Grain-boundary surface terminations incorporating oxygen vacancies for selectively boosting CO[subsc
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She, Xiaojie↗
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Boosting photovoltaic performance of ternary organic solar cells by integrating a multi-functional guest acceptor
Constructing ternary structure is one of the most effective design strategies to break the efficiency ceiling of traditional binary organic solar cells (OSCs). Here, a new Y-series non-fullerene acceptor (Y-T) featuring 1,3-diethyl-2-thiobarbituric acid (DTBA) end groups is developed as a third component for the classical PM6:Y6 binary system. The champion power conversion efficiency of ternary OSCs is increased from 15.64% to 17.37% via incorporating 10 wt% Y-T, with the simultaneously enhanced open-circuit voltage (Voc) of 0.865 V, a short-circuit current density (Jsc) of 26.90 mA/cm 2 , and a fill factor (FF) of 74.97%. The positive contribution of Y-T in the ternary blend can be ascribed to the improved spectroscopic complementarity and enhanced exciton utilization ratio due to the additional energy transfer process. Moreover, Y-T guest acceptor plays a critical role in adjusting the active layer morphology and facilitating three-dimension phase separation, resulting in a balanced charge transport and enhanced FF of ternary OSCs. Overall, this work provides insight into the molecular design of non-fullerene acceptor and suggest guidelines to rationally select guest component for ternary OSCs.
14 SOLAR ENERGY↗
Boosting the activity of non-platinum group metal electrocatalyst for the reduction of oxygen via dual-ligated atomically dispersed precursors immobilized on carbon supports
This paper describes the use of both atomically dispersed precursors (ADPs) and conductive carbon dispersion towards the synthesis of iron-based single atom electrocatalysts for the oxygen reduction reaction (ORR). For non-platinum group metal (non-PGM) catalysts, single iron, cobalt or manganese atoms coordinated with nitrogen are the most active structures towards the ORR. Achieving a high density of active sites made of single atoms is still challenging, requiring careful controls of pyrolysis to reduce the sintering of metal active sites. Herewith, we present a new strategy to synthesize iron-based single atom ORR electrocatalysts using a two pronged approach. We first designed a dual-ligated metal organic framework (MOF) precursor. This MOF was then immobilized onto Ketjen black carbon that serves as a conductive dispersion medium for creating the highly dispersed single atom sites. In this work, we demonstrate a near complete dispersion of the iron sites without obvious formation of nanoparticles. The activity of the resulting electrocatalyst exhibited an onset potential of 0.96 V and a half-wave potential of 0.84 V vs. reversible hydrogen electrode (RHE).
42 ENGINEERING↗
Non-conformal attractor in boost-invariant plasmas
We study the dissipative evolution of (0+1)-dimensionally expanding media with Bjorken symmetry using the Boltzmann equation for massive particles in relaxation-time approximation. Breaking conformal symmetry by a mass induces a non-zero bulk viscous pressure in the medium. It is shown that even a small mass (in units of the local temperature) drastically modifies the well-known attractor for the shear Reynolds number previously observed in massless systems. For generic nonzero particle mass, neither the shear nor the bulk viscous pressure relax quickly to a non-equilibrium attractor; they approach the hydrodynamic limit only late, at small values of the inverse Reynolds numbers. Only the longitudinal pressure, which is a combination of thermal, shear and bulk viscous pressures, continues to show early approach to a far-off-equilibrium attractor, driven by the rapid longitudinal expansion at early times. Second-order dissipative hydrodynamics based on a gradient expansion around locally isotropic thermal equilibrium fails to reproduce this attractor.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data
Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.
CT↗
Advancing ionomer design to boost interfacial and thin-film proton conductivity via styrene-calix[4]arene-based ionomers
Sub-micrometer-thick ion-conducting polymer (ionomer) layers often suffer from poor ionic conductivity at the substrate/catalyst interface. The weak proton conductivity makes the electrochemical reaction at the cathode of proton-exchange-membrane fuel cells sluggish. To address this, here we report on a class of polystyrene-based ionomers having sub-nanometer-sized, sulfonated macrocyclic calix[4]arene-based pendants (PS-calix). In films with thickness comparable to that of ionomer-based binder layers, the conductivity of PS-calix film (~41 mS/cm) is ~13 times higher than that of the current state-of-the-art ionomer, Nafion. We observe a similar improvement in proton conductivity when PS-calix interfaces with Pt nanoparticles, demonstrating the potential of PS-calix in catalyst ink. Leveraging a favorable interfacial chemical composition, PS-calix enhances proton conduction at the film-substrate interface, a shortcoming of Nafion. Moreover, the water in PS-calix films diffuses faster than bulk water and the water confined in Nafion films, suggesting an important role played by sub-nanometer-sized calix[4]arene cavities in creating unique water/ion transport pathways.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Single-Atom Pt Boosting Electrochemical Nonenzymatic Glucose Sensing on Ni(OH) 2 /N-Doped Graphene
Conventional nanomaterials in electrochemical non-enzymatic sensing face huge challenge due to their complex size-, surface- and composition- dependent catalytic properties and low active site density. In this work, we designed a single-atom Pt supported on Ni(OH) 2 nanoplates/nitrogen-doped graphene (Pt 1 /Ni(OH) 2 /NG) as the first example for constructing a single-atom catalyst based electrochemical non-enzymatic glucose sensor. The resulting Pt 1 /Ni(OH) 2 /NG exhibited a low anode peak potential of 0.48 V and high sensitivity of 220.75 μA mM -1 cm -2 towards glucose, which are 45 mV lower and 12 times higher than those of Ni(OH) 2 , respectively. The catalyst also showed excellent selectivity for several important interferences, short response time of 4.6 s, and high stability over 4 weeks. Experimental and density functional theory (DFT) calculated results reveal that the improved performance of Pt 1 /Ni(OH) 2 /NG could be attributed to stronger binding strength of glucose on single-atom Pt active centers and their surrounding Ni atoms, combined with fast electron transfer ability by the adding of the highly conductive NG. Finally, this research sheds light on the applications of SACs in the field of electrochemical non-enzymatic sensing.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Organizing Chaos: Boosting Thermoelectric Properties by Ordering the Clathrate Framework of Ba 8 Cu 16 As 30
The type I clathrate, Ba 8 Cu 16 As 30 , is reinvestigated and found to have a low-temperature polymorph mP 108-Ba 8 Cu 16 As 30 with ordered Cu and As sites. In situ temperature-dependent powder X-ray diffraction experiments guided synthetic efforts toward the synthesis of the ordered monoclinic ( mP 108) and disordered cubic ( cP 54) polymorphs with high phase purity. While a transition from mP 108-Ba 8 Cu 16 As 30 to cP 54-Ba 8 Cu 16 As 30 is not directly observed, cP 54-Ba 8 Cu 16 As 30 is stabilized through quenching from high temperatures and is confirmed through high-resolution synchrotron powder X-ray diffraction. Further, combined theoretical predictions and experimental observations of the thermoelectric properties of both polymorphs reveal that the ordering of Cu and As atoms in the clathrate framework simultaneously enhances the Seebeck coefficient and electronic conductivity by increasing the hole effective mass and reducing the electronic scattering events. Consequently, the zT of mP 108-Ba 8 Cu 16 As 30 reaches a maximum of 0.2 at 575 K, an order of magnitude higher than that of cP 54-Ba 8 Cu 16 As 30 .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Surface Manipulation on Pt 2.2 Ni(111) Nanocatalysts for Boosting Their ORR Performance in Alkaline Media
We have previously shown that Pt–Ni alloy nano-octahedra with {111} facets exhibit outstanding electrochemical performance in the oxygen reduction reaction (ORR) in acidic media when their surfaces are finely tailored at the atomic level. Here, in this investigation, we further refine the surface structure of Pt 2.2 Ni octahedral nanocatalysts to improve ORR performance in a 0.1 M KOH solution using diverse surface manipulation techniques. Through systematic analysis using electrochemical CO stripping, cyclic voltammetry, and X-ray photoelectron spectroscopy, we examined the surfaces of Pt 2.2 Ni octahedral nanocatalysts pretreated with various methods, including etching in acetic acid or perchloric acid, and subsequent electrochemical activation in an alkaline solution or an acidic solution. Among these treatments, those involving acidic media, particularly electrochemical cycling in acidic electrolytes, demonstrated significantly enhanced ORR activity in 0.1 M KOH. The latter exhibited a mass activity of 2.95 A/mg pt and a specific activity of 8.71 mA/cm 2 at 0.90 V, surpassing state-of-the-art Pt/C by 12-fold and 34-fold, respectively. Furthermore, this identified nanocatalyst displayed robust stability, with negligible activity decay observed after 10,000 cycles. This study suggests that the improved ORR activity can be attributed to the Pt-rich surfaces with well-preserved {111} lattices on the surface-modified Pt–Ni nano-octahedra.
36 MATERIALS SCIENCE↗
Intercalation-Induced Amorphization Boosts Aqueous Magnesium-Ion Storage
The design of aqueous battery cathode materials that can store divalent ions with high capacity and satisfactory reversibility is of great technical importance and challenge. Here, we report that divalent Mg 2+ storage is facilitated by an intercalation-induced amorphization of vanadate electrode materials. Electrokinetic analyses and in situ synchrotron X-ray diffraction and absorption spectroscopy collectively demonstrate that vanadate layered materials (Li–V 3 O 8 ) undergo a structural transformation to amorphization induced by Mg 2+ intercalation, and a reversible restoration of crystalline structure upon Mg 2+ deintercalation. Debye scattering simulations suggest that intercalation-induced turbostratic disorder, especially random rotations, translational shifts, oscillatory motions, or varied interlayer spacing of adjacent V–O molecular layers, could be responsible for the observed amorphization. The highly distorted local structure, in turn, facilitates Mg 2+ intercalation across the vanadate electrode materials, responsible for nearly 3/7 of the total Mg 2+ ions intercalated. The study presented reveals an intriguing relationship between ion transport and the reversible amorphization-to-crystallization dynamics it induces, opening a paradigm for designing advanced aqueous battery electrodes.
36 MATERIALS SCIENCE↗
Copper-Doped Tin Oxides Supported on Mesoporous Carbon Xerogel for Boosting the Electrochemical Reduction of CO 2 to Formate in Bicarbonate Solution Coupled with CO 2
The electrochemical reduction of CO 2 into valuable products at mild reaction conditions and using cheap renewable electrical energy are goals to sustain a low-carbon economy. Among the various CO 2 reduction reaction products, formic acid (FA) has received significant attention because of its low Gibbs free energy input requirement and the simple reduction reaction involving the transfer of 2 electrons and 2 protons. In this work, a copper-doped tin oxide catalyst supported on a mesoporous carbon xerogel was shown to enhance the electrochemical reduction of CO 2 to formate in a bicarbonate solution coupled with CO 2 . We observed that the synergistic SnCu oxides enhance the selectivity toward formate from 58.6% for Sn oxide and 28.7% for Cu oxide to over 71.2% for the SnCu oxides. The observed rate of formate production with SnCu oxide was 2.8 times higher compared to the rate of Cu oxide and about 1.5 times higher than with the Sn oxide catalyst. Our results reveal that selectivity for formate comes partly from the electrolysis of the bicarbonate solution and partly from continuous CO 2 gas purged into the solution. The contribution from the electrolysis of bicarbonate solution ranges from 15% to 40% when the concentration of bicarbonate solution ranges from 100 mM to 1 M. Chronoamperometric measurements for stability revealed that Cu oxide and Sn oxide showed stable current density for less than 30 h while under the same conditions, the stable current density was observed for more than 50 h with SnCu oxide catalyst. Additionally, the selectivity toward formate increased by 6% when the reactor pressure was increased from near ambient pressure to 4 psig. Our lab-scale electrochemical cell with SnCu oxide supported on the mesoporous carbon xerogel enhances the CO 2 solubility, minimizes the precipitation of salts that can degrade the catalytic performance, and suppresses the competitive hydrogen evolution reaction, demonstrating the feasibility of using our catalyst and system for the electrochemical conversion of CO 2 into formate with high selectivity, productivity, and stability. Furthermore, this could have significant implications for the mitigation of CO 2 emissions and the development of a sustainable chemical industry.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture
The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
C 1 Chemistry on Metal Carbide Nanoparticles: Boosting the Conversion of CO 2 and CH 4
The studies described in this Perspective show that transition metal carbide (TMC) nanoparticles can be very useful for the activation of three molecules located at the heart of C 1 chemistry: H 2 , CH 4 , and CO 2 . They also can play a major role in the trapping and conversion of two major greenhouse gases. A combination of experiment and theory has shed light on the physical and chemical properties of these systems, which can be very different from those of bulk carbides. Molecular clusters of these compounds, which can be inserted inside the cages of zeolites or carbon nanotubes, have unsaturated metal and carbon atoms that frequently work in a cooperative way when dealing with hard-to-activate molecules, such as CH 4 and CO 2 . These molecular clusters can evolve into nanoparticles of small to medium size (<15 nm) that have unique carbon/metal ratios and structures not seen in the bulk metal carbides. Even when their structures are cuts from bulk lattices, the TMC nanoparticles have corner or edge atoms that are active for the cleavage and conversion of C–H and C–O bonds. In this paper, we cover experimental and theoretical studies with well-defined metal carbide nanoparticles prepared by different methods, free and supported on diverse substrates. The Perspective ends with a discussion of current challenges and potential applications.
03 NATURAL GAS↗
Quantum Chemical Density Matrix Renormalization Group Method Boosted by Machine Learning
The use of machine learning (ML) to refine low-level theoretical calculations to achieve higher accuracy is a promising and actively evolving approach known as Δ-ML. The density matrix renormalization group (DMRG) is a powerful variational approach widely used for studying strongly correlated quantum systems. High computational efficiency can be achieved without compromising accuracy. Here, we demonstrate the potential of a simple ML model to significantly enhance the performance of the quantum chemical DMRG method.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗