ETA 2021 Strategic Plan - Flipbook - Page 26
Science of Scale-up: Translation of
understanding for improved use and
manufacturing
The delay in going from promising materials
concept to validation, optimization, and scale-up
is a significant burden to the commercialization
of novel energy materials and technologies. In
addition, even when a synthesis approach is
achieved in the laboratory, it often cannot be
economically scaled into an industrial process,
whether by size or rate. Providing methods
to ensure the translation from discovery to
synthesis to components to devices has the
potential to cut the time of innovation, with
acceleration times similar to what has been
achieved via MGI for materials discovery.
The science of scale-up will decrease the cycle
time by exploring the underlying physics
and scaling laws for the critical steps in the
manufacturing process. This includes not only
the formation steps, but also ways to minimize
scrap and water and novel methodologies for
modular manufacturing, where numbering
up becomes as important as scaling up.
Initially, batteries and other electrochemical
technologies (e.g., fuel cells, electrolyzers,
photoelectrochemical cells, thermoelectrics,
electrosynthesis) will be used as prototypical
systems to develop core competences further
in the area of scaling science. ETA will explore
critical fabrication and processing issues
that occur in high-volume manufacturing
efficiently through developing well-controlled
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subscale setups that mimic the intrinsic rates
and processes, thereby providing rapid and
intelligent optimization.
Electrochemical systems are an ideal platform
system for establishing scaling capability.
For example, the $60 billion-per-year battery
industry is essential to distributed generation,
transportation, and the grid, and is expected
to double in size over the next 10 years.
However, long-duration storage could remain
a niche technology unless costs decrease
further, systems are made safer, lifetimes
are extended, and charge times decrease.
New materials hold promise for solving these
challenges, and offer a way to bring battery
and electrochemical manufacturing back to
the United States. History suggests the scaling
and processing of new materials hold the
key to translating lab discoveries into market
impact. This context makes energy storage and
related electrochemical energy-conversion in
the electrochemical refinery ideal platforms
for building core capability in scaling science,
as detailed in the Energy Storage Across Time,
Length and Scale strategic initiative and below,
respectively.
Another scaling issue is related to the
circular economy application wherein one is
concerned about degradation at the scale of
the environment, which is influenced by both
abiotic and biotic factors. ETA has a history of
simulating weathering processes as part of ETA
Cool Roof Time Machine research, and similar
approaches of translating smaller scale studies
to real-world implications will be utilized. Our
goal is to advance understanding of the science
behind scaling, to speed the design-build-testlearn cycle by marrying machine learning and
artificial intelligence with the underlying physics,
and reduce the time from discovery to market.
A third challenge associated with scaling both
the total size and the total rate of processes is
the generation and transport of thermal energy
into and out of those process. ETA will build
on its core competency in multimodal heat
transport to understand how different kinds of
candidate renewable heat sources scale, where
the potential bottlenecks lie, and what will be
necessary to overcome them. In particular,
we will investigate solar thermal, controlled
combustion of green and blue hydrogen, and
electrical Joule heating using green electrons
as ways to produce emissions-free heat, as
well as modes of thermal energy storage. Each
approach will be assessed for its potential to
replace the energy density and dispatchability of
fossil fuels that enable the large-scale industrial
processes of today.
Intelligent, Adaptive Analysis: Guiding
manufacturing from a holistic perspective
Enabling success in precision manufacturing
and translational scale-up science requires
intelligent, adaptive analysis. This analysis will
provide rigorous, quantitative feedback on
the degree to which different technologies
and strategies advance broader goals of cost
reduction, emissions mitigation, and reduced
waste throughout the supply chain. ETA has
a long history of leadership in holistic energy
analysis of complex systems. We will design and
simulate the manufacture of new chemicals
and materials to understand minimum energy
and water requirements, develop libraries of
manufacturing process models, and use new
techniques in machine learning and optimization
to iterate on these designs to achieve cost
reduction, emissions reduction, and water-
use goals. Models of scaled-up manufacturing
processes will be integrated into cradle-to-grave
models to enable potential site evaluation,
assembly of potential supply chains based
on domestic availability of key materials and
components, and design of facilities capable
of integrating with a renewables-dominated
grid. Overall, these efforts will lead to a better
understanding of the use-phase and end-of-life
impacts for products.
This focus area will develop and apply more
advanced methods for agile, rapid, and rigorous
techno-economic and life-cycle analysis. These
methods will integrate individual materials and
processes into the broader systemwide context
and estimate costs, net energy, emissions
and waste flows. We also will apply datascience methods, processes, and algorithms
to understand complex mixtures and conduct
predictive exploration of reaction spaces with
new/unknown conditions or materials/system
performance. Inverse design will serve as the
connective tissue between all three focus areas
in this initiative, allowing for the design-buildtest-learn cycle to progress more rapidly and for
the design phase to be motived by a “pull” based
on system-level needs and goals.
For example, for the electrochemical refinery
concept, techno-economic analysis (TEA)
and life-cycle analysis (LCA) will be used to
interrogate the experimental electrochemical
refineries versus thermochemical approaches
to inform the correct chemicals to target. Such
analysis includes various markets including
those that value newer motifs enabled by
the technology (e.g., scalable, distributed
generation). Similarly, for the circular economy
application, ETA will work on establishing a
comprehensive methodology — consisting
of lab-based materials characterization and
rigorous, systemwide modeling — to evaluate
the complete environmental impact of specific
plastic supply routes under a variety of wastemanagement schemes. And to further the
decarbonization of industrial heat, ETA will
leverage the same TEAs and LCAs to understand
which thermochemical synthesis routes have the
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