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At least 865 records · Page 48

Torsional Flexibility Tuning of Hexa-Carboxylate Ligands to Unlock Distinct Topological Access to Zirconium Metal–Organic Frameworks

Zirconium-based metal–organic frameworks (Zr-MOFs) exhibit remarkable structural diversity and functionality. However, uncovering new topological types within this family remains a considerable challenge today. Herein, we report two new hexa-topic ligands designed through the introduction of torsional flexibility, which enable the construction of two Zr-MOFs featuring rare network topologies. The (4,4′,4″,4‴,4‴′,4‴′′-((2-carboxybenzene-1,3,5-triyl)tris(9H-carbazole-9,3,6-triyl))hexabenzoic acid ligand (BTCH)) was obtained by replacing the rigid triptycene core in the H6PET-1 ligand (4,4′,4″,4‴,4‴′,4‴′′-(9,10-dihydro-9,10-[1,2]benzenoanthracene-2,3,6,7,14,15-hexayl)hexabenzoic acid) with a benzene-tricarbazole unit. Owing to its torsionally flexible core that allows rotational freedom to the arms, this ligand directs the construction of NU-2620 (NU represents Northwestern University), a Zr-MOF with 8-connected Zr6 clusters and the rare nuh topology. Further flexibilization of the carbazole units to benzene rings yielded the even more torsionally flexible 5′,5‴-bis(4-carboxyphenyl)-5″-(4,4″-dicarboxy-[1,1′:3′,1″-terphenyl]-5′-yl)-[1,1′:3′,1″:3″,1‴:3‴,1‴′-quinquephenyl]-4,4‴′-dicarboxylic acid ligand (CCTT), which forms NU-2630 featuring 6-connected clusters and the pcu topology. Both frameworks exhibit good chemical stability, prompting evaluation of their performance in CO2 photoreduction catalysis. Under low-concentration CO2 conditions, NU-2620 displays markedly higher catalytic activity than its benzene-based analogue, NU-2630, thanks to the abundance of photoactive carbazole units within its structure. These results demonstrate that introducing torsional flexibility in high-connected linkers can unlock access to new topologies and accelerates the reticular expansion of Zr-MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High yield production of 3-hydroxypropionic acid using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Biotechnology↗

A unifying equation for fermentation sustainability across the titer-rate-yield landscape

Industrial fermentation is central to the sustainable production of fuels and chemicals, yet commercial viability of emerging technologies hinges on improving fermentation titer, rate, and yield (TRY). How these metrics shape system cost remains difficult to generalize due to complex interactions among feedstocks, fermentation, separations, catalytic upgrading, waste management, and facility design. Here, we systematically map theoretical fermentation performance spaces (formed by all potential TRY combinations) for 32 representative biomanufacturing facilities—spanning distinct choices for feedstocks, fermentation regimes and products, separations, and catalytic upgrading—by simulating and evaluating them (via techno-economic analysis, TEA) under uncertainty (600,000 Monte Carlo simulations) and across TRY combinations (7500 TRY combinations for each of 32 configurations). Across this wide design and thermodynamic simulation space, we find the relationship between fermentation TRY and system cost is captured by a simple, generalizable mathematical equation (R 2 of 0.992 − 1.000 across our simulations; 0.954 − 1.000 when validated against prior studies that used different tools). We use this equation to elucidate key drivers that shape cost sensitivity to fermentation performance, generating widely applicable insights. By demonstrating a unifying relationship governs the impact of fermentation on biomanufacturing economics, this work establishes a foundation for agile, holistically predictive, resource-efficient strategies to prioritize fermentation research and development needs and accelerate commercialization of emerging biomanufacturing technologies.

applied mathematics↗

Kinetic-controlled transformations of group-III arsenide nanocubes

Tracking the structural evolution of colloidal nanocrystals (NCs) facilitates the mechanistic studies of their materials chemistry. NC engineering via phase transformation reveals the chemical and physical determinants that drive lattice-scale dynamic processes such as cation exchange. Here, in this study, we employed NCs to demonstrate the cation exchange process from Cu 3 As to InAs and GaAs within nanocubes. The symmetry conversion in unit cells from cubic Cu 3 As to hexagonal InAs and GaAs can be described using a schematic cellular automaton model, which suggests a simplified cube-to-sphere transition. The strong covalent characteristics of III–V materials highlight the kinetic control that navigates the tailorable transformation through either an isotropic trajectory, leading to hollow structures, or a topotaxial trajectory, with abundant stacking faults. The reconstruction of complex covalent bonds is envisioned as the foundation for the synthesis of NCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗

Unlocking liquid chemisorption in solid matrices: immobilized deep eutectic solvent-ZIF-8 composites for next-generation CO 2 capture

Achieving net-zero emissions by 2050 requires scalable and durable CO 2 capture solutions, with direct air capture (DAC) gaining increasing prominence. Deep eutectic solvents (DESs) have emerged as promising candidates due to their strong chemisorptive properties, but their liquid-phase nature limits integration into solid systems. In this study, we introduce a solid–liquid hybrid approach by immobilizing [TEAB][TEPA] 2 , a highly CO 2 -reactive DES, onto various supports via non-covalent immobilization. This strategy induces solid-like behavior while retaining molecular-level reactivity of the DES. Among the supports including ZIF-8, zeolite Y, zirconia, and alumina, the [TEAB][TEPA] 2 @ZIF-8-56% composite demonstrated promising CO 2 uptake capacity of 2.00 mmol g −1 adsorbent at 1 bar, 1.48 at 0.15 bar, 0.96 at 0.01 bar, and 0.59 at 0.4 mbar. Particularly, we can observe that the chemisorption capacity under 400 ppm conditions is successfully introduced into ZIF-8, whereas pristine ZIF-8 showed negligible uptake under these same conditions. Breakthrough experiments confirmed robust capture behavior under humid conditions. The composite exhibited excellent cycling stability over 100 capture-release cycles, supported by thermogravimetric analysis. In situ DRIFTS verified that the chemisorptive nature of the DES remained intact after immobilization. Additional characterization studies, including FTIR, PXRD, N 2 physisorption, and XPS depth profiling, revealed partial DES infiltration and strong interfacial interactions. Comparative results using alumina-based composites underscored the importance of microporosity in stability. Finally, these findings suggest that DES-MOF composites hold promise as carbon capture materials, bridging liquid-phase functionality and solid-state robustness.

Yoo, Yunsung [Northwestern Univ., Evanston, IL (Un↗

Mixed-anion electrolytes: from bulk speciation to interfacial dynamics in divalent metal electrodeposition

Mixing anions is emerging as a promising strategy for multivalent electrolyte design, allowing for adjustment of the solvation structure of bulk cations and enhancing the efficiency of electrochemical processes (e.g. metal deposition for batteries and catalysis). Further progress in electrolyte development requires a fundamental understanding of how tailored electrolyte speciation in mixed anion systems can modify the dynamic electrochemical interface during metal cycling. In this study, we present an anode-focused mechanistic study of exemplar Mg electrolytes containing three different secondary anions, correlating electrochemical behavior with bulk speciation and operando interfacial dynamics. Electrospray Ionization-Mass Spectrometry (ESI-MS) results reveal a general trend of forming mixed anion contact ion pairs (CIPs) across various anions, with the extent of ion pairing influenced by the association strength of the secondary anion. Operando multiharmonic electrochemical quartz crystal microbalance with dissipation (EQCM-D) reveals how these bulk species influence interfacial mass uptake, viscoelasticity, and solvent-coupled hydrodynamic behavior during deposition and stripping. The results indicate that Mg-containing ion pairs and solvated complexes shape adsorption, nucleation, and deposit growth, leading to distinct anion-dependent interphases ranging from more permeable, solvent-coupled layers to relatively compact and rigid deposits. This work establishes a quantitative link between bulk speciation and interfacial dynamics in divalent metal electrodeposition and provides mechanistic guidance for electrolyte design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of the dynamic charge susceptibility near the charge density wave transition in ErTe 3

A charge density wave (CDW) is a phase of matter characterized by a periodic modulation of valence electron density coupled with lattice distortion. Its formation is closely tied to the dynamical charge susceptibility, χ(q, ω) , which reflects the collective electron dynamics of the material. Despite decades of study, χ(q, ω) near a CDW transition has never been measured at nonzero momentum, q, with meV energy resolution. Here, we investigate the canonical CDW transition in ErTe 3 using momentum-resolved electron energy loss spectroscopy, a technique uniquely sensitive to valence band charge excitations. Unlike phonons, which soften via the Kohn anomaly, we find the electronic excitations exhibit purely relaxational dynamics well described by a diffusive model, with the diffusivity peaking just below the critical temperature, T C1 . Additionally, we report for the first time a divergence in the real part of χ(q, ω) in the static limit (ω → 0), a long-predicted hallmark of CDWs. Unexpectedly, this divergence occurs as T → 0, with only a weak thermodynamic signature at T = T C1 . Our study necessitates a reexamination of the traditional description of CDW formation in quantum materials.

M-EELS↗

Characterization of the Cherenkov Photon Background for Low-noise Silicon Detectors in Space

Future space observatories that seek to perform imaging and spectroscopy of faint astronomical sources will require ultra-low-noise detectors that are sensitive over a broad wavelength range. Silicon charge-coupled devices (CCDs), such as EMCCDs, skipper CCDs, multi-amplifier sensing CCDs, and single-electron sensitive read out CCDs have demonstrated the ability to detect and measure single photons from X-ray energies to near the silicon band gap (∼1.1 μm), making them candidate technologies for this application. Here, in this context, we study a relatively unexplored source of low-energy background coming from Cherenkov radiation produced by energetic cosmic rays traversing a silicon detector. We present a model for Cherenkov photon production and absorption that is calibrated to laboratory data, and we use this model to characterize the residual background rate for ultra-low-noise silicon detectors in space. We study how the Cherenkov background rate depends on detector thickness, variations in solar activity, and the contribution of heavy cosmic ray species (Z > 2). We find that for thick silicon detectors, such as those required to achieve high quantum efficiency at long wavelengths, the rate of cosmic-ray-induced Cherenkov photon production is comparable to other detector and astrophysical backgrounds. We apply our Cherenkov background model to simulated spectroscopic observations of extra-solar planets, and we find that thick detectors continue to outperform their thinner counterparts at longer wavelengths despite a larger Cherenkov background rate. Furthermore, we find that minimal masking of cosmic-ray tracks continues to maximize the signal-to-noise ratio of very faint sources despite the existence of extended halos of Cherenkov photons.

Astronomical detectors↗

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. Furthermore, these innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗

Improving galaxy cluster selection with the outskirt stellar mass of galaxies

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, 𝑆 8 . However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. Here, in this work, we evaluate an alternative cluster proxy, outskirt stellar mass, 𝑀 out , defined as the total stellar mass within a [50, 100] kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, 𝜆, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a 𝑀 out selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of 𝑀 out and 𝜆 with halo mass. Our results show 𝑀 out has a scatter consistent with 𝜆, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find 𝜆-selected samples introduce features into the measured Δ⁢Σ signal that are not well fit by a log-normal scatter only model, absent in 𝑀 out selected samples. Our findings suggest that 𝑀 out offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the 𝜆 −𝑀 out scaling relation to be 0.49 ±0.02 and 0.38 ±0.09.

79 ASTRONOMY AND ASTROPHYSICS↗

Evolution of chirality from transverse wobbling in 135 Pr

Chirality is a distinct signature that characterizes triaxial shapes in nuclei. We report the first observation of chirality in the nucleus 135 Pr using a high-statistics Gammasphere experiment with the 123 Sb( 16 O, 4n) 135 Pr reaction. Two chiral-partner bands with the configuration π(1h11/2 )1 ⊗ ν(1h 11/2 ) −2 have been identified in this nucleus. Angular distribution analyses of the ΔI = 1 transitions connecting the two bands reveal a dominant dipole character, and quasiparticle triaxial rotor model calculations show good agreement with the data. Since the simultaneous observation of chirality and transverse wobbling in 135 Pr relies critically on these angular distribution results, we also address and refute the experimental and theoretical criticisms raised in a recent work by Lv et al., presenting additional evidence that further strengthens our interpretation. Furthermore, this marks the first observation of both hallmarks of triaxiality—chirality and wobbling—in the same nucleus.

90 ≤ A ≤ 149↗

Heterogeneous Dynamics in Shear Thickening Colloids Revealed by Intrinsic Heterodyne Correlation Spectroscopy

Shear induced frictional networks have been proposed to be responsible for the emergence of discontinuous shear thickening (DST) in complex fluids. However, little experimental evidence exists to support this model directly. Here, in this study, using x-ray photon correlation spectroscopy (XPCS), we show the existence of an intrinsic heterodyne feature during shear cessation, which originates from the relative motion of mobile particles against an aggregated or jammed network induced by shear thickening. Upon removing the shear, the shear stress dissipates rather quickly in a two-step fashion, whereas the heterogeneous particle dynamics persist much longer with the relative velocity decaying slowly with time as 𝑡 −1 . More importantly, both continuous shear thickening (CST) and DST show similar heterodyne features, indicating the intrinsic mechanisms causing shear thickening are similar in nature

Complex fluid↗

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

Flutter

The following repositories are a set of libraries that are needed for applications that are being developed for users of the Accelerator control system. The programming language used is Dart and for the user interface use the Flutter framework. URL for code repositories: - https://github.com/fermi-ad/flutter-controls-core - https://github.com/fermi-ad/flutter-controls-plotting - https://github.com/fermi-ad/flutter-controls-auth - https://github.com/fermi-ad/flutter-gql-acsys - https://github.com/fermi-ad/flutter-gql-faas - https://github.com/fermi-ad/dart-gql-acsys - https://github.com/fermi-ad/dart-explicit-imports - https://github.com/fermi-ad/dart-gql-faas - https://github.com/fermi-ad/design-system

Neswold, Rich [Fermi National Accelerator Laborato↗

Automated, reliable, and efficient continental-scale replication of 7.3 petabytes of computational simulation data: A case study

We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) computational simulation data from Lawrence Livermore National Laboratory (LLNL) in California to Argonne National Laboratory (ANL) in Illinois and Oak Ridge National Laboratory (ORNL) in Tennessee—a task motivated by a need for increased reliability, capacity, and performance. This task presented significant challenges: the need to move 29 million files twice under time pressure from aging storage hardware; a source file system bottleneck limiting throughput to 1.5 GB/s; frequent site maintenance windows; and the need for complete reliability at scale. We addressed these challenges using a simple replication tool that invoked Globus to transfer large bundles of files while tracking progress in a database, dynamically rerouting transfers to work around maintenance periods and file system limitations. Under the covers, Globus organized transfers to make efficient use of the high-speed Energy Sciences network (ESnet) and the data transfer nodes deployed at participating sites, and also addressed security, integrity checking, and recovery from a variety of transient failures. This success demonstrates the considerable benefits that can accrue from the adoption of performant data replication infrastructure. The replication tool is available at https://github.com/esgf2-us/data-replication-tools.

Globus↗