Electrochemical Reduction of Perfluorooctanoic Acid (PFOA): An Experimental and Theoretical Approach.

Perfluorooctanoic acid (PFOA) is an artificial chemical of global concern due to its high environmental persistence and potential human health risk. Electrochemical methods are promising technologies for water treatment because they are efficient, cheap, and scalable. The electrochemical reduction of PFOA is one of the current methodologies. This process leads to defluorination of the carbon chain to hydrogenated products. Here, we describe a mechanistic study of the electrochemical reduction of PFOA in gold electrodes. By using linear sweep voltammetry (LSV), an E0' of -1.80 V vs Ag/AgCl was estimated. Using a scan rate diagnosis, we determined an electron-transfer coefficient (αexp) of 0.37, corresponding to a concerted mechanism. The strong adsorption of PFOA into the gold surface is confirmed by the Langmuir-like isotherm in the absence (KA = 1.89 × 1012 cm3 mol-1) and presence of a negative potential (KA = 3.94 × 107 cm3 mol-1, at -1.40 V vs Ag/AgCl). Based on Marcus-Hush's theory, calculations show a solvent reorganization energy (λ0) of 0.9 eV, suggesting a large electrostatic repulsion between the perfluorinated chain and water. The estimated free energy of the transition state of the electron transfer (ΔG‡ = 2.42 eV) suggests that it is thermodynamically the reaction-limiting step. 19F - 1H NMR, UV-vis, and mass spectrometry studies confirm the displacement of fluorine atoms by hydrogen. Density functional theory (DFT) calculations also support the concerted mechanism for the reductive defluorination of PFOA, in agreement with the experimental values.

Mechanistic Implications of the Varying Susceptibility of PAHs to Pyro-Catalytic Treatment as a Function of Their Ionization Potential and Hydrophobicity.

Transition metal catalysts in soil constituents (e.g., clays) can significantly decrease the pyrolytic treatment temperature and energy requirements for efficient removal of polycyclic aromatic hydrocarbons (PAHs) and, thus, lead to more sustainable remediation of contaminated soils. However, the catalytic mechanism and its rate-limiting steps are not fully understood. Here, we show that PAHs with lower ionization potential (IP) are more easily removed by pyro-catalytic treatment when deposited onto Fe-enriched bentonite (1.8% wt. ion-exchanged content). We used four PAHs with decreasing IP: naphthalene > pyrene > benz(a)anthracene > benzo(g,h,i)perylene. Density functional theory (DFT) calculations showed that lower IP results in stronger PAH adsorption to Fe(III) sites and easier transfer of π-bond electrons from the aromatic ring to Fe(III) at the onset of pyrolysis. We postulate that the formation of aromatic radicals via this direct electron transfer (DET) mechanism is the initiation step of a cascade of aromatic polymerization reactions that eventually convert PAHs to a non-toxic and fertility-preserving char, as we demonstrated earlier. However, IP is inversely correlated with PAH hydrophobicity (log Kow), which may limit access to the Fe(III) catalytic sites (and thus DET) if it increases PAH sorption to soil OM. Thus, ensuring adequate contact between sorbed PAHs and the catalytic reaction centers represents an engineering challenge to achieve faster remediation with a lower carbon footprint via pyro-catalytic treatment.

Method of H2 Transfer Is Vital for Catalytic Hydrodefluorination of Perfluorooctanoic Acid (PFOA).

The efficient transfer of H2 plays a critical role in catalytic hydrogenation, particularly for the removal of recalcitrant contaminants from water. One of the most persistent contaminants, perfluorooctanoic acid (PFOA), was used to investigate how the method of H2 transfer affected the catalytic hydrodefluorination ability of elemental palladium nanoparticles (Pd0NPs). Pd0NPs were synthesized through an in situ autocatalytic reduction of Pd2+ driven by H2 from the membrane. The Pd0 nanoparticles were directly deposited onto the membrane fibers to form the catalyst film. Direct delivery of H2 to Pd0NPs through the walls of nonporous gas transfer membranes enhanced the hydrodefluorination of PFOA, compared to delivering H2 through the headspace. A higher H2 lumen pressure (20 vs 5 psig) also significantly increased the defluorination rate, although 5 psig H2 flux was sufficient for full reductive defluorination of PFOA. Calculations made using density functional theory (DFT) suggest that subsurface hydrogen delivered directly from the membrane increases and accelerates hydrodefluorination by creating a higher coverage of reactive hydrogen species on the Pd0NP catalyst compared to H2 delivery through the headspace. This study documents the crucial role of the H2 transfer method in the catalytic hydrogenation of PFOA and provides mechanistic insights into how membrane delivery accelerates hydrodefluorination.

Direct and continuous generation of pure acetic acid solutions via electrocatalytic carbon monoxide reduction.

Electrochemical CO2 or CO reduction to high-value C2+ liquid fuels is desirable, but its practical application is challenged by impurities from cogenerated liquid products and solutes in liquid electrolytes, which necessitates cost- and energy-intensive downstream separation processes. By coupling rational designs in a Cu catalyst and porous solid electrolyte (PSE) reactor, here we demonstrate a direct and continuous generation of pure acetic acid solutions via electrochemical CO reduction. With optimized edge-to-surface ratio, the Cu nanocube catalyst presents an unprecedented acetate performance in neutral pH with other liquid products greatly suppressed, delivering a maximal acetate Faradaic efficiency of 43%, partial current of 200 mA⋅cm-2, ultrahigh relative purity of up to 98 wt%, and excellent stability of over 150 h continuous operation. Density functional theory simulations reveal the role of stepped sites along the cube edge in promoting the acetate pathway. Additionally, a PSE layer, other than a conventional liquid electrolyte, was designed to separate cathode and anode for efficient ion conductions, while not introducing any impurity ions into generated liquid fuels. Pure acetic acid solutions, with concentrations up to 2 wt% (0.33 M), can be continuously produced by employing the acetate-selective Cu catalyst in our PSE reactor.

Pyro-Catalytic Degradation of Pyrene by Bentonite-Supported Transition Metals: Mechanistic Insights and Trade-Offs with Low Pyrolysis Temperature.

Transition metal catalysts can significantly enhance the pyrolytic remediation of soils contaminated with polycyclic aromatic hydrocarbons (PAHs). Significantly higher pyrene removal efficiency was observed after the pyrolytic treatment of Fe-enriched bentonite (1.8% wt ion-exchanged content) relative to natural bentonite or soil (i.e., 93% vs 48% and 4%) at the unprecedentedly low temperature of 150 °C with only 15 min treatment time. DFT calculations showed that bentonite surfaces with Fe3+ or Cu2+ adsorb pyrene stronger than surfaces with Zn2+ or Na+. Enhanced pyrene adsorption results from increased charge transfer from its aromatic π-bonds to the cation site, which destabilizes pyrene allowing for faster degradation at lower temperatures. UV-Vis and GC-MS analyses revealed pyrene decomposition products in extracts of samples treated at 150 °C, including small aromatic compounds. As the pyrolysis temperature increased above 200 °C, product distribution shifted from extractable compounds to char coating the residue particles. No extractable byproducts were detected after treatment at 400 °C, indicating that char was the final product of pyrene decomposition. Tests with human lung cells showed that extracts of samples pyrolyzed at 150 °C were toxic; thus, high removal efficiency by pyrolytic treatment does not guarantee detoxification. No cytotoxicity was observed for extracts from Fe-bentonite samples treated at 300 °C, inferring that char is an appropriate treatment end point. Overall, we demonstrate that transition metals in clay can catalyze pyrolytic reactions at relatively low temperatures to decrease the energy and contact times required to meet cleanup standards. However, mitigating residual toxicity may require higher pyrolysis temperatures.

Mechanistic Insight into the Photo-Oxidation of Perfluorocarboxylic Acid over Boron Nitride.

Hexagonal boron nitride (hBN) can photocatalytically oxidize and degrade perfluorocarboxylic acids (PFCA), a common member of the per/polyfluoroalkyl substance (PFAS) family of water contaminants. However, the reaction mechanism governing PFCA activation on hBN is not yet understood. Here, we apply electronic grand canonical density functional theory (GC-DFT) to assess the thermodynamic and kinetic favorability of PFCA photo-oxidative activation on hBN: CnF2n+1COO- + h+ → CnF2n+1· + CO2. The oxidation of all PFCA chains is exothermic under illumination with a moderate barrier. However, the longer-chain PFCAs are degraded more effectively because they adsorb on the surface more strongly as a result of increased van der Waals interactions with the hBN surface. The ability of hBN to act as a photocatalyst is unexpected because of its wide band gap. Therefore, we apply both theoretical and experimental analyses to examine possible defects on hBN that could account for its activity. We find that a nitrogen-boron substitutional defect (NB), which generates a mid-gap state, can enhance UVC (ultraviolet C) absorption and PFCA oxidation. This work provides insight into the PFCA oxidation mechanism and reveals engineering strategies to design better photocatalysts for PFCA degradation.

A rapid feature selection method for catalyst design: Iterative Bayesian additive regression trees (iBART).

Feature selection (FS) methods often are used to develop data-driven descriptors (i.e., features) for rapidly predicting the functional properties of a physical or chemical system based on its composition and structure. FS algorithms identify descriptors from a candidate pool (i.e., feature space) built by feature engineering (FE) steps that construct complex features from the system's fundamental physical properties. Recursive FE, which involves repeated FE operations on the feature space, is necessary to build features with sufficient complexity to capture the physical behavior of a system. However, this approach creates a highly correlated feature space that contains millions or billions of candidate features. Such feature spaces are computationally demanding to process using traditional FS approaches that often struggle with strong collinearity. Herein, we address this shortcoming by developing a new method that interleaves the FE and FS steps to progressively build and select powerful descriptors with reduced computational demand. We call this method iterative Bayesian additive regression trees (iBART), as it iterates between FE with unary/binary operators and FS with Bayesian additive regression trees (BART). The capabilities of iBART are illustrated by extracting descriptors for predicting metal-support interactions in catalysis, which we compare to those predicted in our previous work using other state-of-the-art FS methods (i.e., least absolute shrinkage and selection operator + l0, sure independence screening and sparsifying operator, and Bayesian FS). iBART matches the performance of these methods yet uses a fraction of the computational resources because it generates a maximum feature space of size O(102), as opposed to O(106) generated by one-shot FE/FS methods.

Hydrodefluorination of Perfluorooctanoic Acid in the H2-Based Membrane Catalyst-Film Reactor with Platinum Group Metal Nanoparticles: Pathways and Optimal Conditions.

PFAAs (perfluorinated alkyl acids) have become a concern because of their widespread pollution and persistence. A previous study introduced a novel approach for removing and hydrodefluorinating perfluorooctanoic acid (PFOA) using palladium nanoparticles (Pd0NPs) in situ synthesized on H2-gas-transfer membranes. This work focuses on the products, pathways, and optimal catalyst conditions. Kinetic tests tracking PFOA removal, F- release, and hydrodefluorination intermediates documented that PFOA was hydrodefluorinated by a mixture of parallel and stepwise reactions on the Pd0NP surfaces. Slow desorption of defluorination products lowered the catalyst's activity for hydrodefluorination. Of the platinum group metals studied, Pd was overall superior to Pt, Rh, and Ru for hydrodefluorinating PFOA. pH had a strong influence on performance: PFOA was more strongly adsorbed at higher pH, but lower pH promoted defluorination. A membrane catalyst-film reactor (MCfR), containing an optimum loading of 1.2 g/m2 Pd0 for a total Pd amount of 22 mg, removed 3 mg/L PFOA during continuous flow for 90 days, and the removal flux was as high as 4 mg PFOA/m2/d at a steady state. The EPA health advisory level (70 ng/L) also was achieved over the 90 days with the influent PFOA at an environmentally relevant concentration of 500 ng/L. The results document a sustainable catalytic method for the detoxification of PFOA-contaminated water.

Adsorption and Reductive Defluorination of Perfluorooctanoic Acid over Palladium Nanoparticles.

Per- and polyfluoroalkyl substances (PFASs) comprise a group of widespread and recalcitrant contaminants that are attracting increasing concern due to their persistence and adverse health effects. This study evaluated removal of one of the most prevalent PFAS, perfluorooctanoic acid (PFOA), in H2-based membrane catalyst-film reactors (H2-MCfRs) coated with palladium nanoparticles (Pd0NPs). Batch tests documented that Pd0NPs catalyzed hydrodefluorination of PFOA to partially fluorinated and nonfluorinated octanoic acids; the first-order rate constant for PFOA removal was 0.030 h-1, and a maximum defluorination rate was 16 µM/h in our bench-scale MCfR. Continuous-flow tests achieved stable long-term depletion of PFOA to below the EPA health advisory level (70 ng/L) for up to 70 days without catalyst loss or deactivation. Two distinct mechanisms for Pd0-based PFOA removal were identified based on insights from experimental results and density functional theory (DFT) calculations: (1) nonreactive chemisorption of PFOA in a perpendicular orientation on empty metallic surface sites and (2) reactive defluorination promoted by physiosorption of PFOA in a parallel orientation above surface sites populated with activated hydrogen atoms (Hads*). Pd0-based catalytic reduction chemistry and continuous-flow treatment may be broadly applicable to the ambient-temperature destruction of other PFAS compounds.

Theoretical insights into non-oxidative propane dehydrogenation over Fe3C.

Identifying catalysts for non-oxidative propane dehydrogenation has become increasingly important due to the increasing demand for propylene coupled to decreasing propylene production from steam cracking as we shift to lighter hydrocarbon feedstocks. Commercialized propane dehydrogenation (PDH) catalysts are based on Pt or Cr, which are expensive or toxic, respectively. Recent experimental work has demonstrated that earth-abundant and environmentally-benign metals, such as iron, form in situ carbide phases that exhibit good activity and high selectivity for PDH. In this work, we used density functional theory (DFT) to better understand why the PDH reaction is highly selective on Fe3C surfaces. We use ab initio thermodynamics to identify stable Fe3C surface terminations as a function of reaction conditions, which then serve as our models for investigating rate-determining and selectivity-determining kinetic barriers during PDH. We find that carbon-rich surfaces show much higher selectivity for propylene production over competing cracking reactions compared to iron-rich surfaces, which is determined by comparing the propylene desorption barrier to the C-H scission barrier for dehydrogenation steps beyond propylene. Electronic structure analyses of the d-band center and the crystal orbital Hamilton population (COHP) of the carbides demonstrate that the high selectivity of carbon-rich surfaces originates from the disruption of surface Fe ensembles via carbon. Finally, we investigated the role of phosphate in suppressing coke formation and found that the electron-withdrawing character of phosphate destabilizes surface carbon.

The Holy Grail: Chemistry Enabling an Economically Viable CO2 Capture, Utilization, and Storage Strategy.

Technologies for reducing the concentration of CO2 in our atmosphere are essential for mitigating the risks of climate change, and novel chemistry is required for such technologies to work at scale. Here, we highlight challenges that chemists must overcome to realize the Holy Grail of an economically viable strategy for CO2 capture, utilization, and storage.

Theoretical Determination of Band Edge Alignments at the Water-CuInS2(112) Semiconductor Interface.

Knowledge of a semiconductor electrode's band edge alignment is essential for optimizing processes that occur at the semiconductor/electrolyte interface. Photocatalytic processes are particularly sensitive to such alignments, as they govern the transfer of photoexcited electrons or holes from the surface to reactants in the electrolyte solution. Reconstructions of a semiconductor surface during operation, as well as its interaction with the electrolyte solution, must be considered when determining band edge alignment. Here, we employ density functional theory + U theory to assess the stability of reconstructed CuInS2 surfaces, a system which has shown promise for the active and selective photoelectrocatalytic reduction of CO2 to CH3OH. Using many-body Green's function theory combined with calculations of surface work functions, we determine band edge positions of explicitly solvated, reconstructed CuInS2 surfaces. We find that there is a linear relationship between band edge position and net surface dipole, with the most stable solvent/surface structures tending to minimize this dipole because of generally weak interactions between the surface and solvating water molecules. We predict a conduction band minimum (CBM) of the solvated, reconstructed CuInS2 surface of -2.44 eV vs vacuum at the zero-dipole intercept of the dipole/CBM trendline, in reasonable agreement with the experimentally reported CBM position at -2.64 eV vs vacuum. This methodology offers a simplified approach for approximating the band edge positions at complex semiconductor/electrolyte interfaces.

Growth of Stable Surface Oxides on Pt(111) at Near-Ambient Pressures.

Detailed knowledge of the structure and degree of oxidation of platinum surfaces under operando conditions is essential for understanding catalytic performance. However, experimental investigations of platinum surface oxides have been hampered by technical limitations, preventing in situ investigations at relevant pressures. As a result, the time-dependent evolution of oxide formation has only received superficial treatment. In addition, the amorphous structures of many surface oxides have hindered realistic theoretical studies. Using near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) we show that a time scale of hours (t≥4 h) is required for the formation of platinum surface oxides. These experimental observations are consistent with ReaxFF grand canonical Monte Carlo (ReaxFF-GCMC) calculations, predicting the structures and coverages of stable, amorphous surface oxides at temperatures between 430-680 K and an O2 partial pressure of 1 mbar.

Charge Transfer Stabilization of Late Transition Metal Oxide Nanoparticles on a Layered Niobate Support.

Interfacial interactions between late transition metal/metal oxide nanoparticles and oxide supports impact catalytic activity and stability. Here, we report the use of isothermal titration calorimetry (ITC), electron microscopy and density functional theory (DFT) to explore periodic trends in the heats of nanoparticle-support interactions for late transition metal and metal oxide nanoparticles on layered niobate and silicate supports. Data for Co(OH)2, hydroxyiridate-capped IrOx·nH2O, Ni(OH)2, CuO, and Ag2O nanoparticles were added to previously reported data for Rh(OH)3 grown on nanosheets of TBA0.24H0.76Ca2Nb3O10 and a layered silicate. ITC measurements showed stronger bonding energies in the order Ag < Cu ≈ Ni ≈ Co < Rh < Ir on the niobate support, as expected from trends in M-O bond energies. Nanoparticles with exothermic heats of interaction were stabilized against sintering. In contrast, ITC measurements showed endothermic interactions of Cu, Ni, and Rh oxide/hydroxide nanoparticles with the silicate and poor resistance to sintering. These trends in interfacial energies were corroborated by DFT calculations using single-atom and four-atom cluster models of metal/metal oxide nanoparticles. Density of states and charge density difference calculations reveal that strongly bonded metals (Rh, Ir) transfer d-electron density from the adsorbed cluster to niobium atoms in the support; this mixing is absent in weakly binding metals, such as Ag and Au, and in all metals on the layered silicate support. The large differences between the behavior of nanoparticles on niobate and silicate supports highlight the importance of d-orbital interactions between the nanoparticle and support in controlling the nanoparticles' stability.

Illuminating surface atoms in nanoclusters by differential X-ray absorption spectroscopy.

We use differential extended X-ray absorption fine structure (Δ-EXAFS) to monitor the Ar-induced surface restructuring of silica-supported Pd nanoclusters (1 nm diameter) at 77 K. Δ-EXAFS analysis shows 9 ± 2 nearest-neighbor Pd-Pd bonds expand by 0.104 ± 0.005 Å as a result of Ar adsorption. Atomistic molecular dynamics simulations provide evidence for a model in which Ar drives restructuring of under-coordinated Pd atoms, leading to an increased Pd-Pd bond length of surface Pd atoms with no change in overall nearest-neighbor Pd-Pd coordination number. Based on observations from the atomistic simulations, it is likely that under-coordinated atoms are trapped in metastable states at 77 K and Ar provides the kinetic energy needed to overcome the barrier for surface restructuring. Together, experiment and theory highlight the ability of Δ-EXAFS to probe surface atoms of Pd nanoclusters.

Operator-induced structural variable selection for identifying materials genes.

In the emerging field of materials informatics, a fundamental task is to identify physicochemically meaningful descriptors, or materials genes, which are engineered from primary features and a set of elementary algebraic operators through compositions. Standard practice directly analyzes the high-dimensional candidate predictor space in a linear model; statistical analyses are then substantially hampered by the daunting challenge posed by the astronomically large number of correlated predictors with limited sample size. We formulate this problem as variable selection with operator-induced structure (OIS) and propose a new method to achieve unconventional dimension reduction by utilizing the geometry embedded in OIS. Although the model remains linear, we iterate nonparametric variable selection for effective dimension reduction. This enables variable selection based on ab initio primary features, leading to a method that is orders of magnitude faster than existing methods, with improved accuracy. To select the nonparametric module, we discuss a desired performance criterion that is uniquely induced by variable selection with OIS; in particular, we propose to employ a Bayesian Additive Regression Trees (BART)-based variable selection method. Numerical studies show superiority of the proposed method, which continues to exhibit robust performance when the input dimension is out of reach of existing methods. Our analysis of single-atom catalysis identifies physical descriptors that explain the binding energy of metal-support pairs with high explanatory power, leading to interpretable insights to guide the prevention of a notorious problem called sintering and aid catalysis design.

Development of a ReaxFF potential for Pd∕O and application to palladium oxide formation.

Oxide formation on palladium surfaces impacts the activity and selectivity of Pd-based catalysts, which are widely employed under oxygen rich operating conditions. To investigate oxidation processes over Pd catalysts at time and length scales inaccessible to quantum based computational methods, we have developed a Pd∕O interaction potential for the ReaxFF reactive force field. The parameters of the ReaxFF potential were fit against an extensive set of quantum data for both bulk and surface properties. Using the resulting potential, we conducted molecular dynamics simulations of oxide formation on Pd(111), Pd(110), and Pd(100) surfaces. The results demonstrate good agreement with previous experimental observations; oxygen diffusion from the surface to the subsurface occurs faster on the Pd(110) surface than on the Pd(111) and Pd(100) surfaces under comparable conditions at high temperatures and pressures. Additionally, we developed a ReaxFF-based hybrid grand canonical Monte Carlo∕molecular dynamics (GC-MC∕MD) approach to assess the thermodynamic stability of oxide formations. This method is used to derive a theoretical phase diagram for the oxidation of Pd935 clusters in temperatures ranging from 300 K to 1300 K and oxygen pressures ranging from 10(-14) atm to 1 atm. We observe good agreement between experiment and ReaxFF, which validates the Pd∕O interaction potential and demonstrates the feasibility of the hybrid GC-MC∕MD method for deriving theoretical phase diagrams. This GC-MC∕MD method is novel to ReaxFF, and is well suited to studies of supported-metal-oxide catalysts, where the extent of oxidation in metal clusters can significantly influence catalytic activity, selectivity, and stability.

How structural and vibrational features affect optoelectronic properties of non-stoichiometric quantum dots: computational insights.

While stoichiometric quantum dots (QDs) have been well studied, a significant knowledge gap remains in the atomistic understanding of the non-stoichiometric ones, which are predominantly present during the experimental synthesis. Here, we investigate the effect of thermal fluctuations on structural and vibrational properties of non-stoichiometric cadmium selenide (CdSe) nanoclusters: anion-rich (Se-rich) and cation-rich (Cd-rich) using ab initio molecular dynamics (AIMD) simulations. While the excess atoms on the surface fluctuate more for a given QD type, the optical phonon modes are mostly composed of Se atoms dynamics, irrespective of the composition. Moreover, Se-rich QDs have higher bandgap fluctuations compared to Cd-rich QDs, suggesting poor optical properties of Se-rich QDs. Additionally, non-adiabatic molecular dynamics (NAMD) suggests faster non-radiative recombination for Cd-rich QDs. Altogether, this work provides insights into the dynamic electronic properties of non-stoichiometric QDs and proposes a rationale for the observed optical stability and superiority of cation-rich candidates for light emission applications.

Combined Surface-Enhanced Raman and Infrared Absorption Spectroscopies for Streamlined Chemical Detection of Polycyclic Aromatic Hydrocarbon-Derived Compounds.

Polycyclic aromatic hydrocarbons (PAHs) constitute a class of universally prevalent carcinogenic environmental contaminants. It is increasingly recognized, however, that PAHs derivatized with oxygen, sulfur, or nitrogen functional groups are frequently more dangerous than their unfunctionalized counterparts. This much larger family of chemicals─polycyclic aromatic compounds─PACs─is far less well characterized than PAHs. Using surface-enhanced Raman and IR Absorption spectroscopies (SERS + SEIRA) combined on a single substrate, along with density functional theoretical (DFT) calculations, we show that direct chemical detection and identification of PACs at sub-parts-per-billion concentration can be achieved. Focusing our studies on 9,10-anthraquinone, 5,12-tetracenequinone, 9-nitroanthracene, and 1-nitropyrene as model PAC contaminants, detection is made possible by incorporating a hydroxy-functionalized self-assembled monolayer that facilitates hydrogen bonding between analytes and the SERS + SEIRA substrate. 5,12-Tetracenequinone was detected at 0.3 ppb, and the limit of detection was determined to be 0.1 ppb using SEIRA alone. This approach is straightforwardly extendable to other families of analytes and will ultimately facilitate fieldable chemical detection of these dangerous yet largely overlooked environmental contaminants.

Surface Ligands Dictate the Mechanical Properties of Inorganic Nanomaterials.

The ability for organic surface chemistry to influence the properties of inorganic nanomaterials is appreciated in some instances but is poorly understood in terms of mechanical behavior. Here we demonstrate that the global mechanical strength of a silver nanoplate can be modulated according to the local binding enthalpy of its surface ligands. A continuum-based core-shell model for nanoplate deformation shows that the interior of a particle retains bulk-like properties while the surface shell has yield strength values that depend on surface chemistry. Electron diffraction experiments reveal that, relative to the core, atoms at the nanoplate surface undergo lattice expansion and disordering directly related to the coordinating strength of the surface ligand. As a result, plastic deformation of the shell is more difficult, leading to an enhancement of the global mechanical strength of the plate. These results demonstrate a size-dependent coupling between chemistry and mechanics at the nanoscale.