basis) and incentives that have driven it, and (b) alternative scenarios for growth of an advanced lignocellulosic biofuel industry (biomass input energy basis) starting in 2025. Dashed lines are annual expansion rates (right axis) corresponding to the solid curves of the same color showing annual biomass processed (left axis).

A logistics function of the same form as Eqn. 1 is developed to represent the scale-up trajectory of a future lignocellulosic biofuels industry. It is assumed that commercial biofuel production would begin in 2025 with enough biomass processed to produce 500 million gallons of biofuel, or 65 PJ on a higher heating value basis (65 PJHHV), assuming a biofuel energy content similar to gasoline. For comparison, the average US corn-ethanol facility has a production capacity of 78 million gallons per year, or 7 PJHHV, of ethanol, and the largest one has a capacity of 375 million gallons per year, or 33 PJHHV

If growth of an advanced biofuel industry from 2025 follows a trajectory like that seen for corn ethanol, i.e., slow linear growth for about 20 years before accelerating, the output of a lignocellulosic bioconversion industry by 2050 would still be only a fraction of that of the current corn-ethanol industry. 2050 is chosen as a nominal target date for discussion because deep reductions in carbon emissions economy-wide would be needed by then if global warming is to be limited to less than 2°C.

Alternatively, if sufficient incentives were in place by 2025 so that investment in the industry accelerates without the slow initial phase, growth trajectories like those in Figure 2.3.1b could result. The solid lines in Figure 2.3.1b follow Eqn. 1, but without the linear term (i.e., C1 = 0). The value of C2 is 7000 PJ/y, the projected future sustainable biomass feedstock supply. The value of tinfl varies in 2.5-year increments from one line to the next, and for each value of tinfl, b is set such that the amount of biomass processed in 2025 corresponds to the production of 500 million gallons of biofuel. The dashed lines plot the slopes of the solid lines, i.e., the dashed lines show annual growth rates.

Figure 2.3.2 compares metrics derived from Figure 2.3.1 for the US corn-ethanol and prospective advanced biofuel industries. The target feedstock-energy input, which reflects the scale of the bioconversion industry, for the advanced biofuel industry is more than triple that for the corn-ethanol industry. For the fastest assumed growth, the advanced biofuel industry would essentially reach the target level by 2050, but doing so would require an average annual growth rate (from 10% to 90% of the target) nearly quadruple that observed for the corn-ethanol industry during its most rapid expansion phase. With the slowest assumed growth rate, the advanced biofuel industry reaches only about half of the target by 2050, but still must grow nearly twice as fast as the corn-ethanol industry did in order to reach this modest level.

 

Corn ethanol

Advanced (lignocellulosic) biofuel industry

TARGET total feedstock input, PJ/y

2,150

7,000

Date when 90% of TARGET is reached

 

2043

2047

2051

2055

2058

2062

Years required from 10% to 90%

17

14

17

20

23

25

27

Average feedstock-energy growth, PJ/y/y

111

417

343

292

254

234

205

Average feedstock-volume growth, Mm3/y/y

10

187

154

131

114

105

92

Figure 2.3.2. Comparison of historical US corn-ethanol industry and a prospective advanced biofuel industry.

Also shown in Figure 2.3.2 are average growth rates expressed in terms of biomass feedstock volumes, which reflect the scale of the biomass feedstock supply industry (as distinct from the biomass conversion industry). For the advanced biofuel industry to achieve 90% of the target level by 2043, the average growth in volume of biomass handled is 187 million m3/y/y. This is 19 times the average annual growth seen for the corn ethanol industry. It is so much larger both because of the larger target scale for the bioconversion industry and because the volumetric energy density of baled crop residues or grasses, which constitute the lignocellulosic biomass supply, is only about one-fifth of that for corn grain. At the target lignocellulosic biomass supply level, the biomass collection and transport infrastructure would need to handle 17 times as much volume as managed today by the corn-handling infrastructure for the ethanol industry.

Advanced lignocellulosic biofuel conversion technologies are not yet commercial today. In practice, they would need to be commercially ready within the next three or four years for industrial production to start in 2025 at the scale envisioned in Figure 2.3.1.

 


 

Technology Publications

Bandilla, K.W. and M.A. Celia, 2017. Active Pressure Management through Brine Production for Basin-wide Deployment of Geologic Carbon Sequestration. Int J Greenh Gas Con. 61: 155-167. doi: 0.1016/j.ijggc.2017.03.030 

Bandilla, K.W., B. Guo, and M.A. Celia, 2017. Applicability of Vertically Integrated Models for Carbon Storage in Structured Heterogeneous Domains. Energy Procedia. 114: 3312-3321. doi: 10.1016/j.egypro.2017.03.1463.

Becker, B., B. Guo, K. Bandilla, M.A. Celia, B. Flemisch, and R. Helmig, 2017. A Pseudo Vertical Equilibrium Model for Slow Gravity Drainage Dynamics. Water Resources Research. 53(12): 10491-10507. doi: 10.1002/2017WR021644.

Celia, M.A., 2017. Geological Storage of Captured Carbon Dioxide as a Large-scale Carbon Mitigation Option. Water Resources Research. 53(5): 3527-3533. doi: 10.1002/2017WR020841.

Celia, M.A. and D.H. Feng, 2017. How China and Asia Can Lead the Fight Against Global Warming along the Belt and Road. South China Morning Post. http://www.scmp.com/comment/insight-opinion/article/2110296/how-china-a….

Edwards, R.W.J., F. Doster, M.A. Celia, and K.W. Bandilla, 2017. Numerical Modeling of Gas and Water Flow in Shale Gas Formations with a Focus on the Fate of Hydraulic Fracturing Fluids. Env. Sci. and Tech. 51(23): 13779-13787. doi: 10.1021/acs.est.7b03270.

Guo, B., Y. Tao, K.W. Bandilla, and M. Celia, 2017. Vertically Integrated Dual-porosity and Dual-permeability Models for CO2 Sequestration in Fractured Geological Formations. Energy Procedia. 114: 3343-3352. doi: 10.1016/j.egypro.2017.03.1466.

Greig, C., T.G. Kreutz, E.D. Larson, J.C. Meerman, R.H. Williams, 2017. Lignite-plus-Biomass to Synthetic Jet Fuel with CO2 Capture and Storage: Design, Cost, and Greenhouse Gas Emissions Analysis for a Near-Term First-of-a-Kind Demonstration Project and Prospective Future Commercial Plants. Final report under contract DE-FE0023697 to The National Energy Technology Laboratory, US Department of Energy. http://acee.princeton.edu/wp-content/uploads/2017/10/LBJ-FINAL-REPORT-R….

Meerman, J.C. and E.D. Larson, 2017. Negative-carbon drop-in transport fuels produced via catalytic hydropyrolysis of woody biomass with CO2 capture and storage. Sustainable Energy and Fuels. 1: 866-881. doi: 10.1039/C7SE00013H.

Park, J.H., D.A. Steingart, S. Kodambaka, and F.M. Ross, 2017. Electrochemical electron beam lithography: Write, read, and erase metallic nanocrystals on demand. Sci Adv. 3(7): e1700234. doi: 10.1126/sciadv.1700234.

Park, J.H., N.M. Schneider, D.A. Steingart, H. Deligianni, S. Kodambaka, and F.M. Ross, 2018. Control of Growth Front Evolution by Bi Additives during ZnAu Electrodeposition. Nano Lett. 18(2): 1093-1098. doi: 10.1021/acs.nanolett.7b04640.

Paustian, K., E. Larson, A. Swan, E. Marx, J. Kent, and N. Zenes, 2017. Carbon Farming – A Working Paper Assessing the Potential for Soil C Sequestration. http://acee.princeton.edu/wp-content/uploads/2017/07/Carbon-Framing-wor…;

Schneider, N.M., J.H. Park, J.M. Grogan, D.A. Steingart, H.H. Bau, and F.M. Ross, 2017. Nanoscale evolution of interface morphology during electrodeposition. Nat. Commun. 8(1): 2174. doi:10.1038/s41467-017-02364-9.

 

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