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ACKNOWLEDGMENTS
We thank the SBGrid team for technical assistance, K. Arnett for
support and advice on the BLI experiments, and S. Harrison and
A. Carfi for critical reading of the manuscript. EM data were
collected at the Harvard Cryo-EM Center for Structural Biology
of Harvard Medical School. We acknowledge support for COVID-19–
related structural biology research at Harvard from the Nancy
Lurie Marks Family Foundation and the Massachusetts Consortium
on Pathogen Readiness (MassCPR).Funding:This work was
supported by Fast grants by Emergent Ventures (to B.C. and
D.R.W.), COVID-19 Award by MassCPR (to B.C. and D.R.W.), and
NIH grants AI147884 and AI141002 (to B.C.), AI127193 (to B.C.
and James Chou), and AI39538 and AI165072 (to D.R.W).Author
contributions:B.C., J.Z., T.X., and Y.C. conceived the project.
Y.C. expressed and purified the full-length S proteins with help
from H.P. and carried out negative stain EM. T.X. performed
BLI and cell-cell fusion experiments. J.Z. prepared cryo grids and
performed EM data collection with contributions from M.L.M.
and R.M.W., processed the cryo-EM data, and built and refined
the atomic models. J.L. created all the expression constructs and
performed the neutralization assays with the MLV-based
pseudoviruses. C.L.L. and M.S.S. performed the neutralization
assays with the HIV-based pseudoviruses. H.Z., K.A., and W.Y.
performed the flow cytometry experiments. P.T., A.G., and D.R.W.
produced the anti-S monoclonal antibodies. S.R.V. contributed
to cell culture and protein production. All authors analyzed the
data. B.C., J.Z., T.X., and Y.C. wrote the manuscript with input from
all other authors.Competing interests:W.Y. serves on the
scientific advisory boards of Hummingbird Bioscience and GO
Therapeutics and is currently an employee of GV20 Therapeutics
LLC. All other authors declare no competing interests.Data
and materials availability:The atomic structure coordinates are
deposited in the RCSB Protein Data Bank (PDB) under the
accession numbers 7SBK, 7SBL, 7SBO, 7SBP, 7SBQ, 7SBR, 7SBS,
and 7SBT; the electron microscopy maps have been deposited
in the Electron Microscopy Data Bank (EMDB) under the accession
numbers EMD-24981, EMD-24982, EMD-24983, EMD-24984,
EMD-24985, EMD-24986, EMD-24987, and EMD-24988. All
materials generated during the current study are available from
the corresponding author under an MTA with Boston Children’s
Hospital. This work is licensed under a Creative Commons
Attribution 4.0 International (CC BY 4.0) license, which permits
unrestricted use, distribution, and reproduction in any medium,

provided the original work is properly cited. To view a copy

of this license, visit https://creativecommons.org/licenses/by/4.0/.

This license does not apply to figures/photos/artwork or other

content included in the article that is credited to a third

party; obtain authorization from the rights holder before using

such material.

SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl9463

Materials and Methods

Figs. S1 to S18

Tables S1 to S3

References ( 57 – 69 )

MDAR Reproducibility Checklist

15 August 2021; accepted 22 October 2021

Published online 26 October 2021

10.1126/science.abl9463

CATALYSIS

Sabatier principle of metal-support interaction

for design of ultrastable metal nanocatalysts

Sulei Hu and Wei-Xue Li*

The stability of supported nanocatalysts is crucial to meeting environmental and energy challenges and

necessitates fundamental theory to relieve trial-and-error experimentation and accelerate lab-to-fab

translation. Here, we report a Sabatier principle of metal-support interaction for stabilizing metal

nanocatalysts against sintering based on the kinetic simulations of 323 metal-support pairs using scaling

relations from 1252 energetics data. Too strong of an interaction is shown to trigger Ostwald ripening,

whereas too weak of an interaction stimulates particle migration and coalescence. High-throughput

screening of supports enables the sintering resistance of nanocatalysts to reach the Tammann

temperature on homogeneous supports and far beyond it on heteroenergetic supports. This theory,

which is substantiated by first-principles neural network molecular dynamics simulations and

experiments, paves the way for the design of ultrastable nanocatalysts.

T

he stability of nanomaterials is a matter

of life(time) and death in various nano-

technologies, especially for heterogeneous

metal nanocatalysts, to meet energy and

environmental requirements ( 1 ). The in-

stability, among other issues, caused by the

thermal- and/or chemical-induced sintering

( 2 ) of smaller metal nanoparticles (NPs) into

larger NPs with shrinking atomic utilization

severely decreases productivity, delays the

lab-to-fab translation of highly active nano-

catalysts ( 3 ), and requires plant shutdown for

catalyst replacement or regeneration with

large capital costs ( 4 ). The rational design of

nanocatalysts with sufficient thermal resist-

ance and operando lifetime, in addition to high

activity and selectivity, has important economic

and scientific value, even for the general nano-

science field ( 5 ).

Sintering of metal NPs proceeds through

the formation and diffusion of metal atoms

and/or metal-reactant complexes [Ostwald

ripening (OR)] ( 6 , 7 ) and/or through particle

migration and coalescence (PMC) on the sup-

port (Fig. 1A) ( 8 ). To mitigate sintering, phys-

ical approaches such as spatial confinement

and geometric shielding ( 9 ) have been used,

which involve the incorporation of NPs into

one-dimensional (1D) tubular or 3D micro- or

mesoporous materials ( 10 ) and the full or

partial encapsulation of NPs with less-reactive

thin films with microchannels ( 11 ). The cost of

these approaches is the blockage of active sites

and the impeded transport of reactants. Chem-

ically, alteration of metal-support interaction

(MSI)isusedtostabilizeNPsandcontrolthe

sintering kinetics ( 12 ), which is, however, a

complex function of the support composition

and surface orientation and defects ( 13 ), in-

terface structure, lattice mismatch, mixing and

alloy phase formation, charge rearrangement

( 14 ), and reaction conditions ( 15 ). This fact

results in a large gap between the sintering

kinetics and the underlying MSI and chal-

lenges the screening and/or optimization of

supports, thereby necessitating expensive trial-

and-error experimentation ( 3 ). To bridge this

gap, it is vital to identify the corresponding MSI

descriptor and determine the governing rule

for the sintering kinetics and develop a design

theory to engineer the metal-support interface

for ultrastable nanocatalysts.

Here, we report a Sabatier principle of MSI

for the stability of supported metal NPs against

sintering based on the linear scaling relation-

ship between the particle adhesion energy and

atom binding energy with supports, two MSI

descriptors for the corresponding OR and

PMC processes. Sintering kinetic simulations

1360 10 DECEMBER 2021¥VOL 374 ISSUE 6573 science.orgSCIENCE

Hefei National Laboratory for Physical Sciences at the

Microscale, School of Chemistry and Materials Science, Key

Laboratory of Surface and Interface Chemistry and Energy

Catalysis of Anhui Higher Education Institutes, CAS Center for

Excellence in Nanoscience, iChEM, University of Science and

Technology of China, Hefei, China.

*Corresponding author. Email: [email protected]

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