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Abstract Nanoconfined fluids, particularly water, govern subsurface geochemistry, yet the molecular-level mechanisms by which mineral surfaces dictate confined water structure and mobility remain poorly resolved. Here, we combine solution- and solid-state proton (1H) NMR spectroscopy, NMR relaxometry, modulated-gradient spin–echo (MGSE) NMR diffusometry, infrared spectroscopy, and molecular dynamics simulations to demonstrate that surface hydroxyls drive the structural and dynamic differentiation of water in imogolite nanotubes. In saturated suspensions, we observe the coexistence of distinct water 1H environments, each exhibiting significantly reduced mobility, which we attribute to strong interactions with the imogolite surfaces. As more mobile water is removed, long-range water diffusivity in the fibrous solid samples slows to 1.6 × 10–10 m2·s–1 while local fluctuations increase to 3.4 × 10–8 m2·s–1, indicating a significant increase in molecular restriction through surface interactions. Together, our experiments reveal three coexisting populations with varied structures and mobilities, all distinct from liquid bulk water. We resolve a persistent solid-like interfacial layer strongly bound to surface hydroxyls, characterized by an unusually short T2 (<1 ms), and a very close effective 1H–1H distance of ∼1.55 Å between water and the inner-surface silanol group. An inner-core population occupying the inner cavity exhibits an intermediate dynamic regime with restricted axial diffusion, while outer-surface water associated with aluminum hydroxyls retains relatively higher mobility. These results experimentally substantiate a hierarchy of water populations in imogolite and show how surface chemistry dictates the structures and dynamics of confined water.

A decay and timing detector for superheavy elements has been developed at Lawrence Berkeley National Laboratory with the goal to become the main measurement detector of FIONA. It combines a double-sided silicon strip detector that provides decay energy and position information with a microchannel plate detector which determines the implantation time of the nuclei on the detector through the detection of secondary electrons emitted from the silicon detector upon impact. This new setup was simulated, constructed and tested offline, in a proof-of-principle setup using a beam of 216Po + , the results of which are presented in this work. The new detector provides, for the first time in FIONA, sensitivity to isotopes beyond α emitters (and fissioning isotopes) and decay time information.

EXO-200 was a leading double beta decay experiment consisting of a single-phase, enriched liquid xenon time projection chamber filled with an admixture of 80.672% ^{136}Xe and 19.098% ^{134}Xe. The detector operated at the Waste Isolation Pilot Plant between 2010 and 2018 and was designed to search for double beta decay of ^{136}Xe. Data were acquired in two phases separated by a period of detector upgrades. We report on the search for 0νββ and 2νββ decay of ^{134}Xe with Phase II EXO-200 data, with median 90% CL exclusion sensitivity to half-life T_{1/2}^{0ν}≥3.7×10^{23}  yr and T_{1/2}^{2ν}≥2.6×10^{21}  yr, respectively. No statistically significant signal is observed for either decay mode. We set a world-leading lower limit on the half-life of the neutrinoless decay mode of ^{134}Xe of T_{1/2}^{0ν}≥8.7×10^{23} (90% CL) and the second strongest constraint on the two-neutrino decay of T_{1/2}^{2ν}≥2.9×10^{21} (90% CL), a threefold improvement over the EXO-200 Phase I measurement. New constraints are also set for the 2νββ and 0νββ decays of ^{134}Xe to the lowest excited state of ^{134}Ba.

Lithium extraction from clay deposits is typically hampered by low lithium grades and the high capital and energy demands of conventional processing. We report an ambient temperature electrochemical leaching method that bypasses high-temperature roasting and concentrated-acid leaching, directly liberating 93% of lithium from low-grade hectorite in 24 h at 1 V, with 77% Faradaic efficiency, an energy intensity of 3.91 MWh/t lithium carbonate equivalent (LCE). Utilizing a carbon-mineral composite slurry electrode strategy we achieve electron-driven lattice deconstruction through iron oxidation coupled with proton uptake to drive lithium deintercalation, offering a new strategy for low-temperature critical-metal recovery. A preliminary cost analysis highlights pathways to achieving cost intensities below $3000/t LCE. Challenges remain in improving current density, extraction kinetics, and demonstrating process scalability, however, this work establishes a foundation for effective electrochemical lithium extraction from abundant but previously uneconomical clay deposits.

CRISPR interference (CRISPRi) has emerged as a valuable tool for redirecting metabolic flux to enhance bioproduction. However, its application is often constrained by two challenges: (i) rationally identifying effective gene targets for downregulation and (ii) efficiently constructing multiplexed CRISPRi systems. In this study, we address both challenges by integrating a computational prioritization tool with a versatile assembly method for building multiplexed CRISPRi systems. FluxRETAP (Flux-Reaction Target Prioritization) accurately identified gene targets whose knockdown led to substantial increase of isoprenol titers in Pseudomonas putida KT2440, outperforming a conventional non-computational, pathway-guided target selection. The highest isoprenol titer of nearly 1.5 g/L was achieved by knocking down PP_4118 (a gene encoding α-ketoglutarate dehydrogenase). The use of VAMMPIRE (Versatile Assembly Method for MultiPlexing CRISPRi-mediated downREgulation) enabled accurate assembly of CRISPRi constructs containing up to five sgRNA arrays, reducing context dependency and achieving uniform, position-independent gene downregulation. The integration of FluxRETAP and VAMMPIRE has the potential to advance metabolic engineering by rapidly identifying CRISPRi-mediated knockdowns and knockdown combinations that enhance bioproduction titers, with potential applicability to other microbial systems.

In macromolecular structure refinement, the low observation-to-parameter ratio and the lack of high-resolution data are countered by using a priori information in the form of restraints. Having accurate geometries of the chemical entities in the sample is paramount for generating accurate chemical restraints and, therefore, accurate macromolecular structures. In particular, it is desirable to have accurate restraints for known and novel ligand entities. Quantum mechanics (QM) can minimize the energy of a ligand by adjusting its geometry, and these geometries can be used to generate restraints for macromolecular refinement. This article describes a library of approximately 37 000 small molecules extracted from the Chemical Component Dictionary in the Protein Data Bank and minimized by density-functional QM. The library includes restraint files for use in crystallography or cryo-EM refinement, along with files suitable for molecular-dynamics simulation. Because the geometries are validated using the Cambridge Structural Database, the restraints library provides users with both functional restraints and minimized geometries. This work also provides procedures for generating new and accurate restraints.

The continued emergence of pathogens, whether novel, re-emerging, or engineered, poses a persistent global biosecurity and public health challenge. Recent outbreaks, including COVID-19, Lassa fever, Marburg virus, mpox, and avian influenza, underscore the urgent need for robust systems that enable rapid surveillance, early diagnosis, and timely countermeasures before widespread human transmission occurs. In this article, we focus on early detection technologies and systematically evaluate current diagnostic and sensing modalities. We highlight sequencing and spectroscopy as two complementary approaches capable of providing broad, agnostic detection and rich biological insight. Our analysis emphasizes that scientific innovation alone is insufficient: effective preparedness also requires improved data curation, integration, and sharing to build AI-ready resources that accelerate future responses. We argue for coordinated advances in both technological capabilities and supporting infrastructure to enable the rapid identification and characterization of emerging pathogens and to fully leverage modern science against evolving infectious threats.

Lithium (Li) and magnesium (Mg) are designated as critical mineral materials (CMM) due to their essential roles in clean energy technologies. However, extracting high-purity Li⁺ from brine remains a formidable challenge owing to the presence of Mg²⁺, a physicochemical similar ion that often exists in excess. Here, we introduce a polyoxoniobate-based "Mg-PONb sponge" that enables ultraselective and rapid Li⁺/Mg²⁺ separation across an exceptionally broad range of Mg/Li ratios (0.02 to 200.63). This framework achieves >99.9% Mg²⁺ removal with negligible Li⁺ loss in under 1 min, yielding Li⁺/Mg²⁺ selectivity values exceeding 5000. The sponge demonstrates excellent recyclability, maintaining >99% Mg²⁺ rejection and Li⁺ permeability across five regeneration cycles without structural degradation. Mechanistic investigations reveal that selective Mg²⁺ capture originates from strong coordination with terminal oxygens on the PONb cluster, driving rapid formation of porous Mg-PONb frameworks. This work presents a generalizable, scalable strategy for Li⁺/Mg²⁺ separation and offers a sustainable path toward enhanced Li and Mg recovery from complex brine sources.

The schemes of the Samarskii type are simple modifications of the upwind scheme. We use them on the Shishkin mesh and discuss their advantages over the upwind scheme when applied to the linear one-dimensional singularly perturbed convection–diffusion problem. One of the advantages is that the Samarskii-type schemes have exact first-order accuracy uniform in the perturbation parameter, as opposed to the upwind scheme which is almost first-order uniformly accurate because its accuracy is diminished by logarithmic factors. Although this is not a new result, we re-emphasize it in the paper. We also demonstrate another advantage, that the Samarskii-type schemes are almost second-order uniformly accurate on the layer component of the solution. Motivated by this fact, we present a further improvement of the numerical method.