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At least 163 records · Page 9

Selective Reduction of Carbon Dioxide in Water Using [M(bpy2+)(CO)3(I)]2+ (M = Mn, Re) Electrocatalysts with Pendent Cations

Manganese(I) carbonyl complexes are promising electrocatalysts for CO2 reduction, yet their application in homogeneous aqueous media remains limited by poor solubility and selectivity. Here, we report water-soluble Mn(I) and Re(I) complexes fac-[M(bpy2+)(CO)3X]2+ (X = I or Cl), featuring bipyridine ligands functionalized with -Ph-CH2-(NMe3)+ cationic ammonium groups that integrate water solubility with secondary-sphere stabilization. In bicarbonate buffer at pH 6.8, the Mn catalyst is completely selective for CO production at a low overpotential (η = 0.3 V), operating by a protonation-first mechanism with observed rates of ~10 s−1. Pulse radiolysis reveals that the one-electron reduced Mn species undergoes dimerization in the absence of CO2 but uniquely reacts competitively with CO2 through an initial pre-equilibrium followed by fast formation of a dinuclear CO2-bridged species (ΔGo = −12.4 kcal mol−1). At a higher 0.6 V over-potential, a faster reduction-first pathway (~100 s−1) is available upon reduction of the metallo-carboxylic acid intermediate, Mn-CO2H2+; however, this regime is functionally limited by the formation of a resistive, noncatalytic film on the electrode surface. Comparison to the analo-gous water-soluble Re catalyst (kobs = 440 s−1, η = 0.6 V) highlights the distinct mechanistic ad-vantages of earth-abundant Mn in low-potential catalysis. These results demonstrate how cati-onic second-sphere design enables selective, homogeneous CO2 reduction in water while reveal-ing competing radical and electrode-mediated processes that govern catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando Raman spectroscopy uncovers hydroxide and CO species enhance ethanol selectivity during pulsed CO 2 electroreduction

Pulsed CO 2 electroreduction (CO 2 RR) has recently emerged as a facile way to in situ tune the product selectivity, in particular toward ethanol, without re-designing the catalytic system. However, in-depth mechanistic understanding requires comprehensive operando time-resolved studies to identify the kinetics and dynamics of the electrocatalytic interface. Here, we track the adsorbates and the catalyst state of pre-reduced Cu 2 O nanocubes (~30 nm) during pulsed CO 2 RR using sub-second time-resolved operando Raman spectroscopy. By screening a variety of product-steering pulse length conditions, we unravel the critical role of co-adsorbed OH and CO on the Cu surface next to the oxidative formation of Cu-O ad or CuO x /(OH) y species, impacting the kinetics of CO adsorption and boosting the ethanol selectivity. However, a too low OH ad coverage following the formation of bulk-like Cu 2 O induces a significant increase in the C 1 selectivity, while a too high OH ad coverage poisons the surface for C-C coupling. Thus, we unveil the importance of co-adsorbed OH on the alcohol formation under CO 2 RR conditions and thereby, pave the way for improved catalyst design and operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solar-driven selective conversion of millimolar dissolved carbon to fuels with molecular flux generation

Abstract The direct utilization of dissolved inorganic carbon in seawater for CO 2 conversion promises chemical production on-demand and with zero carbon footprint. Photoelectrochemical (PEC) CO 2 reduction (CO 2 R) devices promise the sustainable conversion of dissolved carbon in seawater to carbon products using sunlight as the only energy input. However, the diffusion-dominant transport mechanism and the near-zero concentration of CO 2 (aq) (CO 2 dissolved in aqueous solution) in static seawater has made it extremely challenging to achieve high solar-to-fuel (STF) efficiency and high carbon-product selectivity. Here, where CO 2 (aq) as a reactant generated in situ by acidification of HCO 3 - flows continuously from BiVO 4 photoanodes to Si photocathodes, enabling a single-step conversion of dissolved carbon into products. Our PEC device significantly increases the CO selectivity from 3% to 21%, which approaches the 30% theoretical limit according to multi-physics modeling. Meanwhile, the Si/BiVO 4 PEC CO 2 R device achieved a STF efficiency of 0.71%. Such flow engineering achieves flow-dependent selectivity, rate, and stability in simulated seawater, thus promising practical solar fuel production at scale.

Liu, Bin↗

Chiral induction at the nanoscale and spin selectivity in electron transmission in chiral methylated BEDT-TTF derivatives

Great efforts have been made in the last few decades to realize electronic devices based on organic molecules. A possible approach in this field is to exploit the chirality of organic molecules for the development of spintronic devices, an applicative way to implement the chiral-induced spin selectivity (CISS) effect. In this work we exploit enantiopure tetrathiafulvalene (TTF) derivatives as chiral inducers at the nanoscale. The aim is to make use of TTF's well-known and unique semiconducting properties, to be expressed in the fields of enantio-selectivity and the chiral-induced spin selectivity (CISS) effect. Further, the experimental results shown in this paper further demonstrate how chirality and spin are deeply interrelated, as foreseen within the CISS effect theory, paving the way for the application of TTF derivatives in the field of spintronics. In this work, we demonstrate that tetramethyl-bis(ethylenedithio)-tetrathiafulvalene (TM-BEDT-TTF) (1) behaves as an efficient spin filter, as evidenced by magneto-atomic force microscopy (mc-AFM) measurements. Additionally, it is shown to be effective in transferring chirality to CdS/CdSe core–shell nanoparticles, as inferred from the analysis of circularly resolved photoluminescence spectra. This makes 1 a promising candidate for a variety of applications, ranging from plasmonics to quantum computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Ion pair extractant selective for LiCl and LiBr

Improved methods for achieving the selective extraction of lithium salts from lithium sources, including rocky ores, salt-lake brines, and end-of-life lithium-ion batteries, could help address projected increases in the demand for lithium. Here, we report an ion pair receptor (2) capable of extracting LiCl and LiBr into an organic receiving phase both from the solid state and from aqueous solutions. Ion pair receptor 2 consists of a calix[4]pyrrole framework, which acts as an anion binding site, linked to a phenanthroline cation binding motif via ether linkages. Receptor 2 binds MgBr 2 and CaCl 2 with high selectivity over the corresponding lithium salts in a nonpolar aprotic solvent. The preference for Mg 2+ and Ca 2+ salts is reversed in polar protic media, allowing receptor 2 to complex LiCl and LiBr with high selectivity and affinity in organic media containing methanol or water. The effectiveness of receptor 2 as an extractant for LiCl and LiBr under liquid–liquid extraction (LLE) conditions was found to be enhanced by the presence of other potentially competitive salts in the aqueous source phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hole transport layer selection for stable and efficient carbon electrode-based perovskite solar cells

Perovskite solar cell (PSC) technology has achieved remarkable progress, with champion power conversion efficiencies (PCE) exceeding 26%. However, the long-term stability of PSCs remains a significant barrier to their widespread commercialization. Carbon-based PSCs (C-PSCs) have gained attention as a promising cost-effective and scalable production solution, replacing expensive metal electrodes and offering improved stability. Despite these advantages, C-PSCs face challenges in matching the performance of noble metal-based PSCs, particularly in terms of carrier extraction efficiency and reduced carrier recombination at the carbon/perovskite interface. The selection of hole transport materials (HTMs) is crucial for optimizing this interface, but comprehensive studies on HTM selection for C-PSCs are limited. This study systematically investigated three commonly used hole transport layers (HTLs): Spiro-OMeTAD, CuSCN, and PTAA. Our results show that Spiro-OMeTAD-based C-PSCs exhibit the best overall performance, achieving a PCE of 19.29%. CuSCN-based devices, while lower in efficiency (11.94% PCE), demonstrated superior stability, retaining approximately 60% of their initial performance after 500 hours under ambient conditions. PTAA-based devices achieved a PCE of 12.92% but exhibited significant degradation, maintaining only ∼35% of their original efficiency over the same duration. These findings highlight the importance of selecting HTLs that balance performance and stability and emphasize the need for further optimization to enhance the commercial viability of C-PSCs.

14 SOLAR ENERGY↗

Evolution of size-selected Pt cluster catalysts on prototypical oxide supports

The current quest for new pathways into sustainable, efficient and durable energy conversion technologies makes the used for a fundamental understanding of the atomic-scale phenomena underlying catalytic processes ever more pressing. In this context, characterizing catalyst particles in situ provides valuable information about the evolution of their composition, structure, oxidation state and charge state during an ongoing process. To disentangle the influence of individual parameters – temperature, pressure, gas composition, cluster size, as well as support acidity, redox state and defect density – it is crucial to control them precisely and separately in experiments. At the example of size-selected Pt n clusters – i.e. sub-nm particles defined to the exact number of atoms – on flat oxide supports, we follow their rich evolution phenomena via (synchrotron-based) X-ray photoelectron spectroscopy (XPS) and scanning tunnelling microscopy (STM) during temperature ramps and in various gas environments. Here, we present our experience with these highly defined, yet complicated-to-create samples in ultra-high vacuum (UHV) and at mbar pressures. We discuss their stability during transport to synchrotrons and under reaction conditions on three prototypical oxide supports and show the various phenomena that can be disentangled. Ptn clusters on the non-reducible silicon dioxide, SiO 2 , remain size-selected and show remarkable stability. Doping strongly influences the size-dependent binding energy shifts and changes the Pt response to oxidative and reaction conditions, which we attribute to different cluster geometries: p-type doping leads to wetting, enhanced sinter resistance and a diminished response to oxidative environments, compared to clusters on n-type doped samples. We compare the system with our previous findings of a similar change in dimensionality for Pt 20 clusters on the reducible ceria, CeO 2 (111), support, induced by modulation of its O vacancy density. The Pt n /CeO 2 system is particularly interesting for strategies to stabilize and redisperse Pt clusters dynamically. Finally, we study the evolution of Pt n clusters on another reducible oxide support, magnetite, Fe 3 O 4 (001), in 0.1 mbar alternating redox conditions at RT and elevated temperature. In analogy to findings previously reported for Pt/TiO 2 (110), the clusters either become encapsulated by a thin oxide film via strong metal–support interaction (SMSI) or deeply buried in the magnetite. Overall, our approach of following the evolution of size-selected clusters on oxide supports leads to fundamental atomic-scale insights on nano-scale catalyst materials, on our path to sustainable, dynamic and self-repairing catalysts.

Falling, Lorenz J. [Technical Univ. of Munich (Ger↗

Phase-Selective Fractionation of Lignocellulosic Biomass Using a Lignin-Based Hydrophobic Deep Eutectic Solvent Biphasic System

Lignocellulose fractionation is a critical step in biomass valorization. Herein, we report a hydrophobic deep eutectic solvent (HDES)-mediated biphasic fractionation strategy that enables the simultaneous and selective separation of cellulose, hemicellulose, and lignin in a single process. Lignin-derived HDESs composed of thymol and 2,6-dimethoxyphenol (syringol) were combined with an acidic aqueous phase to create a water-HDES biphasic system, in which lignin was preferentially extracted into the HDES phase, hemicellulose-derived sugars were selectively solubilized in the aqueous phase, and cellulose was retained in the solid residue. Using wheat straw and poplar wood as representative herbaceous and woody biomass feedstocks, the HDES-acid system exhibited strong synergistic effects, achieving delignification up to 69.8% and xylan removal up to 93.6%. Structural characterization confirmed effective disruption of the lignocellulosic matrix and increased cellulose accessibility, resulting in markedly enhanced enzymatic saccharification, with glucose yields up to 96.2% for wheat straw. This work demonstrates a sustainable and efficient HDES-based biphasic fractionation platform that enables phase-selective separation of major lignocellulosic components and provides a foundation for further development of closed-loop biorefinery processes.

09 BIOMASS FUELS↗

An essential and highly selective protein import pathway encoded by nucleus-forming phage

Targeting proteins to specific subcellular destinations is essential in prokaryotes, eukaryotes, and the viruses that infect them. Chimalliviridae phages encapsulate their genomes in a nucleus-like replication compartment composed of the protein chimallin (ChmA) that excludes ribosomes and decouples transcription from translation. These phages selectively partition proteins between the phage nucleus and the bacterial cytoplasm. Currently, the genes and signals that govern selective protein import into the phage nucleus are unknown. Here, we identify two components of this protein import pathway: a species-specific surface-exposed region of a phage intranuclear protein required for nuclear entry and a conserved protein, PicA (Protein importer of chimalliviruses A), that facilitates cargo protein trafficking across the phage nuclear shell. We also identify a defective cargo protein that is targeted to PicA on the nuclear periphery but fails to enter the nucleus, providing insight into the mechanism of nuclear protein trafficking. Using CRISPRi-ART protein expression knockdown of PicA, we show that PicA is essential early in the chimallivirus replication cycle. Together, our results allow us to propose a multistep model for the Protein Import Chimallivirus pathway, where proteins are targeted to PicA by amino acids on their surface and then licensed by PicA for nuclear entry. The divergence in the selectivity of this pathway between closely related chimalliviruses implicates its role as a key player in the evolutionary arms race between competing phages and their hosts.

59 BASIC BIOLOGICAL SCIENCES↗

Water content modulation enables selective ion transport in 2D MXene membranes

Separation membranes are critical for a range of processes, including but not limited to water desalination, chemical and fuel production, and recycling and recovery applications. Fundamentally, there are intrinsic trade-offs between permeability and selectivity. Local water organization and content can impact membrane structure (short- and long-range) in laminar transition metal carbide (MXene) membranes and impact selective ion permeation. Intercalation of chaotropic cesium (Cs + ) ions within the layers reduces the water content in the membrane and at the surface which cannot be found in the intercalation of other ions. Additionally, 3D imaging using focused ion beam scanning electron microscopy showed fewer defects in the Cs-MXene membrane, due to reduced local water content, leading to more efficient ion sieving. X-ray diffraction and density functional theory calculations on the nanochannel structure demonstrated that the chaotropic ion results in the smallest nanochannel size and induces a stronger resistance to water-induced nanochannel swelling. With a narrower nanochannel, the Cs-MXene membrane limits ion transport pathways, resulting in more selective transport of lithium over other metal cations, as evidenced in both experiment and molecular dynamics simulations. In conclusion, our findings highlight the potential for controlling the structural organization of 2D MXene membranes to enable on-demand transport of ions for diverse applications.

36 MATERIALS SCIENCE↗

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

Here, in this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth. The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range. We find that fixing a target density budget of 1,100 deg -2 , the Random Forest approach gives a density of z > 2 targets of 873 deg -2 , and a density of 493 deg -2 of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg 2 . We predict uncertainties on Alcock-Paczynski parameters α ⊥ and α ∥ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ fNL ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ fNL ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

cosmological parameters from LSS↗

Selecting samples of galaxies with fewer Fingers-of-God

The radial positions of galaxies inferred from their measured redshift appear distorted due to their peculiar velocities. We argue that the contribution from stochastic velocities — which gives rise to `Fingers-of-God' (FoG) anisotropy in the inferred maps — does not lend itself to perturbative modelling already on scales targeted by current experiments. To get around this limitation, we propose to remove FoG using data-driven indicators of their abundance that are local in nature and thus avoid selection biases. In particular, we show that the scale where the measured power spectrum quadrupole changes sign is tightly anti-correlated with both the satellite fraction and the velocity dispersion, and can thus be used to select galaxy samples with fewer FoG. In addition, we show that excluding galaxies in haloes more massive than a given mass threshold can help to discard many of the most problematic galaxies. Such selection could be achieved in practice using maps of the thermal Sunyaev-Zel'dovich distortion of the cosmic microwave background frequency spectrum. These techniques could potentially improve reconstructions of the large-scale velocity and displacement fields from the redshift-space positions of galaxies. They may also extend the reach of perturbative models for galaxy clustering, though in practice we find only marginal gains when fitting one-loop EFTofLSS models to simulations with mitigated FoG due to the relevance of other effects entering at two-loop order.

cosmological parameters from LSS↗

Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 < z < 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1 Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗

Reducing model error using optimized galaxy selection: weak lensing cluster mass estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density Σ crit relative modelling bias on the 60-70% level, while maintaining up to 90% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue ‘The evolution of plant metabolism’.

Life Sciences & Biomedicine - Other Topics↗

Minimizing Selection Bias in Inclusive Jets in Heavy-Ion Collisions with Energy Correlators

The first-ever measurement of energy correlators within inclusive jets produced in heavy-ion collisions, revealed by the CMS Collaboration, shows a clear enhancement at large angles relative to the proton-proton (p-p) baseline. However, interpreting this enhancement is complicated due to selection bias from energy loss, which also distorts the energy correlator heavy-ion to p-p ratio in the hadronization region, hindering our understanding of parton/hadron dynamics in a colored medium. In this Letter, we introduce a new ratio of energy correlator observables that removes the leading effects of selection bias from the two-point energy correlator spectrum (E2C). PYTHIA and HERWIG simulations show that the impact of selection bias in the E2C is reduced by an order of magnitude, while sensitivity to any other medium modifications is retained. This quantity can be obtained directly from the experimental measurements presented by CMS, as illustrated in an accompanying note [C. Andres and J. Holguin, arXiv:2409.07526].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On Rank Selection for Nonnegative Matrix Factorization

Rank selection, i.e. the choice of factorization rank, is the first step in constructing Nonnegative Matrix Factorization (NMF) models. It is a long-standing problem which is not unique to NMF, but arises in most models which attempt to decompose data into its underlying components. Since these models are often used in the unsupervised setting, the rank selection problem is further complicated by the lack of ground truth labels. In this paper, we review and empirically evaluate the most commonly used schemes for NMF rank selection.

Eswar, Srinivas [Argonne National Laboratory]↗