Engineered Microenvironment of Imidazolium Salts by Multi-scale Modeling and Machine Learning Algorithms for Enhanced Electrocatalytic CO2 Reduction to Ethylene and Acetamide via Targeted Delivery of CuAg Alloy Tandem Catalyst Based on Cu(111) Facet Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.21203/rs.3.rs-6647633/v1
Electrocatalytic CO2 reduction (eCO2R) to high-value multicarbon (C2+) hydrocarbons such as ethylene (CH2 = CH2) and acetamide (CH3CONH2) via C–C/N coupling is an attractive and effective technique for achieving zero carbon emissions and advancing renewable energy. Recent studies report the use of engineered microenvironments formed via imidazolium salts (ionic liquid) to establish an electric double-layer (EDL) interfacial Helmholtz layer at the Cu-based catalyst interface. However, monometallic Cu catalysts exhibit low activity and poor Faradaic efficiency (selectivity) for hydrocarbon products, limiting their commercial application. Herein, we demonstrated targeted delivery of CuAg alloy nanoparticles (NPs) and Ag single atoms (SA) tandem on Cu(111) facets. The improved chemical properties of bimetallic nanocrystals arise from the synergistic interaction between Cu and Ag metals, enabling this tandem catalyst system (with Ag active sites) to catalyze CO2 to CO and subsequently convert CO into (C2+) hydrocarbon intermediates via C–C coupling on Cu sites. Furthermore, CO2 reduction to CCO on Cu sites and subsequent conversion to acetamide via C–N coupling between CCO and NH3 on Ag sites are achieved. We modeled EDL at the Cu-based tandem catalyst interface, which was modulated using the electric field–controlling constant potential (EFC–CP) method, including a series of imidazolium salts (both anions and cations) and hydronium ions (H3O+δ) to study their induced electrode potentials. Imidazolium (cation) play a crucial role in increasing local CO2 enrichment and stabilizing carbon-based intermediates. The EFC–CP method within the Helmholtz layer allows explicit consideration of solvent and induced electric field on reaction intermediates. Our results suggest that C–C couplings between *CO and *CO or *CH and *CH are the most favorable for the formation of ethylene. Specifically, 1-butyl-3-methylimidazolium tetrafuoroborate (B2195) and 1-butyl-3-methylimidazolium hexafuorophosphate (B2320) salts decrease the maximum limiting potential (Umax(η)) to − 0.84 and − 1.00 V, respectively, positioning them as promising ionic liquid for eCO2R. To understand EDL effects in eCO2R at the molecular scale, we employed ab initio molecular dynamics simulation, focusing on hydrogen-bond networks and cation effects through a multiscale approach. Furthermore, this design strategy incorporated regression machine learning (ML) using the extreme gradient boosting regression model and the sure independence screening and sparsifying operator approach to identify key features influencing the target property Umax(η) serving as the ML input data. Results show that coupling energy (Ecplg) and the average deviation in ground-state band gaps of constituent elements are the most important features for both ethylene and acetamide synthesis, with B2195 and B2320 imidazolium salts efficiently activating CO2 and driving electroreduction to ethylene with optimized Umax(η).
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-6647633/v1
- https://www.researchsquare.com/article/rs-6647633/latest.pdf
- OA Status
- gold
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410474876
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4410474876Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-6647633/v1Digital Object Identifier
- Title
-
Engineered Microenvironment of Imidazolium Salts by Multi-scale Modeling and Machine Learning Algorithms for Enhanced Electrocatalytic CO2 Reduction to Ethylene and Acetamide via Targeted Delivery of CuAg Alloy Tandem Catalyst Based on Cu(111) FacetWork title
- Type
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preprintOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-05-19Full publication date if available
- Authors
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Yi Xiao, Yunhua Xu, Yingchun Ding, Hua HuangList of authors in order
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-
https://doi.org/10.21203/rs.3.rs-6647633/v1Publisher landing page
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https://www.researchsquare.com/article/rs-6647633/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-6647633/latest.pdfDirect OA link when available
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Acetamide, Ethylene, Catalysis, Alloy, Tandem, Materials science, Scaling, Chemistry, Computer science, Organic chemistry, Metallurgy, Mathematics, Composite material, GeometryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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40Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.was | 183 |
| abstract_inverted_index.− | 286, 289 |
| abstract_inverted_index.(ML) | 337 |
| abstract_inverted_index.(SA) | 98 |
| abstract_inverted_index.0.84 | 287 |
| abstract_inverted_index.1.00 | 290 |
| abstract_inverted_index.CuAg | 90 |
| abstract_inverted_index.band | 381 |
| abstract_inverted_index.both | 392 |
| abstract_inverted_index.from | 111 |
| abstract_inverted_index.gaps | 382 |
| abstract_inverted_index.into | 138 |
| abstract_inverted_index.ions | 205 |
| abstract_inverted_index.most | 263, 388 |
| abstract_inverted_index.play | 215 |
| abstract_inverted_index.poor | 73 |
| abstract_inverted_index.role | 218 |
| abstract_inverted_index.show | 370 |
| abstract_inverted_index.such | 10 |
| abstract_inverted_index.sure | 347 |
| abstract_inverted_index.that | 250, 371 |
| abstract_inverted_index.them | 294 |
| abstract_inverted_index.this | 121, 330 |
| abstract_inverted_index.with | 397, 411 |
| abstract_inverted_index.zero | 30 |
| abstract_inverted_index.(EDL) | 56 |
| abstract_inverted_index.(NPs) | 93 |
| abstract_inverted_index.(both | 199 |
| abstract_inverted_index.(with | 125 |
| abstract_inverted_index.B2195 | 398 |
| abstract_inverted_index.B2320 | 400 |
| abstract_inverted_index.C–C | 143, 251 |
| abstract_inverted_index.C–N | 162 |
| abstract_inverted_index.alloy | 91 |
| abstract_inverted_index.arise | 110 |
| abstract_inverted_index.atoms | 97 |
| abstract_inverted_index.data. | 368 |
| abstract_inverted_index.field | 243 |
| abstract_inverted_index.input | 367 |
| abstract_inverted_index.ionic | 297 |
| abstract_inverted_index.layer | 59, 234 |
| abstract_inverted_index.local | 221 |
| abstract_inverted_index.model | 344 |
| abstract_inverted_index.salts | 48, 198, 278, 402 |
| abstract_inverted_index.sites | 155, 170 |
| abstract_inverted_index.study | 208 |
| abstract_inverted_index.their | 81, 209 |
| abstract_inverted_index.using | 185, 338 |
| abstract_inverted_index.which | 182 |
| abstract_inverted_index.(ionic | 49 |
| abstract_inverted_index.Recent | 37 |
| abstract_inverted_index.active | 127 |
| abstract_inverted_index.allows | 235 |
| abstract_inverted_index.anions | 200 |
| abstract_inverted_index.carbon | 31 |
| abstract_inverted_index.cation | 323 |
| abstract_inverted_index.design | 331 |
| abstract_inverted_index.energy | 373 |
| abstract_inverted_index.formed | 45 |
| abstract_inverted_index.initio | 314 |
| abstract_inverted_index.liquid | 298 |
| abstract_inverted_index.method | 230 |
| abstract_inverted_index.report | 39 |
| abstract_inverted_index.scale, | 310 |
| abstract_inverted_index.series | 195 |
| abstract_inverted_index.single | 96 |
| abstract_inverted_index.sites) | 128 |
| abstract_inverted_index.sites. | 147 |
| abstract_inverted_index.system | 124 |
| abstract_inverted_index.tandem | 99, 122, 179 |
| abstract_inverted_index.target | 360 |
| abstract_inverted_index.within | 231 |
| abstract_inverted_index.(B2195) | 273 |
| abstract_inverted_index.(B2320) | 277 |
| abstract_inverted_index.Cu(111) | 101 |
| abstract_inverted_index.C–C/N | 20 |
| abstract_inverted_index.Herein, | 84 |
| abstract_inverted_index.Results | 369 |
| abstract_inverted_index.average | 377 |
| abstract_inverted_index.between | 115, 164, 253 |
| abstract_inverted_index.convert | 136 |
| abstract_inverted_index.crucial | 217 |
| abstract_inverted_index.driving | 407 |
| abstract_inverted_index.effects | 304, 324 |
| abstract_inverted_index.energy. | 36 |
| abstract_inverted_index.exhibit | 69 |
| abstract_inverted_index.extreme | 340 |
| abstract_inverted_index.facets. | 102 |
| abstract_inverted_index.induced | 210, 241 |
| abstract_inverted_index.liquid) | 50 |
| abstract_inverted_index.machine | 335 |
| abstract_inverted_index.maximum | 281 |
| abstract_inverted_index.metals, | 119 |
| abstract_inverted_index.method, | 192 |
| abstract_inverted_index.modeled | 174 |
| abstract_inverted_index.results | 248 |
| abstract_inverted_index.serving | 363 |
| abstract_inverted_index.solvent | 239 |
| abstract_inverted_index.studies | 38 |
| abstract_inverted_index.suggest | 249 |
| abstract_inverted_index.through | 325 |
| abstract_inverted_index.(cation) | 214 |
| abstract_inverted_index.Cu-based | 62, 178 |
| abstract_inverted_index.EFC–CP | 229 |
| abstract_inverted_index.Faradaic | 74 |
| abstract_inverted_index.However, | 65 |
| abstract_inverted_index.activity | 71 |
| abstract_inverted_index.approach | 353 |
| abstract_inverted_index.boosting | 342 |
| abstract_inverted_index.catalyst | 63, 123, 180 |
| abstract_inverted_index.catalyze | 130 |
| abstract_inverted_index.cations) | 202 |
| abstract_inverted_index.chemical | 105 |
| abstract_inverted_index.constant | 189 |
| abstract_inverted_index.coupling | 21, 144, 163, 372 |
| abstract_inverted_index.decrease | 279 |
| abstract_inverted_index.delivery | 88 |
| abstract_inverted_index.dynamics | 316 |
| abstract_inverted_index.electric | 54, 187, 242 |
| abstract_inverted_index.elements | 385 |
| abstract_inverted_index.employed | 312 |
| abstract_inverted_index.enabling | 120 |
| abstract_inverted_index.ethylene | 12, 393, 410 |
| abstract_inverted_index.explicit | 236 |
| abstract_inverted_index.features | 357, 390 |
| abstract_inverted_index.focusing | 318 |
| abstract_inverted_index.gradient | 341 |
| abstract_inverted_index.identify | 355 |
| abstract_inverted_index.improved | 104 |
| abstract_inverted_index.learning | 336 |
| abstract_inverted_index.limiting | 80, 282 |
| abstract_inverted_index.networks | 321 |
| abstract_inverted_index.operator | 352 |
| abstract_inverted_index.property | 361 |
| abstract_inverted_index.reaction | 245 |
| abstract_inverted_index.strategy | 332 |
| abstract_inverted_index.targeted | 87 |
| abstract_inverted_index.Helmholtz | 58, 233 |
| abstract_inverted_index.acetamide | 17, 160, 395 |
| abstract_inverted_index.achieved. | 172 |
| abstract_inverted_index.achieving | 29 |
| abstract_inverted_index.advancing | 34 |
| abstract_inverted_index.approach. | 328 |
| abstract_inverted_index.catalysts | 68 |
| abstract_inverted_index.couplings | 252 |
| abstract_inverted_index.deviation | 378 |
| abstract_inverted_index.effective | 26 |
| abstract_inverted_index.electrode | 211 |
| abstract_inverted_index.emissions | 32 |
| abstract_inverted_index.establish | 52 |
| abstract_inverted_index.ethylene. | 269 |
| abstract_inverted_index.favorable | 264 |
| abstract_inverted_index.formation | 267 |
| abstract_inverted_index.hydronium | 204 |
| abstract_inverted_index.important | 389 |
| abstract_inverted_index.including | 193 |
| abstract_inverted_index.modulated | 184 |
| abstract_inverted_index.molecular | 309, 315 |
| abstract_inverted_index.optimized | 412 |
| abstract_inverted_index.potential | 190, 283 |
| abstract_inverted_index.products, | 79 |
| abstract_inverted_index.promising | 296 |
| abstract_inverted_index.reduction | 3, 150 |
| abstract_inverted_index.renewable | 35 |
| abstract_inverted_index.screening | 349 |
| abstract_inverted_index.technique | 27 |
| abstract_inverted_index.(EFC–CP) | 191 |
| abstract_inverted_index.activating | 404 |
| abstract_inverted_index.attractive | 24 |
| abstract_inverted_index.bimetallic | 108 |
| abstract_inverted_index.commercial | 82 |
| abstract_inverted_index.conversion | 158 |
| abstract_inverted_index.efficiency | 75 |
| abstract_inverted_index.engineered | 43 |
| abstract_inverted_index.enrichment | 223 |
| abstract_inverted_index.high-value | 6 |
| abstract_inverted_index.increasing | 220 |
| abstract_inverted_index.interface, | 181 |
| abstract_inverted_index.interface. | 64 |
| abstract_inverted_index.multiscale | 327 |
| abstract_inverted_index.properties | 106 |
| abstract_inverted_index.regression | 334, 343 |
| abstract_inverted_index.subsequent | 157 |
| abstract_inverted_index.synthesis, | 396 |
| abstract_inverted_index.understand | 302 |
| abstract_inverted_index.Imidazolium | 213 |
| abstract_inverted_index.constituent | 384 |
| abstract_inverted_index.efficiently | 403 |
| abstract_inverted_index.hydrocarbon | 78, 140 |
| abstract_inverted_index.imidazolium | 47, 197, 401 |
| abstract_inverted_index.influencing | 358 |
| abstract_inverted_index.interaction | 114 |
| abstract_inverted_index.interfacial | 57 |
| abstract_inverted_index.multicarbon | 7 |
| abstract_inverted_index.positioning | 293 |
| abstract_inverted_index.potentials. | 212 |
| abstract_inverted_index.simulation, | 317 |
| abstract_inverted_index.sparsifying | 351 |
| abstract_inverted_index.stabilizing | 225 |
| abstract_inverted_index.synergistic | 113 |
| abstract_inverted_index.Furthermore, | 148, 329 |
| abstract_inverted_index.application. | 83 |
| abstract_inverted_index.carbon-based | 226 |
| abstract_inverted_index.demonstrated | 86 |
| abstract_inverted_index.double-layer | 55 |
| abstract_inverted_index.ground-state | 380 |
| abstract_inverted_index.hydrocarbons | 9 |
| abstract_inverted_index.incorporated | 333 |
| abstract_inverted_index.independence | 348 |
| abstract_inverted_index.monometallic | 66 |
| abstract_inverted_index.nanocrystals | 109 |
| abstract_inverted_index.subsequently | 135 |
| abstract_inverted_index.(selectivity) | 76 |
| abstract_inverted_index.Specifically, | 270 |
| abstract_inverted_index.consideration | 237 |
| abstract_inverted_index.hydrogen-bond | 320 |
| abstract_inverted_index.intermediates | 141 |
| abstract_inverted_index.nanoparticles | 92 |
| abstract_inverted_index.respectively, | 292 |
| abstract_inverted_index.CO<sub>2</sub> | 2, 131, 149, 222, 405 |
| abstract_inverted_index.NH<sub>3</sub> | 167 |
| abstract_inverted_index.intermediates. | 227, 246 |
| abstract_inverted_index.(CH<sub>2</sub> | 13 |
| abstract_inverted_index.CH<sub>2</sub>) | 15 |
| abstract_inverted_index.(C<sub>2+</sub>) | 8, 139 |
| abstract_inverted_index.Electrocatalytic | 1 |
| abstract_inverted_index.eCO<sub>2</sub>R | 306 |
| abstract_inverted_index.electroreduction | 408 |
| abstract_inverted_index.tetrafuoroborate | 272 |
| abstract_inverted_index.eCO<sub>2</sub>R. | 300 |
| abstract_inverted_index.microenvironments | 44 |
| abstract_inverted_index.(eCO<sub>2</sub>R) | 4 |
| abstract_inverted_index.hexafuorophosphate | 276 |
| abstract_inverted_index.field–controlling | 188 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| abstract_inverted_index.1-butyl-3-methylimidazolium | 271, 275 |
| abstract_inverted_index.(H<sub>3</sub>O<sup>+δ</sup>) | 206 |
| abstract_inverted_index.(CH<sub>3</sub>CONH<sub>2</sub>) | 18 |
| abstract_inverted_index.(<italic>E</italic><sub>cplg</sub>) | 374 |
| abstract_inverted_index.<italic>U</italic><sub>max</sub>(η) | 362 |
| abstract_inverted_index.<italic>U</italic><sub>max</sub>(η). | 413 |
| abstract_inverted_index.(<italic>U</italic><sub>max</sub>(η)) | 284 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.14416246 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |