ETA 2021 Strategic Plan - Flipbook - Page 24
the Presidential Materials Genome Initiative
resulted in several examples of computationally
designed materials in the fields of energy
storage, catalysis, thermoelectrics, and hydrogen
storage. It also resulted in large data resources
that can be used to screen for potentially
transformative compounds and provide input
for machine-learning algorithms, to elucidate
hidden correlations and causalities. Today,
new materials can be discovered in months
rather than the years it has taken when
using traditional trial-and-error Edisonian
experimentation. This initiative drives the
concept further by expanding the focus from the
properties of single materials to the synthesis
and reaction pathways of composite materials.
Moreover, to support a circular economy, it is
critical to ask not only what the new material
is, but how it can be made and how it will be
recovered and recycled. This question is key to
this initiative.
Research Summary
Advanced manufacturing is a growing field, with
ample opportunities for rapid realization of
technologies through combined computational
and experimental investigations that run
through the design-build-test-learn framework.
This is especially true for next-generation
manufacturing processes that increasingly must
focus on zero or negative carbon emissions.
These processes include use of novel and green
power vectors such as renewable electrons,
understanding methods and ways to enhance
decarbonization of thermal vectors and use, and
an awareness of overall lifetime and circularity
of both the end product and the manufacturing
pathway. Advances in computational power and
algorithms enable these new manufacturing
methodologies through advanced machine
learning and artificial intelligence, which also
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opens opportunities for cross disciplinary or
hybrid approaches to designing manufacturing.
An example includes reactive capture of
carbon dioxide (CO2) (i.e., combined capture
and conversion) that may rely on different
electrochemical, biological, thermal, or
plasmonic steps in the synthesis of chemicals,
thereby providing truly optimized reaction
pathways. Furthermore, the conceptualization
of different manufacturing pathways, combined
with critical experiments and computation,
enable a targeted experimental test and
validation regime that enables green chemical
routes to be realized in record time.
Advances in computational materials modeling
are accelerating toward a future where most
properties of real and virtual compounds
can be available on demand, enabling rapid
screening in material design. For example,
Concomitant with the advances in material
discovery, there have been advances in
understanding how materials come together to
make a device, whether that process is going
from ink slurry to multifunctional device in a
roll-to-roll process or formation of metastable
materials. We will establish a mathematical
framework, verified by experiments, that links
materials discovery predictions to material
synthesis conditions to material integration
conditions to device performance. Establishing
such a framework will significantly accelerate
the discovery-integration-testing cycle for new
materials development. In addition, these
mathematical frameworks will help guide and
frame intuition.
There is a growing realization that hybrid
motifs are critical for the manufacturing sector,
where multiple synthesis vectors need to be
tightly integrated. Such approaches can open
new development pathways that ultimately
result in a highly decarbonized manufacturing
process and product. Key to this realization is
decarbonization of the thermal energy, which
accounts for 20% of global CO2 emissions. While
electrification can help alleviate some of it, ETA
will also actively research hybrid and thermal
decarbonization approaches such as use of
high-temperature resistive heating, hydrogen
combustion, solar thermal approaches for lowtemperature applications, and thermal storage
for industrial processes.
Focus Areas
The realization of these objectives requires work
in three focus areas: (1) Science of Synthesis;
(2) Science of Scale-up; and (3) Intelligent,
Adaptive Analysis. The research approaches
described under each of these areas are
broadly applicable to a variety of manufacturing
processes, from carbon capture and conversion
to novel material synthesis to the manufacturing
of energy-storage devices. In the near-term,
ETA researchers are applying the approaches
described in each area to three conceptual
applications: the Electrochemical Refinery, the
Circular Economy, and the Decarbonization of
Industrial Heat.
Science of Synthesis: Precision
manufacturing
The U.S. chemical industry is diverse, with
70,000 products and global integration
across a complex web of supply chains.
There are process-related approaches for
reducing energy and decarbonizing the sector;
however, increasing availability of inexpensive
renewable electrons provides an opportunity
to reevaluate and decarbonize the synthesis
of chemicals using electrochemistry. Similarly,
the increased understanding of energy transfer
and additive mechanisms for manufacturing
provide opportunities to synthesize chemicals
using additive molecular manufacturing and
nontraditional energy inputs (e.g., plasma,
electrochemical, acoustic, photonic). These
energy-transfer modalities can be coupled with
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