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At least 19 records

Computing Sparse Tensor Decompositions via Chapel and C++/MPI Interoperability without Intermediate I/O

We extend an existing approach for efficient use of shared mapped memory across Chapel and C++ for graph data stored as 1-D arrays to sparse tensor data stored using a combination of 2-D and 1-D arrays. We describe the specific extensions that provide use of shared mapped memory tensor data for a particular C++ tensor decomposition tool called GentenMPI. We then demonstrate our approach on several real-world datasets, providing timing results that illustrate minimal overhead incurred using this approach. Finally, we extend our work to improve memory usage and provide convenient random access to sparse shared mapped memory tensor elements in Chapel, while still being capable of leveraging high performance implementations of tensor algorithms in C++.

97 MATHEMATICS AND COMPUTING

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence

Support for the 2024 American Conference on Theoretical Chemistry (ACTC) (Final Report)

Funds are requested in support of the 2024 American Conference on Theoretical Chemistry. Funds are being requested from the Department of Energy in support of conference registration fees for graduate student and post-doctoral researcher registration fees. This conference will be held in North Carolina, and between 200 and 250 participants are expected. This is the major North American meeting of theoretical chemists, showcasing diverse developments in all aspects of modern theory, including methods development and applications. Applications span all aspects of chemistry, biochemistry, and materials science, including important applications to energy science. The conference will include four days of seminars and poster sessions. As well as serving as a meeting ground for sharing scientific developments and discoveries, the meeting also serves as a locus for mentoring and career development involving younger scientists. The meeting will be chaired by Prof. David Beratan of Duke University, and he will be assisted by other faculty from the region: Profs. Weitao Yang (Duke), Patrick Charbonneau (Duke), Yosuke Kanai (University of North Carolina - Chapel Hill), Zhiyue Lu (University of North Carolina - Chapel Hill), and Elena Jakubikova (North Carolina State University). This group will form a conference commitee that will define thematic topics for the conference, will invite speakers, and will assist with running the conference.

14 SOLAR ENERGY

2006 Greater Triangle Household Travel Survey

The Greater Triangle Household Travel Survey was a comprehensive study of travel behavior throughout the 12-county Research Triangle Region, including all portions of Chatham, Durham, Franklin, Granville, Johnston, Lee, Orange, Person, Wake, and Vance counties, the eastern portion of Harnett County, and the southern portion of Nash County. The primary objective of this survey effort was to document demographic and travel behavior characteristics of regional travelers in order to update the current regional model and to develop a new, more robust travel demand model for the 12-county region. The 2006 survey was conducted in association with NuStats' DataSource and Louis Berger Group and was sponsored by the Capital Area Metropolitan Planning Organization, the Durham-Chapel Hill-Carrboro Metropolitan Planning Organization, the Triangle Transit Authority, and the North Carolina Department of Transportation. The project was conducted over an eleven-month period from August 2005 through June 2006. The survey utilized standard household travel survey methods, in which all household members from 5,107 households were asked to record all trips for a specified 24-hour period using a specially designed travel log on a non-holiday weekday.

1Hz data

GASNet-EX Specification Collection (Rev. 2024.5.0)

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale systems. It provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). GASNet-EX is an evolution of the popular GASNet communication system, building upon over 20 years of lessons learned, and the primary goals are high performance, interface portability, and expressiveness. The library has been used to implement parallel programming models and libraries such as UPC, UPC++, Fortran coarrays, Legion, Chapel, and many others. This anthology collects together the four separate volumes that currently comprise the GASNet-EX specification, as of the 2024.5.0 release of GASNet-EX.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics

Electron Inversion and Tunneling at Silicon Thermal Oxide Interfaces for Solar-Driven Molecular Catalysis to Syngas

Semiconductor photoelectrodes are regularly coupled to solid-state heterogeneous catalysts to perform solar-driven reduction of CO 2 . Less frequently, molecular catalysts are employed to better control the reactivity toward desired products, yet the development of robust semiconductor/molecule interfaces has proven challenging. Here, we demonstrate that a 2–3 nm thermal oxide layer on Si exhibits stability in aqueous solution, high photovoltage, and a photocurrent density of ∼10 mA/cm 2 for the solar-driven photoelectrochemical reduction of a homogeneous molecular catalyst, producing syngas with an ∼2:1 H 2 to CO ratio. Because of a low defect density, the oxide interface forms an electron inversion layer with metal-like electron density at cathodic potentials. This inversion layer facilitates electron transfer to redox-active molecules via tunneling even if the molecule’s reduction potential is beyond the semiconductor’s conduction band edge. Using an electrolyte solution composed of a homogeneous cobalt bis(terpyridine) catalyst in a water/organic solvent mixture, stable photoelectrochemistry was observed under 1-sun illumination, exhibiting an ∼30% Faradaic efficiency for CO that was similar to a glassy carbon electrode under comparable conditions. Furthermore, the results demonstrate that an ultrathin thermal oxide interface is a robust platform for development of aqueous-stable, molecule-driven photoelectrocatalysis.

Catalysts

Photoelectrochemical Hydride Generation with Oxide-Coated Silicon

Photoelectrochemical generation of a potent organic hydride donor at silicon is demonstrated. Two different oxide-coated p-type silicon photoelectrodes reduced 1,2,3,5,6-pentamethyl-1H-benzo[d]imidazol-3-ium hexafluorophosphate, [PMBI][PF 6 ], to its corresponding imidazole hydride, PMBIH, in the presence of a proton source. Under 1 sun illumination, in acetonitrile with 1,5-diazabicyclo[4.3.0]non-5-ene (DBN) buffer, the p-Si photoelectrodes convert PMBI + to PMBIH with good Faradaic efficiencies (FEs): 78% FE at −2.3 V vs Fc +/0 for Si|TiO 2 and 83% FE at −2.6 V vs Fc +/0 for Si|SiO 2 (where Si|SiO 2 represents silicon coated with an oxide layer). Generally, the Si|TiO 2 catalyzed the reaction at milder potentials than Si|SiO 2 , but the Si|SiO 2 had better selectivity for PMBIH generation over H 2 evolution than Si|TiO 2 . In light of prior studies of these photoelectrodes, the differences in selectivity and onset potential suggest a difference in mechanism, likely an outer-sphere electron transfer (ET) mechanism at the SiO 2 surface and potentially a proton-coupled ET process at the TiO 2 surface. To help understand reaction efficiency and identify areas of improvement, a thermochemical model for understanding net hydride transfer from the semiconductor to an acceptor in solution was developed. We find that the reactions in the present system are quite downhill. The high overpotentials (even while maintaining selectivity over H 2 evolution) emphasize the need for improved catalysts. Furthermore, this approach to evaluate the thermodynamics of net hydride transfer should be broadly valuable for electrochemical and photoelectrochemical processes.

14 SOLAR ENERGY

Dysregulation of lung epithelial cell homeostasis and immunity contributes to Middle East respiratory syndrome coronavirus disease severity

Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoVs from the past 20 years (SARS-CoV, SARS-CoV-2, and MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses. To better understand the virus and host interactions driving lethal MERS-CoV infection, we performed a longitudinal multi-omics analysis of sublethal and lethal MERS-CoV infection in mice. Significant differences were observed in body weight loss, virus titers, and acute lung injury among lethal and sub-lethal virus doses. Virus-induced apoptosis of type I and II alveolar epithelial cells suggests that loss or dysregulation of these key cell populations was a major driver of severe disease. Omics analysis suggested differential pathogenesis was multi-factorial with clear differences among innate and adaptive immune pathways as well as those that regulate lung epithelial homeostasis. Infection of mice lacking functional T and B cells showed that adaptive immunity was important in controlling viral replication but also increased pathogenesis. In summary, we provide a high-resolution host response atlas for MERS-CoV infection and disease severity. Multi-omics studies of viral pathogenesis offer a unique opportunity to not only better understand the molecular mechanisms of disease but also to identify genes and pathways that can be exploited for therapeutic intervention all of which is important for our future pandemic preparedness.

MERS-CoV

Potential-Controlled Deposition of Multilayer CO 2 Reduction Catalyst Films onto Silicon Photoelectrodes Demonstrates Thickness-Dependent Catalytic Rates

Covalently attaching molecular catalysts to semiconductor surfaces yields promising hybrid photoelectrode architectures for reducing CO 2 to higher-value carbon products. Polymeric molecular catalyst films have higher loading densities than their monolayer counterparts, promising greater rates of solar fuel production. Using photoassisted diazonium electrografting, multilayered films of a Re(apbpy)(CO) 3 Cl CO 2 -reduction catalyst were attached to low-doped p-type Si (pSi). Parallel characterization of the newly formed films with ellipsometry, XPS, and ICP-MS revealed that catalyst loading increased with increasingly negative applied grafting potentials (Vgraft), providing us an experimental test bed to study the effects of film thickness on photocatalytic performance. Controlled-potential electrolysis experiments showed enhanced CO evolution rates on all photoelectrodes with increasingly negative applied potentials (V app ), with thicker films exhibiting the greatest rates of enhancement. Competitive proton reduction reactions at the Si surface were not strongly linked to V app but dependent on film thickness, with thicker films showing increased CO-to-H 2 production ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Investigation of 31 P levels near the proton threshold with nuclear resonance fluorescence and the impact on the 30 Si (𝑝,𝛾)⁢ 31 P thermonuclear rate

We investigated the nuclear structure of 31 P near the proton threshold using nuclear resonance fluorescence (NRF) to refine the properties of key resonances in the 30 Si (𝑝,𝛾)⁢ 31 P reaction, which is critical for nucleosynthesis in stellar environments. Excitation energies and spin-parities were determined for several states, including two unobserved resonances at 𝐸 𝑟 = 18.7keV and 𝐸 𝑟 = 50.5keV. The angular correlation analysis enabled the first unambiguous determination of the orbital angular momentum transfer for these states. These results provide a significant update to the 30 Si (𝑝,𝛾)⁢ 31 P thermonuclear reaction rate, with direct implications for models of nucleosynthesis in globular clusters and other astrophysical sites. The revised rate is substantially lower than previous estimates at temperatures below 200 MK, affecting predictions for silicon isotopic abundances in stellar environments. Furthermore, our work demonstrates the power of NRF in constraining nuclear properties, and provides a framework for future studies of low-energy resonances relevant to astrophysical reaction rates.

20 ≤ A ≤ 38

Gerischer Electrochemistry Today

Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Quantitative Analysis of the Semiconductor–Electrolyte Interface Using Cyclic Voltammetry Measurements

Small changes in the chemical potential at a semiconductor interface can result in dramatic changes to the space-charge layer that underpins applications in the electronic and photovoltaic industries as well as in photoelectrochemical cells for fuel production. There has hence been great interest in techniques that directly probe the space-charge layer, yet many fail at the semiconductor–electrolyte interface due to the potential drop in the electric double-layer region of the electrolyte. This article demonstrates that photovoltages, obtained from straightforward cyclic voltammetry measurements, provide an experimental and quantitative approach for characterizing the semiconductor–electrolyte interface. Key parameters accessible through this approach include the flat-band potential ( E fb ), the fraction of the total potential that drops across the space-charge layer (γ sc ) and the electric double layer, as well as the surface recombination lifetime (τ s ). Here, we report photovoltage measurements for p -type Si(111) photoelectrodes in contact with electrolytes containing redox-active species with a range of known reduction potentials that exceed the 1.1 eV bandgap. In tetrabutylammonium [NBu 4 ] + electrolyte, the flat-band potential determined for hydrogen-terminated ( p -Si–H), methyl-terminated ( p -Si–CH 3 ), and chemically oxidized ( p -Si–cSiO x ) surfaces were −0.02, −0.31, and 0.30 V vs Fc +/0 , respectively, agreeing well with expected shifts arising from surface dipole modifications. The quantitative analysis also reveals that 67% of the applied bias drops across the space-charge layer for p -Si–H, 73% for p -Si–CH 3 , and only 44% for p -Si–cSiO x . The remaining potential drop is attributed to the interfacial surface layer, which consists of a molecular dipole or oxide overlayer, and the Helmholtz layer within the electrolyte. When the larger [NBu 4 ] + electrolyte was replaced with Li + , the flat-band position showed minimal changes, but the fraction of the potential drop across the space-charge layer increased significantly, consistent with the small cation altering the structure of the electric double layer.

electrolytes

Elongated Fullerene Unlocks Oxygen-Resistant Perovskite Solar Minimodules

State-of-the-art encapsulation cannot prevent the permeation of oxygen into perovskite solar cells (PSCs). Here, we report the finding that p-i-n structured PSCs degrade quickly under oxygen exposure. Oxidation of C60, rather than perovskites, dominates the degradation. Chemical absorption of oxygen by C60 is identified, which impairs its electron transport property. We modify the electron transport layers to address the instability under oxygen exposure. The elongated fullerene C70 is found to react with oxygen orders of magnitude slower than C60. In combination with a compact SnO2 buffer fabricated by atomic layer deposition, which can slow down the oxygen diffusion, the resulting unencapsulated PSCs with C70 retained 90% of their initial efficiency after 1-sun illumination in pure oxygen for 1,200 h at 70 degrees C, improving stability by hundreds of times. Testing of unencapsulated perovskite minimodules of different perovskite compositions with C70 gives extrapolated lifetimes of 17-41 years at 50 degrees C.

14 SOLAR ENERGY

Syngas Production at Si Hybrid Photoelectrodes Modified with Re(I) and Mn(I) Tricarbonyl Phenanthroline Complexes Containing Reactive Aryl Azide Groups

We installed molecular CO 2 reduction (CO 2 R) catalysts directly onto Si (photo)electrodes. The highly reactive M(5-azido-1,10-phenanthroline)(CO) 3 X (where M = Mn or Re, X = Br or Cl) complexes readily bubbled when dissolved in polar organic solvents, in both the presence and absence of an ultraviolet light source. When placed on hydrogen-terminated Si (H-Si) and native silicon oxide (SiOx), similar amounts of the complex were attached to the surface under illumination (367 nm, 50–200 mW/cm 2 ) or in the dark. Surprisingly, these films revealed submonolayer coverages instead of the multilayered structures we expected. DFT analyses support monolayer formation, showing that the triplet-state nitrene of the complex is more energetically favorable than the singlet state. Using controlled-potential electrolysis experiments, we showed that Re- and Mn-containing films on pSi photoelectrodes generated small amounts of CO when exposed to 1 atm of CO 2 and 1 sun illumination. These amounts of CO were an order of magnitude greater than control surfaces, producing 5.59 × 10 –7 mol CO/h for Re(az-phen) and 7.83 × 10 –7 mol CO/h for Mn(az-phen) films. Much of the charge passed at the pSi electrodes was consumed by the competing hydrogen evolution reaction, which we attribute to the low molecular coverage and the presence of native oxide on the electrode surface after attachment. Finally, this work demonstrates the feasibility of reacting azide-containing ligands with Si surfaces. Still, it highlights the need for alternative ligand structures and reaction conditions to form multilayer films.

azides

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data

Room‐Temperature Formate Ester Transfer Hydrogenation Enables an Electrochemical/Thermal Organometallic Cascade for Methanol Synthesis from CO 2

Abstract The reduction of CO 2 to synthetic fuels is a valuable strategy for energy storage. However, the formation of energy‐dense liquid fuels such as methanol remains rare, particularly under low‐temperature and low‐pressure conditions that can be coupled to renewable electricity sources via electrochemistry. Here, a multicatalyst system pairing an electrocatalyst with a thermal organometallic catalyst is introduced, which enables the reduction of CO 2 to methanol at ambient temperature and pressure. The cascade methanol synthesis proceeds via CO 2 reduction to formate by electrocatalyst [Cp*Ir(bpy)Cl] + (Cp*=pentamethylcyclopentadienyl, bpy=2,2′‐bipyridine), Fischer esterification of formate to isopropyl formate catalyzed by trifluoromethanesulfonic acid (HOTf), and thermal transfer hydrogenation of isopropyl formate to methanol facilitated by the organometallic catalyst (H‐PNP)Ir(H) 3 (H‐PNP=HN(C 2 H 4 P i Pr 2 ) 2 ). The isopropanol solvent plays several crucial roles: activating formate ion as isopropyl formate, donating hydrogen for the reduction of formate ester to methanol via transfer hydrogenation, and lowering the barrier for transfer hydrogenation through hydrogen bonding interactions. In addition to reporting a method for room‐temperature reduction of challenging ester substrates, this work provides a prototype for pairing electrochemical and thermal organometallic reactions that will guide the design and development of multicatalyst cascades.

Fernández, Sergio [Department of Chemistry Univers