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At least 145 records · Page 8

SMEFT ATLAS: The landscape beyond the Standard Model

The Standard Model Effective Field Theory (SMEFT) based on the unbroken gauge group SU(3) 𝐶 ⊗SU(2) 𝐿 ⊗U(1) 𝑌 and containing only particles of the Standard Model (SM) has developed in the last decade to a mature field. It is the framework to be used in the energy gap from scales sufficiently higher than the electroweak scale up to the lowest energy scale at which new particles show up. We summarize the present status of this theory with a particular emphasize on its role in the indirect search for new physics (NP). While flavour physics of both quarks and leptons is the main topic of our review, we also discuss electric dipole moments, anomalous magnetic moments (𝑔−2) 𝜇,𝑒 , 𝑍-pole observables, Higgs observables and high-𝑝𝑇 scattering processes within the SMEFT. We group the observables into ten classes and list for each class the most relevant operators and the corresponding renormalization group equations (RGEs). We exhibit the correlations between different classes implied both by the operator mixing and the SU(2) 𝐿 gauge symmetry. Our main goal is to provide an insight into the complicated operator structure of this framework which hopefully will facilitate the identification of valid ultraviolet completions behind possible anomalies observed in future data. Numerous colourful charts, and 85 tables, while representing rather complicated RG evolution from the NP scale down to the electroweak scale, beautify the involved SMEFT landscape. Over 1000 references to the literature underline the importance and the popularity of this field. We discuss both top-down and bottom-up approaches as well as their interplay. This allows us eventually to present an atlas of different landscapes beyond the SM that includes heavy gauge bosons and scalars, vector-like quarks and leptons and leptoquarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Beyond-mean-field approaches for nuclear neutrinoless double beta decay in the standard mechanism

Nuclear weak decays provide important probes to fundamental symmetries in nature. A precise description of these processes in atomic nuclei requires comprehensive knowledge on both the strong and weak interactions in the nuclear medium and on the dynamics of quantum many-body systems. In particular, an observation of the hypothetical double beta decay without emission of neutrinos (0νββ) would unambiguously demonstrate the Majorana nature of neutrinos and the existence of the lepton-number-violation process. It would also provide unique information on the ordering and absolute scale of neutrino masses. The next-generation tonne-scale experiments with sensitivity up to 10 28 years after a few years of running will probably provide a definite answer to these fundamental questions based on our current knowledge on the nuclear matrix element (NME), the precise determination of which is a challenge to nuclear theory. Beyond-mean-field approaches have been frequently adapted for the study of nuclear structure and decay throughout the nuclear chart for several decades. In this review, we summarize the status of beyond-mean-field calculations of the NMEs of 0νββ decay assuming the standard mechanism of an exchange of light Majorana neutrinos. In conclusion, the challenges and prospects in the extension and application of beyond-mean-field approaches for 0νββ decay are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laser spectroscopy for the study of exotic nuclei

Investigation into the properties and structure of unstable nuclei far from stability is a key avenue of research in modern nuclear physics. These efforts are motivated by the continual observation of unexpected structure phenomena in nuclei with unusual proton-to-neutron ratios. In recent decades, laser spectroscopy techniques have made significant contributions in our understanding of exotic nuclei in different mass regions encompassing almost the entire nuclear chart. This is achieved through determining multiple fundamental properties of nuclear ground and isomeric states, such as nuclear spins, magnetic dipole and electric quadrupole moments and charge radii, via the measurement of hyperfine structures and isotope shifts in the atomic or ionic spectra of the nuclei of interest. These properties offer prominent tests of recently developed state-of-the-art nuclear theory and help to stimulate new developments in improving the many-body methods and nucleon–nucleon interactions at the core of these models. With the aim of exploring more exotic short-lived nuclei located ever closer to the proton and neutron driplines, laser spectroscopy techniques, with their continuous technological developments towards higher resolution and higher sensitivity, are extensively employed at current- and next-generation radioactive ion beam facilities worldwide. Ongoing efforts in parallel promise to improve the availability of these even more exotic species at next-generation facilities. Very recently, an innovative application of laser spectroscopy on molecules containing short-lived nuclei has been demonstrated offering additional opportunities for several fields of research, e.g. fundamental symmetry studies and astrophysics. Here, in this review, the basic nuclear properties measurable with laser spectroscopy will be introduced. How these observables are associated with nuclear structure and nucleon–nucleon interactions will be discussed. Following this, a general overview of different laser spectroscopy methods will be given with particular emphasis on technical advancements reported in recent years. The main focus of this article is to review the numerous highlights that have resulted from studying exotic nuclei in different mass regions with laser spectroscopy techniques since the last edition in this series. Finally, the challenges facing the field in addition to future opportunities will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Band inversion-driven warping and high valley degeneracy

Band inversion is a physical phenomenon that can warp the band structure in topological insulators, generating multiple electronic valleys for conducting carriers. However, the conditions under which band inversion induces warping are not well understood. Here, we derive two general rules that must be satisfied for band warping to occur in centrosymmetric and non-magnetic topological insulators: (1) bands must be sufficiently inverted, and (2) secondary bands must have opposite parity and be close in energy to the band edges. We chart the valley degeneracies that can emerge from band inversion in each of the 11 centrosymmetric point groups, revealing that an increase in the valley degeneracy between 2- and 48-fold is possible from band inversion. The generalized rules offer a unique band engineering approach by capitalizing on the non-trivial electronic structures of topological insulators.

36 MATERIALS SCIENCE↗

Experimental pub crawl from Rayleigh–Bénard to magnetostrophic convection

The interplay between convective, rotational and magnetic forces defines the dynamics within the electrically conducting regions of planets and stars. Yet their triadic effects are separated from one another in most studies, arguably due to the richness of each subset. In a single laboratory experiment, we apply a fixed heat flux, two different magnetic field strengths and one rotation rate, allowing us to chart a continuous path through Rayleigh–Bénard convection (RBC), two regimes of magnetoconvection, rotating convection and two regimes of rotating magnetoconvection, before finishing back at RBC. Dynamically rapid transitions are determined to exist between jump rope vortex states, thermoelectrically driven magnetoprecessional modes, mixed wall- and oscillatory-mode rotating convection and a novel magnetostrophic wall mode. Thus, our laboratory ‘pub crawl’ provides a coherent intercomparison of the broadly varying responses arising as a function of the magnetorotational forces imposed on a liquid-metal convection system.

42 ENGINEERING↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlated Ion Transport Governed by Dynamic Local Structure in High Concentration and Localized High Concentration Electrolytes

Understanding the dynamics of cluster formation and network percolation provides the mechanistic link between microscopic solvation structure and transport in concentrated electrolytes, including localized high-concentration electrolytes (LHCEs). Although recent studies have shown LHCEs to form micelle-like aggregates at specific compositions, a quantitative understanding of how solvation structures and transport properties depend on salt–solvent–diluent ratios remains limited. Here, we integrate molecular dynamics with Onsager transport analyses to chart the evolution of solvation microstructure and associated ionic transport in LiFSI/DMC/TTE, achieving good agreement with experimental conductivities across composition. We show that micelle formation arises from a dynamic instability of the cation–anion network, and that network percolation is the primary determinant of conductivity. Two compositional thresholds emerge: A critical network concentration (CNC) and a critical micelle concentration (CMC) that delineate transitions from extended percolating networks to micelle-like clusters and then to fragments. These structural transitions rationalize the nonintuitive conductivity decrease at intermediate dilution despite monotonically decreasing viscosity and provide composition-level design rules for LHCEs.

Mohanakrishnan, Rohith Srinivaas [University of Ca↗

Bound and Continuum Intersubband Transitions in Colloidal Quantum Wells

Quantum well intersubband transitions are critical for quantum cascade lasers and infrared photodetectors. Control of band offsets allows bound-to-bound intersubband transitions, with confinement of both initial and final states, and bound-to-continuum transitions, in which only the initial state is energetically confined within the potential well. Both types of transitions are also achieved in colloidal CdSe wells by changing the heterostructure shell. Bare wells have narrow intersubband transitions spanning the near-infrared spectrum following effective mass predictions. Atomically precise core/shells enable a readily adjusted potential well for electrons. For CdSe/ZnS, bound-to-bound transitions are narrow and redshift with shell thickness. By contrast, broad bound-to-continuum absorptions are found in CdSe/CdS. Due to small conduction band offsets, higher conduction band states of the well are more delocalized into the CdS shell. In conclusion, these measurements provide unique data to understand the electronic structure of colloidal quantum wells and chart a path to atomically precise optoelectronic materials for the mid-infrared.

colloidal atomic layer deposition↗

Rh → Sb Interactions Supported by Tris(8-quinolyl)antimony Ligands

The study of ambiphilic systems combining L-type and Z-type ligands within the same construct has emerged as a field of active investigation, especially in the cases of ligands containing a group 13 element as a σ-acceptor for transition metals. (1) Parallel to these developments, several groups have investigated more atypical systems in which the Z-type ligand is a group 15 element. (2) Our contributions to this area have focused on the use of phosphinostibine ligands for the generation of transition metal complexes in which the antimony moiety acts as a Z-type ligand. (1d,3) We have shown that the magnitude of the resulting M → Sb interaction can be readily modulated by the oxidation state of the antimony atom (4) as well as its charge which can be manipulated by abstraction of anionic ligands. (5) Our work has also shown that these effects can be leveraged to enhance the catalytic properties of the transition metal center. (4,5) Some of the simplest systems that we have investigated are those resulting from the reaction of platinum dichloride with the bis- or tris-phosphinostibines ClSb(o-dppp) 2 and Sb(o-dppp) 3 , respectively (o-dppp = o-(Ph 2 P)C 6 H 4 ). These reactions proceed by oxidative insertion of the stibine into a Pt- Cl bond to produce complexes A and B, (6) respectively (Chart 1). Reasoning that the properties of these complexes may also be influenced by the nature of the L-type buttresses, we have now questioned whether stibines featuring nitrogen donor ligands could also display the redox noninnocence of their phosphine counterparts and support the formation of such complexes. Following up on some of our work with ambiphilic tellurium-quinoline ligands, (7) we now report on the reaction of tris-(8-quinolyl)stibines (8) toward (MeCN) 3 RhCl 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating Polymer Binder Entanglement in Freestanding Sulfide Solid-State Electrolyte Membranes

This study advances the development of flexible, sheet-type sulfide solid-state electrolytes (SSEs) for use in all-solid-state batteries, emphasizing the important and previously insufficiently investigated role of polymer binder entanglement. Here, the molecular weight of polymer binders is pivotal in crafting robust, freestanding SSE films. Our research uncovers a dual impact: higher molecular weight binders bolster the structural integrity of SSE films but elevate grain boundary resistance and diminish critical current density, whereas lower molecular weight poly(isobutylene) films, despite their more uniform distribution, lack the essential strain hardening or strength for sustained active material contact. Crucially, full cells employing higher molecular weight binders demonstrate improved discharge capacity retention, contrasting sharply with the notable capacity degradation in lower molecular weight cells. Our findings not only deepen the comprehension of binder influences in solid-state batteries but also chart a course for refining all-solid-state battery technologies, a key stride for the future of energy storage solutions.

25 ENERGY STORAGE↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Ligand-Functionalized Polymer Membranes for Selective Ion Separations

Selective ion separations are central to technologies spanning water purification, resource recovery, and clean energy. Conventional polymer membranes, which rely on steric hindrance or Donnan exclusion, struggle to discriminate between chemically similar ions in high-ionic-strength environments. Ligand-functionalized membranes offer a transformative strategy by embedding molecular recognition directly into polymer matrices, enabling selective complexation and transport. Here, this Viewpoint highlights the structure–function relationships underlying ligand-mediated ion separation, emphasizing the interplay of dehydration penalties, ligand coordination, and nanoscale confinement. We discuss design principles, denticity, donor identity, rigidity, and spatial organization, alongside the permeability–selectivity trade-off, multicomponent effects, and stability challenges. Finally, we outline emerging strategies, from bioinspired ligands to computationally guided design, that chart a path toward next-generation membranes for precise and energy-efficient ion separations.

ions↗

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Potential of Hydrogeodesy to Address Water-Related and Sustainability Challenges

Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water-related and sustainability sciences. Addressing this need, we combine a meta-analysis of over 3,000 articles to chart the range, trends, and applications of satellite-based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta-analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water-related and sustainability sciences in order to exploit its full potential.

54 ENVIRONMENTAL SCIENCES↗

Advancing the Representation of Human Actions in Large‐Scale Hydrological Models: Challenges and Future Research Directions

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.

catchment hydrology↗

Polar coupling enabled nonlinear optical filtering at MoS 2 /ferroelectric heterointerfaces

Complex oxide heterointerfaces and van der Waals heterostructures present two versatile but intrinsically different platforms for exploring emergent quantum phenomena and designing new functionalities. The rich opportunity offered by the synergy between these two classes of materials, however, is yet to be charted. Here, we report an unconventional nonlinear optical filtering effect resulting from the interfacial polar alignment between monolayer MoS 2 and a neighboring ferroelectric oxide thin film. The second harmonic generation response at the heterointerface is either substantially enhanced or almost entirely quenched by an underlying ferroelectric domain wall depending on its chirality, and can be further tailored by the polar domains. Unlike the extensively studied coupling mechanisms driven by charge, spin, and lattice, the interfacial tailoring effect is solely mediated by the polar symmetry, as well explained via our density functional theory calculations, pointing to a new material strategy for the functional design of nanoscale reconfigurable optical applications.

36 MATERIALS SCIENCE↗

The global spectrum of tree crown architecture

Abstract Trees can differ enormously in their crown architectural traits, such as the scaling relationships between tree height, crown width and stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of terrestrial ecosystems, we lack a complete picture of what drives this incredible diversity in crown shapes. Using data from 374,888 globally distributed trees, we explore how climate, disturbance, competition, functional traits, and evolutionary history constrain the height and crown width scaling relationships of 1914 tree species. We find that variation in height–diameter scaling relationships is primarily controlled by water availability and light competition. Conversely, crown width is predominantly shaped by exposure to wind and fire, while also covarying with functional traits related to mechanical stability and photosynthesis. Additionally, we identify several plant lineages with highly distinctive stem and crown forms, such as the exceedingly slender dipterocarps of Southeast Asia, or the extremely wide crowns of legume trees in African savannas. Our study charts the global spectrum of tree crown architecture and pinpoints the processes that shape the 3D structure of woody ecosystems.

Science & Technology - Other Topics↗