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At least 181 records · Page 10

Charged-particle production as a function of the relative transverse activity classifier in pp, p–Pb, and Pb–Pb collisions at the LHC

Measurements of charged-particle production in pp, p–Pb, and Pb–Pb collisions in the toward, away, and transverse regions with the ALICE detector are discussed. These regions are defined event-by-event relative to the azimuthal direction of the charged trigger particle, which is the reconstructed particle with the largest transverse momentum $(p^{trig}_T)$ in the range 8 < $p^{trig}_T$< 15 GeV/c. The toward and away regions contain the primary and recoil jets, respectively; both regions are accompanied by the underlying event (UE). In contrast, the transverse region perpendicular to the direction of the trigger particle is dominated by the so-called UE dynamics, and includes also contributions from initial- and final-state radiation. The relative transverse activity classifier, $R_T = N^T_{ch}/\langle N^T_{ch}\rangle$, is used to group events according to their UE activity, where $N^T_{ch}$ is the charged-particle multiplicity per event in the transverse region and $\langle N^T_{ch}\rangle$ is the mean value over the whole analysed sample. The energy dependence of the R T distributions in pp collisions at $\sqrt{s_{NN}}$ = 2.76, 5.02, 7, and 13 TeV is reported, exploring the Koba-Nielsen-Olesen (KNO) scaling properties of the multiplicity distributions. The first measurements of charged-particle p T spectra as a function of R T in the three azimuthal regions in pp, p–Pb, and Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV are also reported. Data are compared with predictions obtained from the event generators PYTHIA 8 and EPOS LHC. This set of measurements is expected to contribute to the understanding of the origin of collective-like effects in small collision systems (pp and p–Pb).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The PTPN2/PTPN1 inhibitor ABBV-CLS-484 unleashes potent anti-tumour immunity

Immune checkpoint blockade is effective for some patients with cancer, but most are refractory to current immunotherapies and new approaches are needed to overcome resistance. The protein tyrosine phosphatases PTPN2 and PTPN1 are central regulators of inflammation, and their genetic deletion in either tumour cells or immune cells promotes anti-tumour immunity. However, phosphatases are challenging drug targets; in particular, the active site has been considered undruggable. Here we present the discovery and characterization of ABBV-CLS-484 (AC484), a first-in-class, orally bioavailable, potent PTPN2 and PTPN1 active-site inhibitor. AC484 treatment in vitro amplifies the response to interferon and promotes the activation and function of several immune cell subsets. In mouse models of cancer resistant to PD-1 blockade, AC484 monotherapy generates potent anti-tumour immunity. We show that AC484 inflames the tumour microenvironment and promotes natural killer cell and CD8 + T cell function by enhancing JAK–STAT signalling and reducing T cell dysfunction. Inhibitors of PTPN2 and PTPN1 offer a promising new strategy for cancer immunotherapy and are currently being evaluated in patients with advanced solid tumours (ClinicalTrials.gov identifier NCT04777994). More broadly, our study shows that small-molecule inhibitors of key intracellular immune regulators can achieve efficacy comparable to or exceeding that of antibody-based immune checkpoint blockade in preclinical models. Finally, to our knowledge, AC484 represents the first active-site phosphatase inhibitor to enter clinical evaluation for cancer immunotherapy and may pave the way for additional therapeutics that target this important class of enzymes.

60 APPLIED LIFE SCIENCES↗

Small Molecule Activation with Intramolecular “Inverse” Frustrated Lewis Pairs

The intramolecular “inverse” frustrated Lewis pairs (FLPs) of general formula 1-BR 2 -2-[(Me 2 N) 2 C=N]-C 6 H 4 (3-6) [BR 2 = BMes 2 (3), BC 12 H 8 , (4), BBN (5), BBNO (6)] were synthesized and structurally characterized by multinuclear NMR spectroscopy and X-ray analysis. Furthermore, these novel types of pre-organized FLPs, featuring strongly basic guanidino units rigidly linked to weakly Lewis acidic boryl moieties via an ortho-phenylene linker, are capable of activating H-H, C-H, N-H, O-H, Si-H, B-H and C=O bonds. 4 and 5 deprotonated terminal alkynes to form the zwitterionic borates 1-(RC≡C-BR 2 )-2-[(Me 2 N) 2 C=NH]-C 6 H 4 (R = Ph, H) and reacted with ammonia, BnNH 2 and pyrrolidine, to generate the adducts 1-(R 2 HN→BR 2 )-2-[(Me 2 N) 2 C=NH]-C 6 H 4 , where the N-H functionality is activated by intramolecular H-bond interactions. In addition, 5 was found to rapidly add across the double bond of H 2 CO, PhCHO and PhNCO to form cyclic zwitterionic guanidinium borates in excellent yields. Likewise, 5 is capable of cleaving H 2 , HBPin and PhSiH 3 to form various amino boranes. Collectively, the results demonstrate that these new types of intramolecular FLPs featuring weakly Lewis acidic boryl and strongly basic guanidino moieties are as potent as conventional intramolecular FLPs with strongly Lewis acidic units in activating small molecules.

08 HYDROGEN↗

Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗

Baltic Sea coastal sediment-bound eukaryotes have increased year-round activities under predicted climate change related warming

Climate change related warming is a serious environmental problem attributed to anthropogenic activities, causing ocean water temperatures to rise in the coastal marine ecosystem since the last century. This particularly affects benthic microbial communities, which are crucial for biogeochemical cycles. While bacterial communities have received considerable scientific attention, the benthic eukaryotic community response to climate change remains relatively overlooked. In this study, sediments were sampled from a heated (average 5°C increase over the whole year for over 50 years) and a control (contemporary conditions) Baltic Sea bay during four different seasons across a year. RNA transcript counts were then used to investigate eukaryotic community changes under long-term warming. The composition of active species in the heated and control bay sediment eukaryotic communities differed, which was mainly attributed to salinity and temperature. The family level RNA transcript alpha diversity in the heated bay was higher during May but lower in November, compared with the control bay, suggesting altered seasonal activity patterns and dynamics. In addition, structures of the active eukaryotic communities varied between the two bays during the same season. Hence, this study revealed that long-term warming can change seasonality in eukaryotic diversity patterns. Relative abundances and transcript expression comparisons between bays suggested that some taxa that now have lower mRNA transcripts numbers could be favored by future warming. Furthermore, long-term warming can lead to a more active metabolism in these communities throughout the year, such as higher transcript numbers associated with diatom energy production and protein synthesis in the heated bay during winter. In all, these data can help predict how future global warming will affect the ecology and metabolism of eukaryotic community in coastal sediments.

59 BASIC BIOLOGICAL SCIENCES↗

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗

Active learning with multifidelity modeling for efficient rare event simulation

Here, while multifidelity modeling provides a cost-effective way to conduct uncertainty quantification with computationally expensive models, much greater efficiency can be achieved by adaptively deciding the number of required high-fidelity (HF) simulations, depending on the type and complexity of the problem and the desired accuracy in the results. We propose a framework for active learning with multifidelity modeling emphasizing the efficient estimation of rare events. Our framework works by fusing a low-fidelity (LF) prediction with an HF-inferred correction, filtering the corrected LF prediction to decide whether to call the high-fidelity model, and for enhanced subsequent accuracy, adapting the correction for the LF prediction after every HF model call. The framework does not make any assumptions as to the LF model type or its correlations with the HF model. In addition, for improved robustness when estimating smaller failure probabilities, we propose using dynamic active learning functions that decide when to call the HF model. We demonstrate our framework using several academic case studies (including some high-dimensional problems) and two finite element model case studies: estimating Navier-Stokes velocities using the Stokes approximation and estimating stresses in a transversely isotropic model subjected to displacements via a coarsely meshed isotropic model. Across these case studies, not only did the proposed framework estimate the failure probabilities accurately, but compared with either Monte Carlo or a standard variance reduction method, it also required only a small fraction of the calls to the HF model.

42 ENGINEERING↗

Reviewing clinical considerations and guideline recommendations of C1 inhibitor prophylaxis for hereditary angioedema

Abstract Background Hereditary angioedema (HAE), a rare disease that is characterized by painful and recurring non‐allergic swelling episodes, is caused by the deficiency or dysfunction of C1 inhibitor (C1INH) protein. A comprehensive HAE management plan may require long‐term prophylaxis (LTP) in addition to on‐demand treatment to help “normalize” patients' lives so that they may fully engage in work, school, family, and leisure activities. Aim The main objective of this narrative review is to provide an overview of updated guideline recommendations specific to LTP of HAE and discuss clinical considerations and pharmacologic management options, with a focus on C1INH. Materials and Methods The authors reviewed relevant HAE literature for current recommendations regarding LTP and the role of C1NH. Results Acute HAE attacks are treated with on‐demand medication; however, there is a consensus that LTP should routinely be considered for risk reduction and prevention of future episodes. The 2017 World Allergy Organization/European Academy of Allergy and Clinical Immunology guidelines recommend that all patients with HAE be evaluated for LTP routinely and the 2020 HAE Association (HAEA) guidelines emphasize that the decision to use LTP should not be based on rigid criteria, but rather should be based on individual patient needs. Both guidelines recommend C1INH as first‐line/preferred therapy for LTP in a range of patient types including adults, children/adolescents, and pregnant/lactating patients. The HAEA also recommends the kallikrein inhibitor, lanadelumab, as a first‐line option for LTP. HAE pathway‐specific agents for LTP have not been associated with notable safety concerns. Discussion Plasma‐derived C1INH has been available for 40+ years in Europe and impacts multiple targets within the HAE pathway. C1INH has been used for on‐demand treatment and LTP. A subcutaneous formulation of plasma‐derived C1INH is approved for LTP and produces functional C1INH activity levels consistently above the threshold needed for protection from HAE attacks. Other pathway‐specific options for LTP include the plasma kallikrein inhibitors, lanadelumab‐flyo and berotralstat, approved for adults and pediatric patients aged ≥12 years. C1INH is approved for adults and pediatric patients aged ≥6 years. Conclusion Assessing the need for LTP is vital in the ongoing dialogue between clinicians and patients, as both disease‐related factors and patient preferences may change over time. Among available options for LTP, plasma‐derived C1INH is the broadly recommended first‐line option for LTP in patients with HAE, including pregnant/lactating women and pediatric patients (≥6 years).

Anderson, John↗

Systematic Influence of Electronic Modification of Ligands on the Catalytic Rate of Water Oxidation by a Single-Site Ru-Based Catalyst

Catalytic water oxidation is an important process for the development of clean energy solutions and energy storage. Despite the significant number of reports on active catalysts, systematic control of the catalytic activity remains elusive. In this study, descriptors are explored that can be correlated with catalytic activity. [Ru(tpy)(pic) 2 (H 2 O)](NO 3 ) 2 and [Ru(EtO-tpy)(pic) 2 (H 2 O)](NO 3 ) 2 (where tpy=2,2': 6',2“-terpyridine, EtO-tpy=4'-(ethoxy)-2,':6',2”-terpyridine, pic=4-picoline) are synthesized and characterized by NMR, UV/Vis, EPR, resonance Raman, and X-ray absorption spectroscopy, and electrochemical analysis. Addition of the ethoxy group increases the catalytic activity in chemically driven and photocatalytic water oxidation. Thus, the effect of the electron-donating group known for the [Ru(tpy)(bpy)(H 2 O)] 2+ family is transferable to architectures with a tpy ligand trans to the Ru-oxo unit. Under catalytic conditions, [Ru(EtO-tpy)(pic) 2 (H 2 O)](NO 3 ) 2 displays new spectroscopic signals tentatively assigned to a peroxo intermediate. In conclusion, reaction pathways were analyzed by using DFT calculations. [Ru(EtO-tpy)(pic) 2 (H 2 O)](NO 3 ) 2 is found to be one of the most active catalysts functioning by a water nucleophilic attack mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bio‐Based Piezo‐ and Thermoresistive Photocurable Sensing Materials from Acrylated Epoxidized Soybean Oil

Abstract Bio‐based photocurable polymers are increasingly in demand as environmentally friendly materials for advanced applications. Together with functional fillers, these represent a next step for the generation of functional and active smart materials, compatible with additive manufacturing technologies. Herein, acrylated epoxidized soybean oil (AESO) mixed with different amounts of reduced graphene oxide (rGO) up to 6 wt% in order to obtain UV‐curable piezoresistive and thermoresistive materials, is reported. It is shown that the addition of rGO to AESO hinders the curing process, but always maintains double bond conversions higher than 50%. Composites are characterized by a good dispersion of micrometric filler clusters. Further, the thermal stabilities are close to 300 °C and crosslinking degrees are above 1.75 mmol cm –3 . The Young modulus of the composites decreases with the addition of the rGO fillers, in particular for the higher filler contents, and electrical conductivities up to 0.13 S m –1 are obtained for the composites with the highest rGO content. UV‐curable composites with piezoresistive and thermoresistive responses suitable for applications are thus obtained, characterized by gauge factors around 26 for deformations up to 2% and maximum thermoresistive sensitivity of S = 0.43, values similar to the values obtained for petroleum‐based materials.

Mendes‐Felipe, Cristian↗

Highly durable fuel cell electrocatalyst with low-loading Pt-Co nanoparticles dispersed over single-atom Pt-Co-N-Graphene nanofiber

The limited durability of Pt electrocatalysis toward cathodic oxygen reduction reaction remains challenging, yet crucial for the development of Proton Exchange Membrane Fuel Cell. Here, we present a rational design of a robust catalyst consisting of PtCo nanoparticles supported on Pt-Co-N-graphene nanofiber prepared through electrospun Cobalt-Metal-Organic-Framework. The catalyst delivers unprecedented mass activity of 2.48 A·mgPt -1 , and retains 80% of initial value after 60,000 Accelerated-Stress-Test cycles. Operando X-ray absorption spectroscopies show that the electronic configurations of Pt sites in PtCo and Co sites in Co-N4 in the hybrid catalyst are modified toward high catalytic activities. Density Functional Theory unveils that the enhanced curvature of the substrate induced by the morphology engineering lowers the reaction thermodynamic barrier on Co-N4 sites, favoring the formation of H2O and suppressing that of H2O2. This result along with the strong affinity of PtCo nanoparticles to the Pt-Co-N-graphene fiber endows the catalyst an exceptional durability.

acidic electrolyte↗

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark↗

Cross-reactive immunogenicity of group A streptococcal vaccines designed using a recurrent neural network to identify conserved M protein linear epitopes

The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal sequence of the protein defines the more than 200 M types of Strep A and also contains epitopes that elicit opsonic antibodies, some of which cross-react with heterologous M types. Current efforts to develop broadly protective M protein-based vaccines are directed at identifying potential cross-protective epitopes located in the N-terminal regions of cluster-related M proteins for use as vaccine antigens. In this study, we have used a comprehensive approach using the recurrent neural network ABCpred and IEDB epitope conservancy analysis tools to predict 16 residue linear B-cell epitopes from 117 clinically relevant M types of Strep A (~88% of global Strep A infections). Furthermore, to examine the immunogenicity of these epitope-based vaccines, nine peptides that together shared ≥60% sequence identity with 37 heterologous M proteins were incorporated into two recombinant hybrid protein vaccines, in which the epitopes were repeated 2 or 3 times, respectively. The combined immune responses of immunized rabbits showed that the vaccines elicited significant levels of antibodies against all nine vaccine epitopes present in homologous N-terminal 1–50 amino acid synthetic M peptides, as well as cross-reactive antibodies against 16 of 37 heterologous M peptides predicted to contain similar epitopes. The epitope-specificity of the cross-reactive antibodies was confirmed by ELISA inhibition assays and functional opsonic activity was assayed in HL-60-based bactericidal assays. The results provide important information for the future design of broadly protective M protein-based Strep A vaccines.

60 APPLIED LIFE SCIENCES↗

Structure–Activity Relationships in Ether-Functionalized Solid-State Metal–Organic Framework Electrolytes

The structure–property relationships of metal–organic framework (MOF)-based solid-state electrolytes are not well understood. Herein, a systematic investigation of 12 Zr(IV)-based UiO-66 MOFs with varying ether-chain functional groups was carried out to elucidate the critical microscopic interactions that facilitate improved solid-state electrolyte performance. Enhanced sampling molecular dynamics (MD) simulations were employed and revealed a three-tier ion hopping mechanism: linker–linker hopping, linker-counterion hopping, and counterion-counterion hopping. Detailed structural analysis of the MD trajectories revealed that the chemistry and morphology of the linker groups affect the relative stability and population distribution of the electrolyte components, such that crown-ether-based linker groups enhance the probability of extended, low-barrier ion percolation pathways. As a result, we were able to tune the ionic conductivities by rationally manipulating the counterion distributions, linker binding strengths, and the configurational entropy (multivariability of the linkers). The resulting performance of these MOF-based solid-state electrolytes was significantly enhanced, with a methoxy-functionalized framework (UiO-66-L1 100 ) achieving high ionic conductivities of 2.32 × 10 –4 S/cm and 2.07 × 10 –3 S/cm at 30 °C and 90 °C, respectively, an order of magnitude greater than other all-solid-state MOF electrolyte systems. The electrolyte stability was evaluated with LiIn|LPSCl|MOF:LiTFSI|LPSCl|LiIn symmetric cells, showing excellent Li plating/stripping processes for over 2 months.

36 MATERIALS SCIENCE↗

Microwave-Driven Nonoxidative and Selective Conversion of Methane to Ethylene over Mn-Based Catalysts

Recent advancements in microwave-driven nonoxidative catalytic synthesis of C 2 H 4 from CH 4 coupling offer a promising, energy-efficient, and eco-friendly alternative to conventional methods, where selective heating under microwave irradiation enables comparable conversions at substantially lower bulk temperatures and shorter reaction times. This study explores the performance of an MnO X -based catalyst supported on CeO 2 and HY zeolite (silica-toalumina ratio = 5.1) for the nonoxidative coupling of CH 4 (NOCM) under microwave irradiation. Inspired by the well-established efficacy of MnO X catalyst in oxidative CH 4 coupling (OCM), their application in NOCM has also shown significant performance. The catalytic system achieved 15% CH 4 conversion and 99% selectivity toward C 2 hydrocarbons and maintained 64% selectivity toward C 2 H 4 surpassing the yields reported in the literature even at higher temperatures (700−1000 °C). Catalyst performance was correlated with measurements by in situ Raman spectroscopy, and additional characterizations were performed using H 2 −temperature programmed reduction , NH 3 −temperature programmed desorption, and BET surface area analysis to understand structural changes during the reactions. These findings suggested that Mn functions as active sites for CH 4 activation in nonoxidative environments while also promoting efficient C−C coupling under microwave irradiation.

Catalysts↗

Development and Characterization of Electrodes for Surface-Specific Attenuated Total Reflection Two-Dimensional Infrared Spectroelectrochemistry

Electrochemical interfaces still have remaining mysteries surrounding the interfacial region of the electrical double layer, despite being prevalent throughout the energy and water remediation industries. The electrical double layer is where many important dynamic processes such as catalysis and electron transfer occur. The goal of this work is to study the electrical double layer with two-dimensional infrared (2D IR) spectroscopy to experimentally access the details of the structural dynamics of this complex environment. However, there are several experimental challenges to applying 2D IR spectroscopy to this application, such as assuring the surface specificity of the spectrum, optimizing the signal strength while minimizing spectral distortions from dispersion and Fano line shapes, and selecting electrode materials that are both sufficiently IR compatible and conductive. Here we will discuss various considerations when designing 2D IR experiments of electrode interfaces utilizing several substrates and experimental configurations and demonstrate a robust method for 2D IR experiments of electrode interfaces under applied potential that combines nonconducting Si ATR wafers with conductive ITO and thin nanostructured films of plasmonically active Au functionalized with 3-mercapto-2-butanone (MCB). We show that layered electrodes on thin Si ATR wafers with MCB are sensitive to applied potential and that the distortions in the linear and 2D IR spectra are heavily dependent on the morphology of the Au surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Titanium-, Nitrogen-Doped Carbon Flowers Catalyze Electrochemical Nitrate Reduction Reaction to Ammonia

An emerging design heuristic for electrochemical nitrate reduction (NO 3 RR) catalysts is synthesizing electron-deficient sites to facilitate binding of electron-rich NO 3 – . However, this rule has rarely been applied to metal-, nitrogen-doped carbon (MNC) catalysts. Titanium (Ti), with low electronegativity and high NO 3 RR reactivity, is a compelling MNC candidate. To date, atomically dispersed TiN x motifs have eluded synthesis due to the strong oxophilicity of Ti. Here, in this work, we leverage nitrogen-rich carbon flowers (CF) to overcome synthetic challenges and produce Ti-, N-doped carbon flower (TiCF) catalysts. Advanced materials characterization demonstrates that TiCF catalysts are a mixed phase material with 3/4 of Ti atoms in TiO 2 -like nanoparticles and 1/4 of Ti atoms in novel, atomically dispersed TiN x sites. TiCF achieves 61 ± 7% NH 3 -selectivity at −0.70 V vs RHE and 14 ± 5 mA/cm 2 to NH 3 formation (| j NH 3 |) at −0.85 V vs RHE in (0.1 M NaOH + 0.1 M NaNO 3 + 0.45 M Na 2 SO 4 ) electrolyte. Control studies show both CF morphology and Ti sites are essential for high NO 3 RR activity. Density functional theory calculations attribute the NO3RR reactivity to TiN x , which facilitates multiple bond formation with surface intermediates to promote favorable NH3 synthesis pathways. Thus, TiCF exhibits 60× higher | j NH 3 | values than bulk Ti and NH 3 yield rates (>0.06 mmol NH 3 /h/cm 2 ) that are competitive with state-of-the-art MNC catalysts (e.g., FeNC, CuNC). TiCF introduces a new class of Ti electrocatalysts, advancing the MNC design space and sustainable NH 3 production.

ammonia↗