Co-Optimization of

Fuels & Engines

FY16 Year in Review

better fuels | better vehicles | sooner
 Table of Contents 

Letter from the Leadership Team..............................................3

Big-Picture Targets .............................................................................4

Dialogue with Stakeholders..........................................................5

Integrated Capabilities.....................................................................6

Technical Research Accomplishments & Impact.............9

Building the Foundation......................................................................10

Thrust I: Spark Ignition ........................................................................16

Thrust II: Advanced Compression Ignition.......................................23

Next Steps ............................................................................................. 26

Publications...........................................................................................27

Media Coverage................................................................................. 29

Partners...................................................................................................30

About the Co-Optimization of 

Fuels & Engines (Co-Optima) Initiative 

Transportation accounts for 70% of U.S. petroleum 

consumption and 27% of the country’s greenhouse gas 

(GHG) emissions, and the internal combustion engines 

(ICEs) that generate most of these emissions will continue to power vehicles for decades to come. The U.S. 

Department of Energy’s (DOE’s) Co-Optima initiative 

is accelerating the introduction of affordable, scalable, 

and sustainable fuels and high-efficiency, low-emission 

engines with a first-of-its-kind effort to simultaneously 

tackle fuel and engine research and development (R&D). 

Co-Optima is conducting research to identify the fuel 

properties and engine design characteristics needed to 

maximize vehicle performance and affordability, while 

deeply cutting harmful emissions. Rather than endorsing a single solution, this initiative is designed to arm 

industry, policymakers, and other key stakeholders with 

the scientific foundation and market intelligence required 

to make investment decisions, break down barriers to 

commercialization, and bring new high-performance fuels 

and advanced engine systems to market sooner.

DOE’s Office of Energy Efficiency & Renewable Energy 

(EERE) has brought together nine national laboratories—

the National Renewable Energy Laboratory and Argonne, 

Idaho, Lawrence Berkeley, Lawrence Livermore, Los Alamos, Oak Ridge, Pacific Northwest, and Sandia National 

Laboratories—to collaborate on this groundbreaking research. The outcome of this effort will be new tools, data, 

and knowledge to pave the way for future generations of 

fuel and vehicle innovations.

2 | Co-Optima FY16 Year in Review
 Letter from the Leadership Team 

n its first year, the Co-Optima initiative moved from robust concept to concrete results. The two DOE 

offices, nine national laboratories, and industry stakeholders that compose Co-Optima successfully worked 

to integrate fuels and engine R&D, breakdown barriers, and tackle challenges. This report highlights the 

progress made by Co-Optima in fiscal year 2016.

In this inaugural year, our parallel Co-Optima research tracks have focused on fuels and engine technologies 

related to spark-ignition (SI) and advanced compression ignition (ACI) systems. The first phase, Thrust I, has 

concentrated on:

u Improving near-term SI engine efficiency

u Assessing desirable properties for bio-derived or bio-based components (blendstocks) to be blended with 

petroleum-derived gasoline 

u Identifying more than 40 promising blendstock candidates 

u Evaluating the impact of discrete fuel properties on advanced SI engine performance.

Researchers have also initiated R&D on Thrust II ACI combustion strategies focused on achieving higher efficiency with lower levels of harmful emissions than can be achieved today. We evaluated fuel property impacts on 

kinetically controlled and low-temperature combustion (LTC) strategies and began to improve our understanding of how co-optimized fuel properties and engine strategies can contribute to longer-term solutions.

Not only is Co-Optima integrating fuel and engine research efforts, but we’re addressing deployment barriers 

and fostering technological innovation. Co-Optima is also facilitating research collaboration by bringing together some of the nation’s top fuel and engine scientists, engineers, and analysts. With the support of EERE’s Vehicle Technologies and Bioenergy Technologies Offices, we are pursuing a technology-neutral approach. At the 

same time, ongoing dialogue with a wide range of stakeholders ensures that our team is guided by marketplace 

realities and driven to develop technology solutions that will substantially lower market barriers.

We’re encouraged by initial evaluations that indicate technologies and strategies under exploration by 

Co-Optima researchers will have the potential for significant passenger vehicle fuel economy improvements. 

As Thrust I and Thrust II research progresses, our goal—better fuels, better vehicles, sooner—is within reach.

John Farrell

National Renewable Energy 

Laboratory

John Holladay

Pacific Northwest National 

Laboratory

Robert Wagner

Oak Ridge National 

Laboratory

Co-Optima FY16 Year in Review | 3 
Deliver

$30-$40

annually via improved fuel economy

 Big-Picture Targets 

Contribute to national goal of

REDUCTION in transportation 80%GHG EMISSIONS by 2050

Accelerate the SPEED OF DEPLOYMENT

with commercial introduction of NEW FUELS/

TECHNOLOGIES BY 2025

Co-Optima's ultimate goal is to provide U.S. industry with the R&D needed to strengthen energy security and stimulate economic growth 

while reducing harmful emissions from transportation.

2035

INCREASE ENERGY INDEPENDENCE with 

biofuels from domestic feedstocks supplying as much as

15% OF LIQUID FUELS BY

Improve passenger vehicle

FUEL ECONOMY BY

50% 15% beyond the projected

results of existing R&D efforts

Spur the U.S. ECONOMIC GROWTH

with the establishment of

500,000 NEW JOBS

BILLION IN 

COST SAVINGS

4 | Co-Optima FY16 Year in Review
 Dialogue with Stakeholders 

o help ensure the success of this ambitious 

initiative, Co-Optima leaders have established ongoing dialogue with government 

and industry decision makers — through 

“listening day” events and outreach to trade 

associations and other organizations. Representatives from stakeholder groups have been invited to weigh in on key research components and 

priorities, and Co-Optima has built and relies on an 

external advisory board. 

Stakeholders have emphasized the importance 

of identifying concrete value propositions, clearly 

defining project scope, taking an inclusive approach across agencies and levels of government, 

and establishing collaborative dialogue. Because 

of these conversations, Co-Optima is pairing R&D 

efforts with exploration of market realities. This 

dialogue has made it possible to identify research 

needs, potential risks, and mitigation strategies in 

the areas of engine efficiency and performance, 

fuel production and distribution, infrastructure 

compatibility, and retail sales. 

Particularly valuable perspectives have been 

provided by stakeholders on overall market viability, considering the impact of factors including 

economic conditions, investment requirements, 

deployment timelines, government policy, and 

consumer acceptance in their assessment of how 

to best cultivate marketplace acceptance. 

The national labs and EERE recognize that continued exchanges with these partners will be critical 

at each stage of the Co-Optima initiative, and plans 

are already underway to build on this foundation of 

stakeholder engagement. Additional listening day 

and stakeholder events are being scheduled. 

A Funding Opportunity Announcement (FOA) was 

released in FY16 to involve universities in Co-Optima research, and it is anticipated that awards will 

be announced in the first half of 2017.

Key Listening Day Takeaways

Topic Stakeholder Observations

Scoping New 

Horizons for 

Fuels and 

Vehicles

• New fuels have to be drop-in 

compatible with existing distribution 

equipment and vehicles to avert 

costs and complexities of major 

infrastructure changes.

Spark 

Ignition 

Applications 

• Successful co-optimization will rely on 

market certainty, as well as on engine 

and fuel producer cooperation.

• It will be important to explore options 

other than octane, compression 

ratios, and clean LTC. 

Advanced 

Combustion 

Applications 

• There is no low-GHG fuel substitute 

commercially available at the needed 

volumes.

• An optimized system of fuels/engines 

might prove more tractable by 

blending fuels.

Barriers to 

Deployment

• The best approach to overcoming 

barriers combines policy 

with successful technology 

implementation, incentives, consumer 

outreach, and infrastructure 

compatibility.

Stakeholder 

Engagement 

• Buy-in from and market readiness 

of all stakeholders will be vital to 

successful deployment of new fuels 

and engines.

• Representation from consumer 

groups should be expanded.

Co-Optima FY16 Year in Review | 5 

Listening Day Workshop Participation

Number of Attendees per Sector 

5

7

6

4 13

18

5

Government Agencies

Trade/Consumer Groups

Petroleum Industry

National Labs

Staff

Biofuels Industry

Original Equipment 

Manufacturers
Integrated Capabilities in Support of End-to-End Scope

High-Performance Fuels

u Identify promising bio-derived blendstocks

u Develop selection criteria for fuel molecules

u Identify viable production pathways 

Modeling and Simulation Toolkit

u Leverage high-fidelity simulation capabilities

u Extend the range, confidence, and 

applicability of engine experiments

Advanced Engine Development

u Quantify interactions between fuel 

properties, engine design, and 

operating strategies 

u Enable optimal design of efficient, 

emission-compliant engines

Analysis of Sustainability, Scale, 

Economics, Risk, and Trade

u Analyze energy, economic, and 

environmental benefits to the United States 

u Examine routes to feedstock production 

at scale through existing biomass markets

Fuel Properties

u Identify critical properties and 

allowable ranges

u Systematically catalog properties

u Predict fuel blending behavior 

MarketTransformation

u Identify and mitigate challenges 

of moving new fuels and engines 

to market 

u Engage with full range of 

stakeholders 

Co-Optima’s integrated approach merges the previously independent areas of low-carbon fuel and combustion R&D, spanning a diverse 

range of capabilities and expertise. The initiative’s end-to-end scope ranges from basic science research to analysis of deployment factors. Activities that often cut across the key research areas are outlined below. 

6 | Co-Optima FY16 Year in Review
Co-Optimized

Engines

R&D

Fuels

R&D

Co-Optima FY16 Year in Review | 7 
Using the Past to Guide 

Future Success

A detailed examination of previous fuel and 

vehicle introductions and input from stakeholders are providing the Co-Optima team 

with key insights to guide the direction of 

the R&D toward the successful deployment 

of new technologies. A thorough review of 

existing research is exploring the potential 

impact of vehicle distribution patterns, infrastructure compatibility, feedstock supply, 

and laws and incentives. For example, the 

high volume of cellulosic biomass makes 

storage and transportation expensive, but 

previous studies show that processing 

these sustainable, domestically produced 

feedstocks into pellets can make shipping 

and warehousing efficient.

This extensive review of existing research 

also confirmed that compatibility with 

current infrastructure, extensive consumer outreach, and consistent government 

policies will be vital to the success of any 

new fuel and engine introductions. Identification of these possible market barriers and 

mitigation strategies will help industry and 

government decision makers reduce risks 

involved in eventual commercialization.

8 | Co-Optima FY16 Year in Review
 Technical Research Accomplishments & Impact

he petroleum and automotive industries long ago cracked the code on how to design engines and formulate fuels 

that would meet drivers’ performance expectations. But what does it take to maximize the performance, energy 

efficiency, and environmental attributes of the next generation of advanced fuels and engines? Co-Optima research 

is pioneering the comprehensive and coordinated science and engineering needed to deliver on all three fronts.

In the first year of this initiative, the integrated multi-lab team has joined forces across disciplines to simultaneously tackle advanced engine development, fuel property identification, renewable fuels production, simulation tool development, 

life-cycle and techno-economic analyses, and deployment barriers. The Co-Optima team operates according to a central 

fuel hypothesis: If target values for critical fuel properties that maximize efficiency and reduce harmful emissions for a 

given engine architecture are identified, then fuels that have properties with those values (regardless of chemical composition) will provide comparable performance. This fuel property-based approach is making it possible for researchers to 

deliver rigorous technical understanding without favoring a specific technology or approach.

The operating requirements for light-duty, medium-duty, and heavy-duty vehicles can differ widely. Co-Optima’s two 

parallel research thrusts make it possible to address this full spectrum of requirements, while also examining short-term 

and long-term solutions based on SI and ACI strategies.

Highlights on the following pages represent just a selection of the top FY16 Co-Optima accomplishments.

Co-Optima FY16 Year in Review | 9 
Tiered Screening Approach Narrows the Field of Potential 

Fuel Candidates 

Blendstock candidate identification began with a survey of all possible 

hydrocarbons and oxygenates that can be produced from biomass. Researchers then developed and implemented a tiered screening approach 

to rapidly identify candidates that have fuel properties advantageous to 

Thrust I engine operation. The first level ensured the candidates had the 

requisite chemical and physical properties needed to be blended into 

commercial fuels. This yielded more than 40 candidates. The second tier 

involves more detailed property measurements and detailed analyses to 

identify those that have the potential to improve engine efficiency and be 

commercially available by approximately 2025. The third tier then involves 

confirmatory testing and more refined analyses to confirm the potential of 

the blendstock candidates.

ust as the Co-Optima initiative bridges fuel and engine innovation, a body of foundational research spans the two parallel 

thrust areas, providing the scientific underpinnings for R&D on 

multiple fronts.

Perhaps the most important of these foundational elements has been 

the establishment of a central fuel hypothesis that performance in 

engines is linked to fuel properties. This governing hypothesis has 

guided researchers in developing screening criteria, surveying hundreds of bio-derived molecules, and creating a fuel property database containing the chemical and physical properties of more than 

400 petroleum- and bio-derived blendstocks. Researchers have also 

defined a robust engine merit function that defines the relationship 

between key fuel properties and engine efficiency and is being used 

to assess the validity of the central fuel hypothesis through carefully 

designed simulations and engine and reactor experiments.

Other activities crucial to the initiative’s success have included identification of critical life-cycle, market, and techno-economic metrics and the 

analyses of the performance of leading bio-blendstock candidates. In addition, researchers have developed modeling and simulation tools that are 

being used for scenario-based decision analysis and will be essential to 

defining the fuel/engine options that maximize performance while meeting key sustainability, affordability, scalability, and compatibility metrics. 

The following section highlights research that provides a foundation for 

Co-Optima Thrust I and Thrust II activities.

Tier 1: High-level Screening

Tier 2: Candidate Selection

Tier 3: Candidate Evaluation

Number of

Candidates

5

Hundreds

Quantity of

Fuel Required

Gallons

One Liter

None

40

 Building the Foundation 

The tiered screening approach began with a high-level screening for suitable 

chemical properties, followed by detailed candidate selection, which has yielded 

promising candidates for engine tests.

Engine and Fuels Central Hypothesis

If target values for critical fuel properties that maximize efficiency and 

reduce harmful emissions for a given engine architecture are identified, 

then fuels that have properties with those values (regardless of chemical composition) will provide comparable performance.

10 | Co-Optima FY16 Year in Review
Assessment of Fuel-Enabled Efficiency Gains 

Embodied in “Merit Function” 

To assist in evaluating promising fuel blendstock candidates, a Thrust I fuel efficiency “merit function” has 

been developed that estimates the potential gains in 

engine efficiency associated with changes in key fuel 

properties. Combined with an assessment of the GHG 

impacts from the production of the blendstocks, the 

merit function allows a semiquantitative assessment 

of the overall GHG reduction potential of various fuel 

blendstock candidates. Although the function reflects 

the current knowledge of fuel effects on efficiency, 

ongoing work within the Co-Optima effort is aimed 

at refining this knowledge, as well as extending the 

knowledge through high-fidelity simulations.

Analysis Assesses the Benefits of Proposed Fuels and Engines 

Harnessing a suite of models—including techno-economic, life-cycle, vehicle fleet simulation, biofuel 

production simulation, and economic impact models—a team of Co-Optima analysts assessed the 

potential of Thrust I and Thrust II engines and fuels to reduce GHG emissions and fossil-energy consumption in the light-duty sector through 2050. Carried out at the outset of Co-Optima, the analysis 

estimated a 3%–14% reduction in GHG emissions from the light-duty fleet. The benefits analyses 

will be expanded and refined during the second year of Co-Optima as more information becomes 

available regarding the identity and performance of the proposed fuels. Also, the vehicle deployment 

scenarios will be refined with stakeholder inputs and the scenario expanded to include Thrust II 

medium- and heavy-duty vehicles.

ASSERT Models: Benefits Analysis

( 2.0)[0.67 0.5( 2.0)]

3

( 46[ / ])

130

( 415[ / ])

1.6

0.01[ / / ]( 415[ / ])

1.6

( 8)

1.6

( 91)

− 150 − − + −

− +

− + − +

− − − =

LFV H PMI PMI

S cm s

ON kJ kg HoV kJ kg HoV kJ kg

S K RON Merit L mix

mix mix

mix mix

Σ

Distillation Particulate Emissions

Heat of Vaporization

RON Flame Speed

Octane

Sensitivity

The merit function captures the impact of major fuel properties 

on the efficiency of an advanced SI engine. 

As shown here, a complex suite of models was 

used to examine the impacts of proposed CoOptima fuels and engines, including such impacts 

as GHG emissions, fossil-fuel consumption, and 

job creation.

ADOPT BSM

How will the biofuels

industry grow?

JEDI

GREET

What are the GHG 

emissions and energy

intensity of 

various fuels?

Feedback between Thrust I fuel price and

impact on sales of next year’s Thrust I/II vehicles

Volume of fuel

consumed by type

How much Thrust I/II

vs. conventional fuel

is consumed?

How will the

fuel market 

evolve over time?

Life-cycle fossil energy consumption

and GHG emission intensities of various

Thrust I/II and conventional fuel pathways

How many biorefineries

need to be constructed

to meet demand?

What feedstock

growth is required

to meet demand?

Vehicle fleet

composition

(including

Thrust I/II)

Total annual petroleum

consumption and GHG emissions 

from the light-duty vehicle sector in 

each Co-Optima scenario

Gross jobs benefit

vs. time associated 

with Thrust I/II

deployment

Bioeconomy

AGE

What are the energy 

and environmental 

impacts of the 

biofuels industry?

How many vehicles

are sold (by type) 

based on consumer 

choice?

What are the 

economic impacts 

from biofuel

plant construction?

Key

material TEA flows

What is the potential

economic viability of

a research process?

Yields and cost for biofuels

production (from TEA)

Co-Optima FY16 Year in Review | 11 
Model Predicts Octane Numbers for Blended Fuels with 

Bio-Derived Components 

Fuels are generally characterized by important combustion metrics such as 

RON, MON, and flame speed, but predicting these values for fuel mixtures 

is difficult because of complex chemical–kinetic interactions that cause 

non-linear behavior. To address this issue, the Co-Optima team is developing 

a chemical kinetic model that can predict RON, MON, and flame speed and 

can model the complex behavior of these mixtures in SI engines. Accurate, 

validated kinetic mechanisms such as these are critical for developing insight into how fuel properties impact combustion and as inputs to highfidelity combustion simulations. These results will guide efforts to discover 

promising bio-derived fuel and gasoline blends that provide the desired 

ignition and flame speed properties under advanced SI engine conditions.

A newly developed chemical model can predict the RON and MON for blends of 

gasoline and bio-derived fuels. The predicted RON for ethanol blends is shown 

here. PRFx are primary reference fuels. 

Ethanol Volume Fraction (%)

Data

Simulations

PRF100

PRF60

PRF0

0

0 20 40 60 80 100

20

40

60

80

100

Research Octane Number (RON)

Database Is Developed for Bio-Derived Fuel Blendstocks 

and Their Gasoline Blends 

A publicly accessible Fuel Property Database has been created and 

populated with fuel and chemical property information for candidate 

bio-based fuel blendstocks. The database focuses on fuel blendstocks 

(both pure components and mixtures) proposed by the Co-Optima team 

and is populated with data from literature or measured, and/or predicted 

data. It currently contains data on nearly 400 bio-based fuel blendstocks. 

In early FY17, the database will be expanded to include data on blends of 

the most promising Thrust I blendstocks with both a gasoline designed for 

such blending a reformulated blendstock for oxygenate blending (RBOB) 

and a four-component surrogate for RBOB that allows for determining the 

research octane number (RON) and motor octane number (MON)

The Fuel Property Database includes data on 382 bio-based fuel blendstocks—such 

as 2-butanol, shown here—and on blends of the most promising Thrust I blendstocks.

12 | Co-Optima FY16 Year in Review
Machine Learning Tool Classifies Fuel Properties in 

Blendstock Evaluation

Co-Optima researchers developed an open source and general-purpose 

machine learning tool for classifying fuel properties of biologically produced 

chemicals. This allows synthetic fuel biologists, chemists, and fuel researchers to rapidly classify, screen, and rank compounds based on their desired 

fuel properties. Because measuring properties like RON can be intractable 

for large numbers of chemicals, this tool can dramatically decrease the work 

in triaging chemicals for experimental validation, potentially leading to new 

components for fuel blends. In a direct experimental test of this software, using measured RON, the classification predictions provided meaningful leads.

Co-Optimizer Software Solves Merit Function 

for Fuel Blendstocks

Identifying co-optimized solutions requires assessing the tradeoffs 

between a number of complex parameters — engine efficiency, environmental performance, infrastructure compatibility, etc. To address 

this in a systematic manner, a modeling approach has been developed 

that optimizes fuel component blending to maximize engine efficiency (as defined by the merit function). Users can specify constraints on 

each of the 21 metrics identified to assess environmental, economic, 

and infrastructure attributes of the blendstocks in the fuel property 

database. This type of optimization problem constitutes a difficult-to-solve, mixed-integer, non-linear programming problem. The 

team has turned to genetic algorithms to generate solutions efficiently and is exploring surrogate optimization to allow complicated blending models that still achieve interactive levels of performance. The 

team is examining the tradeoff between engine merit function and 

cost and exploring the impact of a number of factors to understand 

how potential biofuel blendstocks impact engine performance.

Regression of experimentally measured RON by probability in high RON class (RON 

> 94.4) for validation compounds. A linear regression of classification probability of 

RON > 94.4 by experimentally measured RON has an r 2 = 0.653 (P < 0.001). Based 

on this relationship, all 16 compounds are correctly classified, with one compound 

falling away from the 95% confidence intervals of classification (this compound is 

shown in the horizontal shaded area). 

0.6

0.8

1.0

80 100 120

Prediction Probability RON > 94.4 0.6

0.8

1.0

80 100 120

} Marginal

Region

94.4

High

Confidence

Region

High

Confidence

Region

Experimentally Measured RON

}

}

Co-Optima FY16 Year in Review | 13 
New Tool Automatically Generates Physically 

Accurate Surrogate Fuel Mixtures 

Co-Optima engineers have developed a tool that quickly generates surrogate fuel mixtures to match key physical and kinetic properties of current 

and proposed fuels, a necessary input into fuel and engine simulations. The 

“surrogate generator” automates a painstaking process that could only match 

a few physical properties for one fuel. It employs a fast chemical–kinetic 

solution method to calculate the fuel’s ignition characteristics, combining that 

with molecular composition and distillation data to produce better matches to 

more data in minutes. Using the tool on a supercomputer, it can run in parallel 

to investigate a wide array of model fuel surrogates.

Parallel-Cycle Simulations Yield Fuel Velocity Statistics in Bulk 

The Co-Optima project has simulated 35 motor engine cycles using a parallel-cycle approach for a pent-roof optical engine. This is the first time this kind 

of approach has been applied to an engine with non-simplified combustion 

chamber geometry. With this method, each engine cycle is simulated in parallel 

rather than sequentially, potentially saving an order of magnitude or more time 

to complete the simulations. The results show reasonable agreement between 

particle image velocimetry measurements and simulation results and provide a 

solid foundation to build upon for simulations of combustion engine cycles. 

This flow chart demonstrates how the surrogate generator tool iteratively solves for 

the surrogate fuel mixture (vector v of component volume fractions) that has the 

“best” match to the experimentally measured properties for the real fuel.

Comparison of fuel velocity mean and standard deviation data along the x-axis 

through the spark gap. 

14 | Co-Optima FY16 Year in Review
Spray Chamber Simulates Engine Temperatures 

and Pressures 

Co-Optima engineers have designed a spray chamber that will 

recreate the typical conditions for either gasoline or diesel injection while offering optical access for research needs. The design 

involved extensive finite element and thermal analysis to achieve 

an optimal design for the 

chamber’s optical, thermal, 

and strength performance. 

When fabricated and 

installed, the chamber will 

offer a continuous flow of 

charge gas at temperature 

and pressure, allowing fuel 

effects on spray development to be investigated with 

up to a 300-fold increase in 

productivity.

Microliter Fuel Ignition Tester Detects Octane Number Dependence

Co-Optima and Louisiana State University have developed a prototype microliter Fuel 

Ignition Tester (μFIT), in which premixed fuel and air flow down a small-diameter quartz 

tube that is externally heated, creating a positive temperature gradient down the length 

of the tube. This geometry allows a number of steady and unsteady flame dynamics to 

be established and studied with μFIT, varying the flow velocity, fuel reactivity, fuel-air 

ratio, and temperature gradient. With a fueling rate of roughly a microliter per minute, 

μFIT can potentially perform rapid fuel screening with sub-microliter samples, providing 

estimates to the fuel property inputs needed for the engine merit functions. In addition, 

detailed thermal modeling eliminated a major source of temperature error in the μFIT 

system, which is enabling a redesign of the equipment and procedures to make the measurements suitable for more quantitative comparisons.

Flame ignition (red) and extinction (blue) positions at different flow speeds in the 

μFIT prototype. The flames become unstable at low flow velocities, entering a mode of 

repetitive extinction and ignition. In a single cycle, these dynamics provide insight into 

high-temperature chemical kinetics at the ignition point, low-temperature kinetics at the 

extinction point, and laminar flame speed. The octane number of the two components and 

their mixture was found to have a nearly linear correlation to the wall temperature at the 

point of flame extinction across both stable and unstable flame regimes. 

The predicted gas temperature distribution in the spray chamber while 

pressurized shows that the high-temperature gases at 1,100 K (red) are 

isolated from chamber walls, which remain at 400 K (blue) to maintain 

the integrity of the pressure vessel.

Co-Optima FY16 Year in Review | 15 
 Thrust I: Spark Ignition

park ignition (SI) engines found in most of today's 

light duty vehicles use less fuel and produce fewer 

polluting emissions than cars did 20 years ago, but 

further advances to these engines and the fuels that 

power them are needed to maximize efficiency and vehicle 

performance while reducing harmful emissions. Co-Optima 

Thrust I activities have focused on identifying fuel properties 

that can enable market introduction of downsized, turbocharged SI engines in the 2025 timeframe. More specifically, 

researchers are mapping the relationships between production pathways, molecular structure, fuel chemical/physical 

properties, and engine performance. 

Researchers identified more than 400 blendstock candidates 

that can be produced via biological or fossil pathways and 

applied a tiered screening approach to eliminate candidates 

that had properties unsuitable for use in commercial fuels. 

This evaluation resulted in identification of more than 40 

molecules/mixtures with properties suitable for Thrust I 

fuel blendstocks. Researchers continue to refine this list to 

pinpoint those with properties with the greatest potential to 

enhance SI engine performance. 

These assessments are being guided by analyses of 20 

representative molecules/mixtures across 21 metrics related 

to sustainability, economics, scalability, and market viability. 

Experiments and modeling have provided crucial insights that 

have improved the understanding of fuel property impacts on 

SI engine performance.

The following section highlights select Co-Optima Thrust I 

accomplishments.

Assessment Identifies More Than 40 Bio-Derived 

Materials as Potential Blendstocks 

Co-Optima researchers performed the first systematic assessment of the suitability of oxygenate functional groups in fuel blends for SI engines. The team used a multistep approach 

that assessed a broad range of chemical functionalities, eliminating those with poor fuel 

characteristics. This approach allowed the team to identify more than 400 potential blendstocks within the remaining functional groups that can be derived from biomass, including 

individual molecules and mixtures. The team then applied a tiered screening approach to 

determine which have a high likelihood of meeting fuel property metrics. Ultimately, the 

team identified 39 blendstocks with a RON greater than 98 that met Tier 1 screening metrics. The blendstocks were then subjected to further performance and property testing.

The team evaluated the full range of potential bio-derived chemistries, evaluated functional 

groups that could potentially be fuels, and then identified nearly 400 candidates for 

further testing. Ultimately, more than 40 compounds and mixtures met the Tier 1 screening 

requirements and were targeted for additional research.

16 | Co-Optima FY16 Year in Review
Metric Favorable Neutral Unfavorable

Example 1:

Target cost ($/gge)

Falls in lowestcost grouping of 

blendstocks

Falls in middlecost grouping of 

blendstocks

Falls in highestcost grouping of 

blendstocks

Example 2:

Life-cycle GHG 

emissions

Likely to achieve 

a greater than 

60% reduction 

in life-cycle 

GHG emissions 

as compared 

to conventional 

gasoline in 2015.

Could achieve 

a greater than 

60% reduction 

in life-cycle 

GHG emissions 

as compared 

to conventional 

gasoline in 2015.

Unlikely to achieve 

a greater than 

60% reduction 

in life-cycle 

GHG emissions 

as compared 

to conventional 

gasoline in 2015.

Analysis Evaluates 20 Thrust I Candidate Blendstocks 

Co-Optima analysts developed 21 metrics in the categories of process economics, technology readiness, sustainability, and market barriers against which to 

evaluate a subset of 20 promising Thrust I candidate blendstocks with a RON 

exceeding 98. These metrics include the target cost and state of technology for 

blendstock production, as well as life-cycle GHG emissions. Such metrics are 

key to further assessing the viability of candidate blendstocks that meet the 

required physical properties. Blendstock candidates were assessed at the close 

of Co-Optima’s first year. Five candidates were identified for more rigorous 

analyses in the project’s second year.

Compatibility Issues Examined in Analysis of 

32 Blendstocks, Six Elastomers 

Co-Optima researchers have examined the compatibility of 32 fuel candidate blendstocks with six elastomers, using a theoretical chemical method 

called the Hansen solubility analysis. The blendstocks were evaluated for 

blends with dodecane (representing gasoline) and E10D (representing 10% 

ethanol blends), and the results show that the blend level has a significant 

impact on compatibility. For many candidates, the solubility potential (or 

potential swelling) increases with higher blendstock content and peaks at 

low- to mid-range concentrations. For many elastomers, the solubility is 

within an acceptable range, but experimental testing will be undertaken in 

FY17 to confirm their compatibility.

Two examples of the 21 metrics for blendstocks—target cost and life-cycle GHG emissions

—and the criteria used to rank them as “favorable,” “neutral,” and “unfavorable.”

Solubility analysis results for pentanoic acid and methyl ester demonstrate 

that blend levels can have a significant impact on solubility, although for many 

elastomers, the solubility is within an acceptable range.

Co-Optima FY16 Year in Review | 17 
Higher Fuel Laminar Flame Speed Expands Dilute 

or Lean Operation 

Five fuel blends (all based on pure components) were designed to test the 

effect of laminar flame speed (LFS) on the lean and exhaust-gas recirculation (EGR) dilution limits of SI combustion with various constant heats 

of vaporization (HoV). While having a low HoV is important for stable 

combustion, the higher LFS is also important because it allows for leaner 

mixtures or increased EGR dilution even while the HoV is high. Compared 

to typical engine design parameters (spark energy, tumble ratio, and direct 

injection (DI), fuel LFS had similar impacts on lean and EGR-dilute SI combustion limits. 

Increased fuel LFS allowed higher EGR dilution and lean tolerance, resulting in 

improved engine indicated thermal efficiency. Fuel LFS effects were as significant 

as changes to key engine design parameters.

High-Octane Blends Improve Fuel Efficiency 

in Aggressively Tuned Engines 

At a compression ratio of 12:1, use of 98 RON fuels (including E20) yields 

significant fuel efficiency improvements relative to 92 RON fuel, offering 

the possibility of fuel economy parity with E10 fuels for some driving 

cycles. The benefit of octane increases with the aggressiveness of the 

driving cycle due to the higher fraction of time spent in knock-limited 

combustion phasing conditions. Higher RONs reduce the need to retard 

combustion phasing under these conditions, improving fuel efficiency. 

Engine downsizing and down-speeding are well suited to take advantage 

of higher-octane fuels because these engines encounter the knock limit 

more frequently. 

E10-equivalent fuel economy results for the three study fuels at a compression ratio 

of 12:1 show fuel economy benefits for fuels with higher RONs.

18 | Co-Optima FY16 Year in Review
Kinetic Simulation Provides Insight to Pre-Spark Heat Release 

Co-Optima is successfully applying chemical–kinetic modeling to provide 

insight into the regions of reactivity and how that relates to different fuels. Experimental temperature and pressure traces combined with kinetic simulations 

of autoignition chemistry are demonstrating how boosted operating conditions interact with regions of enhanced reactivity at highly boosted conditions. 

Specifically, pre-spark heat release is observed in stoichiometric SI engines 

with some fuels at conditions that are important for Thrust I technologies. This 

method can provide insight into Co-Optima paths for fuel compositions and 

operating conditions as the project moves forward.

An island of low temperature heat release (LTHR) was identified in the pressure/ 

temperature space using kinetic simulations and is presented using the contour 

plots above. The lines depict the compressive process in the temperature/pressure 

space for different operating conditions. The investigation found that the highest 

load condition (Condition C, green) is the only operating condition that interacts 

with the LTHR island and, as a result, is the only operating condition to exhibit prespark heat release.

Boost Can Cause Pre-Spark Heat Release in SI Engines 

Operation under boosted conditions is essential to Co-Optima’s Thrust I 

effort to maintain acceptable power density for downsized and downsped 

SI engines. However, boosted engines encounter temperature and pressure conditions that are not seen in naturally aspirated engines, which 

constitute the majority of today's SI engines. These boost conditions are 

also well outside the range experienced in either the RON or MON tests. 

Investigations revealed that with sufficient boost, some fuels exhibit heat 

release prior to SI. This behavior may have far-reaching implications on understanding the boundary conditions for engine knock and other abnormal 

combustion phenomena.

Pre-spark heat release 

development as the intake 

temperature is increased 

with iso-octane under 

boosted conditions in a 

stoichiometric SI engine. 

Co-Optima FY16 Year in Review | 19 
HoV Contributes to Octane Sensitivity 

Increasing the latent HoV of gasoline blendstocks has the potential to 

increase fuel knock resistance in DI engines. However, studies that fix the 

octane sensitivity find that HoV does not produce an additional anti-knock 

benefit. Two new studies were performed to further investigate the relationship between HoV and octane sensitivity. One study found similar 

combustion phasing under knock-limited spark advance (KLSA) conditions 

for three similar fuels with differing HoVs, while a second study found that 

KLSA is well correlated with the RON. The study results indicate that HoV 

anti-knock effects can be viewed as a contributor to octane sensitivity.

Fuel HoV Influences the Knock Limit 

at High Intake Temperatures 

The RON and octane sensitivity of a fuel are closely associated with its 

knock resistance, but recent research has found that the fuel’s HoV plays 

a role at high intake air temperatures. Research with a single-cylinder, 

gasoline DISI engine at a fixed retarded combustion phasing and intake air 

temperatures higher than 60°C found that fuels with higher HoV values 

enabled operation at significantly higher load. This important Co-Optima 

research decouples the physical HoV effect from the RON and octane 

sensitivity effects, and for the first time, demonstrates engine operating 

conditions where HoV effects on knock resistance can be measured.

Knock-limited loads at late combustion phasing (CA50 = 20.5° ATDC) are shown 

with 100 RON fuels. At higher intake air temperatures, fuels with higher HoVs allow 

higher loads to be achieved.

Chemical and thermal components of octane sensitivity derived from Foong’s work 

at the University of Melbourne shows that the HoV contributes to octane sensitivity 

at high concentrations of ethanol.

20 | Co-Optima FY16 Year in Review
Particulate Matter from Ethanol Blends Has Lower 

Activation Energy than from Gasoline 

Co-Optima has determined that Thrust I fuel blends will likely influence particulate matter (PM) oxidation behavior in the absence of an aftertreatment 

solution, which could have regulatory implications. Gasoline particulate filter 

(GPF) cores were exposed to exhaust from a DI engine running on either 

100% gasoline (E0) or a 30% blend of ethanol in gasoline (E30). Subsequent 

measurements were done with neutron imaging. As shown below, it was 

determined that the thickness of the PM soot cake did not change until 20% 

of the carbon had been removed with little difference between fuels. While 

the E30 PM was easier to oxidize, both the E0 and E30 PM oxidize differently 

than diesel PM.

Studies with GPF cores show the presence of organic fraction, increasing the 

activation energy for oxidation.

Possible Link Found Between Particulate 

Matter and Ethanol’s Interaction with Aromatics 

Co-Optima researchers characterizing a set of 15 gasoline blends made 

the unanticipated discovery that ethanol suppresses aromatic evaporation 

and pushes it to higher temperatures. Incomplete fuel vaporization and 

mixing produces higher PM emissions—especially for aromatic compounds 

with a high sooting tendency. E15 or E30 blends inhibited evaporation of 

the aromatic at the midpoint of the distillation curve, causing the fuel to 

be enriched with the aromatic toward the end of the distillation. In ongoing work, the Co-Optima project is testing these fuels in a DISI engine to 

measure PM emissions.

Distillate composition results for 10% by volume blends of p-cymene in E0, E15, 

and E30 demonstrate a suppressed aromatic distillation until a large fraction of the 

ethanol has evaporated.

Higher ethanol levels suppress 

aromatic distillation until virtually 

all the ethanol has evaporated

Co-Optima FY16 Year in Review | 21 
Committee Tackles Standards for Electronic Misfueling 

Mitigation Technologies 

When vehicles designed for new fuels are accidentally fueled with incompatible legacy fuels, or vice versa, it can result in serious vehicle performance issues and potentially irreparable damage. Misfueling mitigation 

strategies can prevent these mistakes. Of all available techniques, electronic misfueling mitigation technologies that would enable wireless communication between the vehicle and the dispenser appear most effective. Yet 

such an approach would require the development of new technical standards. Input from automotive and fuel retailing stakeholders has underscored the need for such a standard and an investigation of related factors. 

The Co-Optima program plans to assemble a committee to accelerate the 

establishment of needed mitigation strategies. 

Fuel-grade guidance labels, whether inside the filler door or on the pump, are less 

effective than mechanical or electronic means of preventing misfueling. For CoOptima fuels, more foolproof strategies are needed.

Imaging Reveals Mechanism for 

Smoke Emissions at Higher Engine Speeds 

Spray-guided stratified-charge operation of SI engines is one approach to 

lean operation, which yields higher efficiency. However, fuel stratification 

may lead to excessive smoke emissions. Co-Optima researchers employed 

several optical diagnostics in a DISI engine that used in-cylinder swirl to stabilize the combustion at higher speeds. A new high-speed infrared fuel-vapor imaging technique demonstrated that tumble flows are generated in 

conjunction with the swirl and create asymmetric fuel distributions, leading 

to excessively rich gas volumes that promote soot formation. This research 

may lead to clean and efficient stratified-charge SI engine operation and 

guide the formulation of new high-octane gasoline fuels.

Infrared fuel-vapor images during gasoline fuel injection (a) and at the time of 

the main combustion phase (b). Green and blue contours correspond to dilute 

and dense liquid boundaries detected by a separate Mie-scattering technique. 

The last image (c) shows an example of soot luminosity caused by tumbleinduced fuel-vapor asymmetry.

22 | Co-Optima FY16 Year in Review
Under mixing-controlled combustion of a free spray vs. DFI, the natural luminosity (NL) image in the top row 

shows an absence of hot soot with DFI, which is supported by the absence of any soot in the corresponding 

diffuse back illumination (DBI) image in the bottom row. The OH* chemiluminescence (CL) images in the 

middle row show that there is indeed robust combustion with DFI, and the time-resolved lift-off length, H, is 

determined from these images (upper right plot). The plot in the lower right corner shows that the total soot 

mass as determined by DBI is 5 to >100 times lower with DFI relative to the free spray.

 Thrust II: Advanced Compression Ignition

ven if the performance of SI engines 

is taken to the limit, greater efficiency improvements can be realized 

through commercialization of ACI 

technologies. Co-Optima Thrust II research 

efforts are exploring the factors important 

for enabling ACI technologies, along with the 

supporting fuel technologies necessary to 

produce a higher-impact series of solutions. 

Engine and fuels performance researchers 

have been working hand-in-hand to identify 

fuel properties that critically impact kinetically controlled combustion and LTC. In 

addition, they are mapping the interplay of 

molecular structure, fuel properties, engine 

design, and operating strategies needed to 

enable high-efficiency ACI engine operation 

across a broad range of applications. Researchers are using Thrust II engine simulations with detailed combustion kinetics to 

assess fuel property effects in conditions beyond the range possible with Thrust I engine 

experiments. 

The following highlights provide more detail 

on these Thrust II accomplishments.

Ducted Fuel Injection Reduces Soot from Mixing-Controlled Combustion 

The Co-Optima project employed constant-volume combustion-vessel experiments to measure soot 

reductions enabled by a variety of ducted fuel injection (DFI) configurations studied over a range of 

ambient temperatures (850 K–1,200 K), densities (14.8 and 22.8 kg/m3), and oxygen mole fractions 

(15% and 21%). Soot was typically reduced by half to more than two orders of magnitude, depending 

on ambient conditions and duct configuration. DFI could be a key Co-Optima technology because 

it is an effective, simple, mechanical approach that is not highly sensitive to the use of dilution for 

control of nitrogen oxides (NOx) or to fuels having significant variability in their properties. This 

discovery has particularly important implications to compression ignition engine technologies, which 

are efficient but have sooting challenges.

Co-Optima FY16 Year in Review | 23 
In-Cylinder Fuel Stratification 

Is Key to Classifying 

Advanced Combustion Modes 

Co-Optima researchers have developed a new perspective on ACI 

combustion strategies by classifying 

them along a spectrum that features 

increasing degrees of air and fuel 

stratification at the start of combustion. This new perspective unites how 

all of these previously thought “individual” combustion modes relate to 

one another along this spectrum. This 

perspective of investigating low-temperature combustion on a continuum 

of in-cylinder stratification is critical 

to informing new research efforts focused on achieving potential efficiency gains and emissions reductions 

with these related modes, perhaps 

offering researchers more flexibility in 

expanding ACI to cover wider engine 

operating load ranges.

ACI combustion strategies are shown as a continuum based on the level of fuel stratification at ignition, with gasoline compression-ignition 

modes on the bottom and advanced diesel and dual-fuel ACI modes on the top.

24 | Co-Optima FY16 Year in Review
Study Finds Engine Designs that 

Promote Stratification Can Yield 

Reliable Autoignition 

Co-Optima engineers tested two fuels with 

different anti-knock properties—one similar 

to E10 and the other similar to a naphtha 

distillate—finding that the boost level had 

the most significant impact on autoignition, 

while stratification was just as important as 

the fuel choice. The results will help develop clean, efficient engines that can burn fuels with variations at the pump. Knowledge 

of such fuel properties will allow future engines to employ injection parameters, EGR, 

and boost to create reliable autoignition.

Infrared Combustion Imaging Aims to Extend RCCI 

Load Limits 

The Co-Optima project is employing infrared imaging to improve the understanding of in-cylinder mixing and fuel-property effects on ignition and combustion 

processes in reactivity-controlled compression ignition (RCCI) combustion. RCCI 

experiments are being coordinated between two laboratories with overlapping 

sets of operating conditions that vary premixed-fuel fraction and DI timing. The 

infrared images show how different in-cylinder fuel distributions correlate to 

different pressure-rise rates, which currently limit high-load operation of RCCI 

engines. These imaging results provide guidance for targeting specific operating 

conditions for more detailed and quantitative laser-based fuel-tracer fluorescence 

diagnostics to measure fuel concentration and temperature in FY17.

Fuel property results at 2,000 rpm/

lambda=3, testing the influence of injection 

pressure (P), start of injection (S), boost 

(B), and fuel (F) upon three main groups 

of effects: Crank angles of 10%, 50%, and 

90% (CA10, CA50, and CA90, respectively); 

indicated mean effective pressure (IMEP), 

the coefficient of variation (COV) in IMEP, 

noise, and brake-specific fuel consumption 

(BSFC); and emissions of nitrous oxides 

(NOx), hydrocarbons (HC), and carbon 

monoxide (CO). The y-axis shows the 

relative significance of each factor compared 

to the other factors. Longer bars signify 

more influence of that parameter upon the 

measurement listed, while shorter bars mean 

the factor has little or no influence upon the 

measured parameter.

Infrared images of thermal emissions from hot in-cylinder fuel and combustion 

products for three different modes of RCCI combustion: (a) early injection timing, 

with distributed ignition and modest pressure rise-rates; (b) intermediate injection 

timing, with localized (mixture preparation controlled) ignition and high pressurerise rates; and (c) late injection timing, with jet-mixing-controlled combustion 

similar to conventional diesel combustion and modest pressure-rise rates.

Co-Optima FY16 Year in Review | 25 
 Next Steps

he Co-Optima team is looking forward to significant developments in the year 

ahead. The team plans to assess the validity of the central fuel hypothesis by 

the project’s 18-month mark. It is anticipated that at least three bio-based candidates will have passed screening as potential Thrust I blend components and 

demonstrated engine performance comparable to that of a petroleum-derived fuel. 

At that time, Thrust I blendstock discovery efforts will be considered complete, and a 

decision will be made to determine the relative research priorities needed to accelerate delivery of Thrust I fuels and advanced engines to the market. This decision point 

will involve an end-to-end scenario-based analysis defined through engagement and 

discussions with stakeholders. 

Work on Thrust II ACI R&D will press forward, with experiments, simulations, and 

analyses planned to identify how fuel properties and ACI operating strategies can 

be co-optimized to achieve the high efficiency and low-emissions potential of these 

combustion approaches. Thrust II R&D will be enhanced through new collaborations 

with the nation’s top universities. Eight university teams will work with Co-Optima 

researchers to carry out fundamental studies to complement the work being done 

at the national labs.

26 | Co-Optima FY16 Year in Review
 Publications

Big-Picture Issues Confronting Co-Optima — J. Farrell. Sustainable Transportation Summit, July 2016, Washington, D.C.

www.nrel.gov/docs/fy16osti/66904.pdf 

BioCompoundML: A General Biofuel Property Screening Tool for Biological 

Molecules using Random Forest Classifiers — L.S. Whitmore, R.W. Davis, R.L. 

McCormick, J.M. Gladden, B.A. Simmons, A. George, and C.M. Hudson. Energy & 

Fuels, 30: 8410-8418, 2016.

pubs.acs.org/doi/pdf/10.1021/acs.energyfuels.6b01952

Chemical Kinetics of Octane Sensitivity in a Spark-Ignition Engine — C.K. Westbrook, M. Mehl, W.J. Pitz, and M. Sjöberg. Combustion and Flame, 2016. 

www.sciencedirect.com/science/article/pii/S0010218016301146

Combined Effects of Fuel and Dilution Type on Efficiency Gains of Lean WellMixed DISI Engine Operation with Enhanced Ignition and Intake Heating for Enabling Mixed-Mode Combustion — M. Sjöberg and W. Zeng. SAE Int. J. Engines, 

9:750-767, 2016.

saemobilus.sae.org/content/2016-01-0689

Co-Optima Simulation Toolkit Team — M. McNenly, S. Som, D. Carrington, K. D. 

Edwards, R. Grout, J. Kodavasal, G. Lacaze, J. Oefelein, P. Pal, V. Ram, N. Van Dam, 

J. Waters, and R. Whitesides. DOE 2016 Annual Merit Review and Peer Evaluation 

Meeting for the Vehicles Technologies Office, Washington, DC, June 5-9, 2016.

www.energy.gov/sites/prod/files/2016/07/f33/ft040_mcnenly_som_toolkit%20_

simulation_2016.pdf 

Co-Optima Stakeholder Listening Day Summary Report — D. Longman. 2016.

www.energy.gov/sites/prod/files/2016/04/f30/co-optima_listening_day_summary_report_0.pdf

Co-Optimization of Fuels and Engines — J. Farrell. M-PACT 2016, Indianapolis, 

Indiana, March 2016.

www.nrel.gov/docs/fy16osti/66567.pdf

Co-Optimization of Fuels and Engines — J. Farrell, SAE High Efficiency Internal 

Combustion Engine Symposium, Detroit, Michigan, April 11, 2016.

www.nrel.gov/docs/fy16osti/66333.pdf 

Co-Optimization of Fuels and Engines FOA: National Lab Project Overview 

Webinar Presentations — Hosted by the EERE Bioenergy Technologies Office, 

September 14, 2015.

Co-Optimization of Fuels & Engines (Co-Optima) Overview — J. Farrell, J. Holladay, 

A. Pontau, and R. Wagner. DOE 2016 Annual Merit Review and Peer Evaluation Meeting for the Vehicles Technologies Office, Washington, DC, June 5-9, 2016.

www.energy.gov/sites/prod/files/2016/07/f33/ft037_farrell_co-optima_overview_2016.pdf

Co-Optimization of Fuels & Engines for Tomorrow’s Energy-Efficient Vehicles. 

Fact sheet, March 2016.

www.nrel.gov/docs/fy16osti/66146.pdf 

Effects of Fuel Composition on EGR Dilution Tolerance in Spark Ignited Engines 

— J.P. Szybist and D. Splitter. SAE Int. J. Engines, 9:819-831, 2016.

papers.sae.org/2016-01-0715/

The Effect of Functional Groups in Bio-Derived Fuel Candidates — R.W. Jenkins, 

C.D. Moore, T.A. Semelsberger, D.J. Chuck, J.C. Gordon, and A.D. Sutton. ChemSusChem, 9: 922, 2016.

onlinelibrary.wiley.com/doi/10.1002/cssc.201600552/full

Effects of Iso-octane/Ethanol Blend Ratios on the Observance of Negative Temperature Coefficient Behavior within the Ignition Quality Tester — G.E. Bogin, Jr., 

J. Luecke, M.A. Ratcliff, E. Osecky, and B.T. Zigler. Fuel 186:82-90, 2016

www.sciencedirect.com/science/article/pii/S0016236116307578

Co-Optima FY16 Year in Review | 27 
Elucidating Reactivity Regimes in Cyclopentane Oxidation: Jet Stirred Reactor 

Experiments, Computational Chemistry, and Kinetic Modeling — M.J. Al Rashidi, S. Thion C. Togbé, G. Dayma, M. Mehl, P. Dagaut, W.J. Pitz, J. Zádoe, and S.M. 

Sarathy. Proceedings of the Combustion Institute, In press, 2016.

www.sciencedirect.com/science/article/pii/S1540748916300360

Exploring the Relationship Between Octane Sensitivity and Heat-of-Vaporization 

— R. McCormick, M. Ratcliff, and B.T. Zigler. SAE Int. J. Fuel Lubr., 9:80-90, 2016.

papers.sae.org/2016-01-0836/

Fuel Properties and Chemical Kinetics — R.L. McCormick, G. Fioroni, J. Szybist, T. 

Bays, P. Miles, M. McNenly, B. Pitz, J. Luecke, M. Ratcliff, B. Zigler, S. Goldsborough. 

DOE 2016 Annual Merit Review and Peer Evaluation Meeting for the Vehicles 

Technologies Office, Washington, DC, June 5-9, 2016.

www.energy.gov/sites/prod/files/2016/07/f33/ft038_mccormick_szybist_fuel_

properties_2016.pdf

Investigation of Iso-octane Ignition and Validation of a Multizone Modeling 

Method in an Ignition Quality Tester — E.M. Osecky, G.E. Bogin, Jr., S.M. Villano, 

M.A. Ratcliff, J. Luecke, B.T. Zigler, and A.M. Dean. Energy & Fuels, 30 (11): 9761–

9771, 2016.

pubs.acs.org/doi/abs/10.1021/acs.energyfuels.6b01406

Knock Resistance and Fine Particle Emissions for Several Biomass-Derived 

Oxygenates in a Direct-Injection Spark-Ignition Engine — M.A. Ratcliff, J. Burton, 

P. Sindler, E. Christiansen, G.M. Chupka, L. Fouts, and R.L. McCormick. SAE Int. J. 

Fuel Lubr., 9:59-70, 2016.

papers.sae.org/2016-01-0705/

Leaner Lifted-Flame Combustion Enabled by the Use of an Oxygenated Fuel in 

an Optical CI Engine — R. Gehmlich, C. Dumitrescu, Y. Wang, and C. Mueller. SAE 

Int. J. Engines, 9: 1526-1543, 2016.

papers.sae.org/2016-01-0730/

NOx Conversion Over Ag/Alumina Catalysts via EtOH-SCR Using EtOH/Gasoline 

Blends — F. Gunnarsson, J. A. Pihl, T. J. Toops, M. Skoglundh, and H. Härelind. 

Applied Catalysis, B 202, 42-50, 2017.

The Selective Catalytic Reduction of NOx Over Ag/Al2O3 with Isobutanol as the 

Reductant — D.W. Brookshear, J.A. Pihl, T.J. Toops, B. West, and V. Prikhodko. 

Catalysis Today, 267, 65-75, 2016.

dx.doi.org/10.1016/j.cattod.2016.01.034.

Thrust II Engine Projects, Sprays, and Emissions Control Research — P. Miles, M. 

Sjöberg, J. Dec, S. Ciatti, C. Kolodziej, S. Curran, M. Musculus, and C. Mueller. DOE 

2016 Annual Merit Review and Peer Evaluation Meeting for the Vehicles Technologies Office, Washington, DC, June 5-9, 2016.

www.energy.gov/sites/prod/files/2016/06/f32/ft039_miles_2016_o_web.pdf 

Towards Development of a Fundamentally-Based Chemical Model for Cyclopentanone: High-Pressure-Limit Rate Constants for H-Atom Abstraction and Fuel 

Radical Decomposition — C.-W. Zhou, J.M. Simmie, W.J. Pitz, and H.J. Curran. J. 

Phys. Chem., A 120: 7037–7044, 2016.

dx.doi.org/10.1021/acs.jpca.6b03994

Two-Dimensional Soot Volume Fraction Measurements in Flames Doped with 

Large Hydrocarbons — D.D. Das, W.J. Cannella, C.S. McEnally, C.J. Mueller, and 

L.D. Pfefferle. Proceedings of the Combustion Institute, In press, 2016.

ac.els-cdn.com/S1540748916301055/1-s2.0-S1540748916301055 main.pdf?_

tid=66828708-aacc-11e6-8d06-00000aacb360&acdnat=1479170735_e1c4e598a4bb9117bd93d7d537a8c6fd

Utilizing Boost and Double Injections for Enhanced Stratified-Charge DISI Operation with Gasoline and E30 Fuels — W. Zeng and M. Sjöberg. THIESEL, Valencia, 

Spain, September 16, 2016.

www.cmt.upv.es/Thiesel2016/Thiesel02_06_11.aspx

28 | Co-Optima FY16 Year in Review
 Media Coverage

Co-Optima: A Moon Shot to Reach Car Fuel-Economy Heights — L. Hall, 

Fuel Freedom Foundation, June, 2016.

www.fuelfreedom.org/co-optima-a-moon-shot-to-reach-car-fueleconomy-heights/

Designing Tomorrow’s Engines: DOE’s Co-Optima — J. Stolark, 

Environmental and Energy Study Institute, June, 2016.

www.eesi.org/articles/view/designing-tomorrows-fuels-for-tomorrowsengines-does-co-optima

Co-Optima: Re-Designing Engines, Fuels, Marketplace Strategies All at 

Once — J. Lane, Biofuels Digest, July, 2016.

www.biofuelsdigest.com/bdigest/2016/07/24/cooptima-redesigningengines-fuels-marketplace-strategies-all-at-once/

GM, Honda Execs Agree: Higher Octane Gas Needed to Optimize ICE 

Efficiency — L. Brooke. SAE Organization, August 2016.

articles.sae.org/14940/

Photos in this report were provided by:

National Renewable Energy Laboratory

Oak Ridge National Laboratory

Sandia National Laboratories

iStock

Co-Optima FY16 Year in Review | 29 
Vehicle Technologies Office | Bioenergy Technologies Office

Lawrence Livermore 

National Laboratory

Project Partners 

30 | Co-Optima FY16 Year in Review
| Project Partners 

Reuben Sarkar

Deputy Assistant Secretary for 

Transportation — EERE

Jonathan Male

Director, BETO — EERE

Michael Berube

Director, VTO — EERE

Johney Green

Associate Laboratory Director, Mechanical 

& Thermal Systems Engineering — NREL

Mohammad Khaleel 

Associate Laboratory Director, Energy 

and Environmental Sciences — ORNL

Jud Virden

Associate Laboratory Director, Energy 

and Environment — PNNL

Marianne Walck

VP California Laboratory/ Lead, Energy 

and Climate Program — SNL

BETO

Alicia Lindauer 

Technology Manager, Bioenergy 

Analysis & Sustainability

Borka Kostova

Technology Manager, Bioenergy 

Technologies

VTO

Gupreet Singh

Program Manager, Advanced 

Combustion Engine R&D

Kevin Stork

Technology Manager, 

Fuels & Lubricants 

David Brooks

USCAR

Bill Cannella

American Petroleum Institute

Ralph Cavalieri

Retired, Washington State University

John Eichberger

Fuels Institute

David Foster

University of Wisconsin (Emeritus)

Roger Gault

Truck & Engine Manufacturers Association

James Guthrie

CA Air Resources Board

Paul Machiele

EPA

Michael McAdams

Advanced Biofuels Association

Chris Pritchard

Flint Hills Resources

John Wall

Retired Cummins Inc.

Edgar Wolff-Klammer

UL

EERE Program Representatives

External Advisory Board

Board of Directors

Co-Optima FY16 Year in Review | 31 
Prepared by the National Renewable Energy Laboratory and 

Sandia National Laboratories for the U.S. Department of Energy.

DOE/GO-102017-4933 January 2017

energy.gov/fuel-engine-co-optimization