Chemistry Publications

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Atomically precise nanoclusters predominantly seed gold nanoparticle syntheses
(Springer Nature, 2023) Qiao, Liang; Pollard, Nia; Senanayake, Ravithree D.; Yang, Zhi; Kim, Minjung; Ali, Arzeena S.; Hoang, Minh Tam; Yao, Nan; Han, Yimo; Hernandez, Rigoberto; Clayborne, Andre Z.; Jones, Matthew R.
Seed-mediated synthesis strategies, in which small gold nanoparticle precursors are added to a growth solution to initiate heterogeneous nucleation, are among the most prevalent, simple, and productive methodologies for generating well-defined colloidal anisotropic nanostructures. However, the size, structure, and chemical properties of the seeds remain poorly understood, which partially explains the lack of mechanistic understanding of many particle growth reactions. Here, we identify the majority component in the seed solution as an atomically precise gold nanocluster, consisting of a 32-atom Au core with 8 halide ligands and 12 neutral ligands constituting a bound ion pair between a halide and the cationic surfactant: Au32X8[AQA+•X-]12 (X = Cl, Br; AQA = alkyl quaternary ammonium). Ligand exchange is dynamic and versatile, occurring on the order of minutes and allowing for the formation of 48 distinct Au32 clusters with AQAX (alkyl quaternary ammonium halide) ligands. Anisotropic nanoparticle syntheses seeded with solutions enriched in Au32X8[AQA+•X-]12 show narrower size distributions and fewer impurity particle shapes, indicating the importance of this cluster as a precursor to the growth of well-defined nanostructures.
A deep learning solution for crystallographic structure determination
(International Union of Crystallography, 2023) Pan, T.; Jin, S.; Miller, M. D.; Kyrillidis, A.; Phillips, G. N.
The general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept.
Graphene as a rational interface for enhanced adsorption of microcystin-LR from water
(Elsevier, 2023) Roberts, Jesse L.; Zetterholm, Sarah Grace; Gurtowski, Luke; Fernando, PU Ashvin I.; Evans, Angela; Puhnaty, Justin; Wyss, Kevin M.; Tour, James M.; Fernando, Brianna; Jenness, Glen; Thompson, Audie; Griggs, Chris; Rice Advanced Materials Institute; Welch Institute for Advanced Materials; Smalley-Curl Institute
Cyanotoxins such as microcystin-LR (MC-LR) represent a global environmental threat to ecosystems and drinking water supplies. The study investigated the direct use of graphene as a rational interface for removal of MC-LR via interactions with the aromatic ring of the ADDA1 chain of MC-LR and the sp2 hybridized carbon network of graphene. Intra-particle diffusion model fit indicated the high mesoporosity of graphene provided significant enhancements to both adsorption capacities and kinetics when benchmarked against microporous granular activated carbon (GAC). Graphene showed superior MC-LR adsorption capacity of 75.4 mg/g (Freundlich model) compared to 0.982 mg/g (Langmuir model) for GAC. Sorption kinetic studies showed graphene adsorbs 99% of MC-LR in 30 min, compared to zero removal for GAC after 24 hr using the same MC-LR concentration. Density functional theory (DFT), calculations showed that postulated π-based interactions align well with the NMR-based experimental work used to probe primary interactions between graphene and MC-LR adduct. This study proved that π-interactions between the aromatic ring on MC-LR and graphene sp2 orbitals are a dominant interaction. With rapid kinetics and adsorption capacities much higher than GAC, it is anticipated that graphene will offer a novel molecular approach for removal of toxins and emerging contaminants with aromatic systems.
Mass Spectrometry of RNA-Binding Proteins during Liquid–Liquid Phase Separation Reveals Distinct Assembly Mechanisms and Droplet Architectures
(American Chemical Society, 2023) Sahin, Cagla; Motso, Aikaterini; Gu, Xinyu; Feyrer, Hannes; Lama, Dilraj; Arndt, Tina; Rising, Anna; Gese, Genis Valentin; Hällberg, B. Martin; Marklund, Erik. G.; Schafer, Nicholas P.; Petzold, Katja; Teilum, Kaare; Wolynes, Peter G.; Landreh, Michael; Center for Theoretical Biological Physics
Liquid–liquid phase separation (LLPS) of heterogeneous ribonucleoproteins (hnRNPs) drives the formation of membraneless organelles, but structural information about their assembled states is still lacking. Here, we address this challenge through a combination of protein engineering, native ion mobility mass spectrometry, and molecular dynamics simulations. We used an LLPS-compatible spider silk domain and pH changes to control the self-assembly of the hnRNPs FUS, TDP-43, and hCPEB3, which are implicated in neurodegeneration, cancer, and memory storage. By releasing the proteins inside the mass spectrometer from their native assemblies, we could monitor conformational changes associated with liquid–liquid phase separation. We find that FUS monomers undergo an unfolded-to-globular transition, whereas TDP-43 oligomerizes into partially disordered dimers and trimers. hCPEB3, on the other hand, remains fully disordered with a preference for fibrillar aggregation over LLPS. The divergent assembly mechanisms revealed by ion mobility mass spectrometry of soluble protein species that exist under LLPS conditions suggest structurally distinct complexes inside liquid droplets that may impact RNA processing and translation depending on biological context.
The role of graphene in new thermoelectric materials
(Royal Society of Chemistry, 2023) Mulla, Rafiq; White, Alvin Orbaek; Dunnill, Charles W.; Barron, Andrew R.
Graphene has high electrical conductivity, making it an attractive material for thermoelectric applications. However, its high thermal conductivity is a major challenge, and initial studies indicate that using pristine graphene alone cannot achieve optimal thermoelectric performance. Therefore, researchers are exploring ways to improve thermoelectric materials by either leveraging graphene's high intrinsic electrical conductivity or compounding graphene with additives to reduce the intrinsic thermal conductivity of the materials. Therefore, the research focus is now being shifted to graphene composites, primarily with polymer/organic conductors. One promising avenue of research is the development of graphene composites with polymer or organic conductors, which have shown some improvements in thermoelectric performance. However, the achieved “dimensionless figure of merit (ZT)” values of these composites are still far lower than those of common inorganic semiconductors. An alternative approach involves incorporating a very small amount of graphene into inorganic materials to improve their overall thermoelectric properties. These new concepts have successfully addressed the detrimental effects of graphene's intrinsic thermal conductivity, with the added interfaces in the matrix due to the presence of graphene layers working to enhance the properties of the host material. The use of graphene presents a promising solution to the longstanding challenge of developing high-performance and cost-effective thermoelectric materials. This paper discusses these innovative research ideas, highlighting their potential for revolutionizing the field of thermoelectric materials.
Pareto-optimal cycles for power, efficiency and fluctuations of quantum heat engines using reinforcement learning
(American Physical Society, 2023) Erdman, Paolo A.; Rolandi, Alberto; Abiuso, Paolo; Perarnau-Llobet, Martí; Noé, Frank
The full optimization of a quantum heat engine requires operating at high power, high efficiency, and high stability (i.e., low power fluctuations). However, these three objectives cannot be simultaneously optimized—as indicated by the so-called thermodynamic uncertainty relations—and a systematic approach to finding optimal balances between them including power fluctuations has, as yet, been elusive. Here we propose such a general framework to identify Pareto-optimal cycles for driven quantum heat engines that trade off power, efficiency, and fluctuations. We then employ reinforcement learning to identify the Pareto front of a quantum dot-based engine and find abrupt changes in the form of optimal cycles when switching between optimizing two and three objectives. We further derive analytical results in the fast- and slow-driving regimes that accurately describe different regions of the Pareto front.
The oxido clusters of bismuth
(Elsevier, 2023) Whitmire, Kenton H.; Wall, Kathryn
The oxido clusters of bismuth have received increasing attention over the past several decades. This can in part be attributed to the use of bismuth compounds as pharmaceuticals, dating back hundreds of years for treating gastrointestinal disorders and as general antimicrobial and antifungal agents. This is enabled by bismuth's low toxicity compared to its more infamous neighbors in the periodic table. The field received a substantial boost in activity aimed at producing precursor compounds to homo- and heterometallic metal oxides via sol gel syntheses thanks to the discovery of various high TC superconducting bismuth-containing phases. More recently these compounds have shown interesting catalytic, electronic and optical properties. There is a strong resemblance of the structures of the oxido species to solid state bismuth oxides, and the chemistry of the oxido clusters is strongly intertwined with the fundamental coordination chemistry of bismuth, which shows strong Lewis acidity and high coordination numbers. As a result, the oxido clusters of bismuth have proven to have a rich structural chemistry with nuclearities ranging from two to fifty bismuth atoms, and many structures are known that incorporate other metals including the alkali metals, alkaline earth metals, transition metals and lanthanides as part of the oxido core. Compounds with a [Bi6O4(OH)4]6+ core are particularly prevalent, but Bi4, Bi9 and Bi38 structures are also well-represented. The ligand sets that support the formation and stabilization of these structures include a wide variety of organic alkoxides, siloxides, carboxylates, sulfonates, phosphonates and acetylacetonates. Multifunctional ligands have been used for the production of MOF-like structures via hydrothermal methods that can result in discrete bismuth oxido clusters linked via ligand bridges or polymeric bismuth oxido structures decorated with the organic ligands and organized into 1-, 2- or 3-dimensional structures. This review is designed to summarize the synthetic methods used to prepare them, present key aspects of their physical and chemical properties as well as discussing the important features of the structures reported to date. Of significant importance is the obvous blurring of the boundaries between the discrete bismuth oxido clusters that can be described as conventional inorganic coordination compounds, organobismuth oxides and oxido bismuth compounds where the bismuth oxido core is itself a polymer.
State Preparation of Antisymmetrized Geminal Power on a Quantum Computer without Number Projection
(American Chemical Society, 2023) Khamoshi, Armin; Dutta, Rishab; Scuseria, Gustavo E.
The antisymmetrized geminal power (AGP) is equivalent to the number projected Bardeen–Cooper–Schrieffer (PBCS) wave function. It is also an elementary symmetric polynomial (ESP) state. We generalize previous research on deterministically implementing the Dicke state to a state preparation algorithm for an ESP state, or equivalently AGP, on a quantum computer. Our method is deterministic and has polynomial cost, and it does not rely on number symmetry breaking and restoration. We also show that our circuit is equivalent to a disentangled unitary paired coupled cluster operator and a layer of unitary Jastrow operator acting on a single Slater determinant. The method presented herein highlights the ability of disentangled unitary coupled cluster to capture nontrivial entanglement properties that are hardly accessible with traditional Hartree–Fock based electronic structure methods.
Theoretical understanding of evolutionary dynamics on inhomogeneous networks
(IOP Publishing, 2023) Teimouri, Hamid; Khavas, Dorsa Sattari; Spaulding, Cade; Li, Christopher; Kolomeisky, Anatoly B.; Center for Theoretical Biological Physics
Evolution is the main feature of all biological systems that allows populations to change their characteristics over successive generations. A powerful approach to understand evolutionary dynamics is to investigate fixation probabilities and fixation times of novel mutations on networks that mimic biological populations. It is now well established that the structure of such networks can have dramatic effects on evolutionary dynamics. In particular, there are population structures that might amplify the fixation probabilities while simultaneously delaying the fixation events. However, the microscopic origins of such complex evolutionary dynamics remain not well understood. We present here a theoretical investigation of the microscopic mechanisms of mutation fixation processes on inhomogeneous networks. It views evolutionary dynamics as a set of stochastic transitions between discrete states specified by different numbers of mutated cells. By specifically considering star networks, we obtain a comprehensive description of evolutionary dynamics. Our approach allows us to employ physics-inspired free-energy landscape arguments to explain the observed trends in fixation times and fixation probabilities, providing a better microscopic understanding of evolutionary dynamics in complex systems.
Nucleosome Breathing Facilitates the Search for Hidden DNA Sites by Pioneer Transcription Factors
(American Chemical Society, 2023) Mondal, Anupam; Felipe, Cayke; Kolomeisky, Anatoly B.; Center for Theoretical Biological Physics
Transfer of genetic information starts with transcription factors (TFs) binding to specific sites on DNA. But in living cells, DNA is mostly covered by nucleosomes. There are proteins, known as pioneer TFs, that can efficiently reach the DNA sites hidden by nucleosomes, although the underlying mechanisms are not understood. Using the recently proposed idea of interaction-compensation mechanism, we develop a stochastic model for the target search on DNA with nucleosome breathing. It is found that nucleosome breathing can significantly accelerate the search by pioneer TFs in comparison to situations without breathing. We argue that this is the result of the interaction-compensation mechanism that allows proteins to enter the inner nucleosome region through the outer DNA segment. It is suggested that nature optimized pioneer TFs to take advantage of nucleosome breathing. The presented theoretical picture provides a possible microscopic explanation for the successful invasion of nucleosome-buried genes.
Robust formulation of Wick’s theorem for computing matrix elements between Hartree–Fock–Bogoliubov wavefunctions
(AIP Publishing, 2023) Chen, Guo P.; Scuseria, Gustavo E.
Numerical difficulties associated with computing matrix elements of operators between Hartree–Fock–Bogoliubov (HFB) wavefunctions have plagued the development of HFB-based many-body theories for decades. The problem arises from divisions by zero in the standard formulation of the nonorthogonal Wick’s theorem in the limit of vanishing HFB overlap. In this Communication, we present a robust formulation of Wick’s theorem that stays well-behaved regardless of whether the HFB states are orthogonal or not. This new formulation ensures cancellation between the zeros of the overlap and the poles of the Pfaffian, which appears naturally in fermionic systems. Our formula explicitly eliminates self-interaction, which otherwise causes additional numerical challenges. A computationally efficient version of our formalism enables robust symmetry-projected HFB calculations with the same computational cost as mean-field theories. Moreover, we avoid potentially diverging normalization factors by introducing a robust normalization procedure. The resulting formalism treats even and odd number of particles on equal footing and reduces to Hartree–Fock as a natural limit. As proof of concept, we present a numerically stable and accurate solution to a Jordan–Wigner-transformed Hamiltonian, whose singularities motivated the present work. Our robust formulation of Wick’s theorem is a most promising development for methods using quasiparticle vacuum states.
Bacteria-Specific Feature Selection for Enhanced Antimicrobial Peptide Activity Predictions Using Machine-Learning Methods
(American Chemical Society, 2023) Teimouri, Hamid; Medvedeva, Angela; Kolomeisky, Anatoly B.; Center for Theoretical Biological Physics
There are several classes of short peptide molecules, known as antimicrobial peptides (AMPs), which are produced during the immune responses of living organisms against various infections. In recent years, substantial progress has been achieved in applying machine-learning methods to predict the activities of AMPs against bacteria. In most investigated cases, however, the outcome is not bacterium-specific since the specific features of bacteria, such as chemical composition and structure of membranes, are not considered. To overcome this problem, we developed a new computational approach that allowed us to train several supervised machine-learning models using a specific set of data associated with peptides targeting E. coli bacteria. LASSO regression and Support Vector Machine techniques have been utilized to select, among more than 1500 physicochemical descriptors, the most important features that can be used to classify a peptide as antimicrobial or ineffective against E. coli. We then performed the classification of active versus inactive AMPs using the Support Vector classifiers, Logistic Regression, and Random Forest methods. This computational study allows us to make recommendations of how to design more efficient antibacterial drug therapies.
Impregnation of KOAc on PdAu/SiO2 causes Pd-acetate formation and metal restructuring
(Royal Society of Chemistry, 2023) Jacobs, Hunter P.; Elias, Welman C.; Heck, Kimberly N.; Dean, David P.; Dodson, Justin J.; Zhang, Wenqing; Arredondo, Jacob H.; Breckner, Christian J.; Hong, Kiheon; Botello, Christopher R.; Chen, Laiyuan; Mueller, Sean G.; Alexander, Steven R.; Miller, Jeffrey T.; Wong, Michael S.
Potassium-promoted, oxide-supported PdAu is catalytically active for the gas-phase acetoxylation of ethylene to form vinyl acetate monomer (VAM), in which the potassium improves long-term activity and VAM selectivity. The alkali metal is incorporated into the catalyst via wet impregnation of its salt solution, and it is generally assumed that this common catalyst preparation step has no effect on the catalyst structure. However, in this work, we report evidence to the contrary. We synthesized a silica-supported PdAu (PdAu/SiO2, 8 wt% Pd, 4 wt% Au) model catalyst containing Pd-rich PdAu alloy and pure Au phases. Impregnation with potassium acetate (KOAc) aqueous solution and subsequent drying did not cause XRD-detectible changes to the bimetal structure. However, DRIFTS indicated the presence of Pd3(OAc)6 species, which is correlated to up to 2% Pd loss after washing of the dried KOAc-promoted PdAu/SiO2. Carrying out the impregnation step with an AcOH-only solution and subsequent drying caused significant enlargement of the pure Au grain size and generated a smaller amount of Pd3(OAc)6. During co-impregnation of AcOH and KOAc, grain sizes were enlarged slightly, and substantial amounts of K2Pd2(OAc)6 and Pd3(OAc)6 were detected by DRIFTS and correlated to up to 32% Pd loss after washing. Synchrotron XAS analysis showed that approximately half the Pd atoms were oxidized, corroborating the presence of the Pd-acetate species. These results indicate wet-impregnation-induced metal leaching can occur and be substantial during catalyst preparation.
Vitamin B12 and hydrogen atom transfer cooperative catalysis as a hydride nucleophile mimic in epoxide ring opening
(Cell Press, 2023) Funk, Brian E.; Pauze, Martin; Lu, Yen-Chu; Moser, Austin J.; Wolf, Gemma; West, Julian G.
Epoxide ring-opening reactions have long been utilized to furnish alcohol products that are valuable in many subfields of chemistry. While many epoxide-opening reactions are known, the hydrogenative opening of epoxides via ionic means remains challenging because of harsh conditions and reactive hydride nucleophiles. Recent progress has shown that radical chemistry can achieve hydrogenative epoxide ring opening under relatively mild conditions; however, these methods invariably require oxophilic metal catalysts and sensitive reagents. In response to these challenges, we report a new approach to epoxide ring-opening hydrogenation using bio-inspired Earth-abundant vitamin B12 and thiol-centric hydrogen atom transfer (HAT) co-catalysis to produce Markovnikov alcohols under visible light irradiation. This powerful reaction system exhibits a broad substrate scope, including a number of electrophilic and reductively labile functionalities that would otherwise be susceptible to reduction or cleavage by hydride nucleophiles, and preliminary mechanistic experiments are consistent with a radical process.
Enhanced thermoelectricity in Bi-sprayed bismuth sulphide particles
(Elsevier, 2023) Mulla, Rafiq; Kiani, Sajad; White, Alvin Orbaek; Dunnill, Charles W.; Barron, Andrew R.
Bismuth sulphide (Bi2S3), an n-type semiconductor that critically demonstrates the Seebeck effect with Seebeck coefficients of about 300 μVK−1. However, its poor electrical conductivity makes it unsuitable for thermoelectric applications. In this study, we present a facile preparation method for fabricating Bi-sprayed Bi2S3 particles that alters their thermoelectric properties. Samples were created with differing Bi concentrations into the Bi2S3 compound to test for enhanced thermoelectric properties of the resulting Bi/Bi2S3 composites. The incorporation of excess Bi into Bi2S3 significantly improves the compound's electrical conductivity and optimises overall thermoelectric performance. The electrical conductivity of the Bi/Bi2S3 composites improved from 6.5 Scm−1 (for pristine Bi2S3) to 154 Scm−1 (for highest Bi added Bi2S3). Although the Seebeck coefficient of samples decreased with Bi incorporation, a high power factor (∼390 μWm−1K−2) has been achieved for an optimised composition of the composite. Incorporation of metallic Bi has led to an increase in the thermal conductivity of the samples, but the increase is not significant for the optimised composition of the composites where a high thermoelectric performance has been observed. Therefore, enhanced power factor and moderate thermal conductivity have resulted in a peak ZT value of 0.11 at room temperature. The strategy proposed here improves the thermoelectricity in Bi2S3 and shows excellent potential for developing better-performing thermoelectric compounds with excess elemental contents.
An associative memory Hamiltonian model for DNA and nucleosomes
(PLOS, 2023) Lu, Weiqi; Onuchic, José N.; Pierro, Michele Di; Center for Theoretical Biological Physics
A model for DNA and nucleosomes is introduced with the goal of studying chromosomes from a single base level all the way to higher-order chromatin structures. This model, dubbed the Widely Editable Chromatin Model (WEChroM), reproduces the complex mechanics of the double helix including its bending persistence length and twisting persistence length, and the temperature dependence of the former. The WEChroM Hamiltonian is composed of chain connectivity, steric interactions, and associative memory terms representing all remaining interactions leading to the structure, dynamics, and mechanical characteristics of the B-DNA. Several applications of this model are discussed to demonstrate its applicability. WEChroM is used to investigate the behavior of circular DNA in the presence of positive and negative supercoiling. We show that it recapitulates the formation of plectonemes and of structural defects that relax mechanical stress. The model spontaneously manifests an asymmetric behavior with respect to positive or negative supercoiling, similar to what was previously observed in experiments. Additionally, we show that the associative memory Hamiltonian is also capable of reproducing the free energy of partial DNA unwrapping from nucleosomes. WEChroM is designed to emulate the continuously variable mechanical properties of the 10nm fiber and, by virtue of its simplicity, is ready to be scaled up to molecular systems large enough to investigate the structural ensembles of genes. WEChroM is implemented in the OpenMM simulation toolkits and is freely available for public use.
Self-assembling peptides as immunomodulatory biomaterials
(Frontiers Media S.A., 2023) Hernandez, Andrea; Hartgerink, Jeffrey D.; Young, Simon
Self-assembling peptides are a type of biomaterial rapidly emerging in the fields of biomedicine and material sciences due to their promise in biocompatibility and effectiveness at controlled release. These self-assembling peptides can form diverse nanostructures in response to molecular interactions, making them versatile materials. Once assembled, the peptides can mimic biological functions and provide a combinatorial delivery of therapeutics such as cytokines and drugs. These self-assembling peptides are showing success in biomedical settings yet face unique challenges that must be addressed to be widely applied in the clinic. Herein, we describe self-assembling peptides’ characteristics and current applications in immunomodulatory therapeutics.
Slippery Alkoxysilane Coatings for Antifouling Applications
(Amerian Chemical Society, 2023) Apsey, Henry; Hill, Donald; Barron, Andrew R.; Alexander, Shirin
Herein, we report the wettability and antifouling behavior of a range of different siloxane coatings on plastic and glass substrates. The films investigated are prepared using trimethoxysilane precursors with different alkyl chain lengths (1–18 C atoms) in order to study how the nature of the hydrophobic group affects the different parameters used to characterize wettability (contact angles, sliding angles, and contact angle hysteresis). Atomic force microscopy analysis shows that the coatings possess low surface topography [root mean squared roughness (rms) < 50 nm] and are highly transparent as studied using UV–vis spectroscopy. The sliding properties of H2O, CH2I2, methanol, and ethylene glycol were observed to be strongly influenced by the chain length of the alkoxysilane precursor used. The coatings formed from the longer chain analogues show comparable water sliding angles to superhydrophobic surfaces. These coatings show similar performance to analogous alkoxysilane coating-bearing fluorinated groups, indicating that they could act as viable environmentally friendly alternatives to some of the fluorinated films that have been widely adopted. Furthermore, these surfaces are highly durable toward common forms of abrasion and are observed to show low adhesion toward synthetic feces, indicating that their utility extends further than repelling liquids alone. Consequently, these coatings could show promise for potential use in applications in the medical sector where fouling by biological mixtures leads to an unsustainable use of materials.
Directing and Understanding the Translation of a Single Molecule Dipole
(Amerian Chemical Society, 2023) Simpson, Grant J.; García-López, Víctor; Boese, A. Daniel; Tour, James M.; Grill, Leonhard; Smalley-Curl Institute; NanoCarbon Center
Understanding the directed motion of a single molecule on surfaces is not only important in the well-established field of heterogeneous catalysis but also for the design of artificial nanoarchitectures and molecular machines. Here, we report how the tip of a scanning tunneling microscope (STM) can be used to control the translation direction of a single polar molecule. Through the interaction of the molecular dipole with the electric field of the STM junction, it was found that both translations and rotations of the molecule occur. By considering the location of the tip with respect to the axis of the dipole moment, we can deduce the order in which rotation and translation take place. While the molecule–tip interaction dominates, computational results suggest that the translation is influenced by the surface direction along which the motion takes place.
Plate-Like Colloidal Metal Nanoparticles
(Amerian Chemical Society, 2023) Scarabelli, Leonardo; Sun, Muhua; Zhuo, Xiaolu; Yoo, Sungjae; Millstone, Jill E.; Jones, Matthew R.; Liz-Marzán, Luis M.
The pseudo-two-dimensional (2D) morphology of plate-like metal nanoparticles makes them one of the most anisotropic, mechanistically understood, and tunable structures available. Although well-known for their superior plasmonic properties, recent progress in the 2D growth of various other materials has led to an increasingly diverse family of plate-like metal nanoparticles, giving rise to numerous appealing properties and applications. In this review, we summarize recent progress on the solution-phase growth of colloidal plate-like metal nanoparticles, including plasmonic and other metals, with an emphasis on mechanistic insights for different synthetic strategies, the crystallographic habits of different metals, and the use of nanoplates as scaffolds for the synthesis of other derivative structures. We additionally highlight representative self-assembly techniques and provide a brief overview on the attractive properties and unique versatility benefiting from the 2D morphology. Finally, we share our opinions on the existing challenges and future perspectives for plate-like metal nanomaterials.

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