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The use of sulfone-based redox mediators in electrocatalytic CO 2 reduction by Cr-centered complexes enhances the turnover frequencies at lower overpotentials via inner-sphere electron transfer and pancake bonding.
Low-temperature, scalable routes to transition metal nitride (TMN) nanoparticles are desirable for a wide range of applications, yet their synthesis typically requires high temperatures (>350 °C) and reactive gas environments (e.g., NH 3 or H 2 /N 2 ). Here, we report a colloidal synthesis of mono- and bimetallic TMN nanoparticles using preformed metal carbonyl clusters as precursors and urea or diethylenetriamine (DETA) as nitrogen sources. This strategy enables access to size-controlled, phase-pure ε-Fe 3 N x and Fe y Ni 3−y N nanoparticles at temperatures below 300 °C, without the need for flowing reactive gas atmospheres. By systematically varying nitrogen precursor, reaction temperature, and cluster identity, we achieve tunable nitrogen stoichiometry (x) and phase selectivity between N-rich and N-poor TMNs. Structural and magnetic characterization confirms clean decomposition of the precursors and phase formation consistent with controlled nitridation at the nanoscale. Preliminary electrochemical measurements in alkaline media demonstrate that these materials exhibit oxygen evolution reaction (OER) overpotentials comparable to RuO 2 , highlighting their viability for future electrocatalytic applications.
Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling optogenetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Furthermore, our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.
Seaweeds represent a rich source of sulfated polysaccharides with similarity to heparan sulfate, a facilitator of myriad virus host cell attachment. For this reason, attention has been drawn to their antiviral activity, including the potential for anti-SARS-CoV-2 activity. We have identified and structurally characterized several fucoidan extracts, including those from different species of brown macroalga, and a rhamnan sulfate from a green macroalga species. A high molecular weight fucoidan extracted from Saccharina japonica (FSjRPI-27), and a rhamnan sulfate extracted from Monostroma nitidum (RSMn), showed potent competitive inhibition of spike glycoprotein receptor binding to a heparin-coated SPR chip. This inhibition was also observed in cell-based assays using hACE2 HEK-293 T cells infected by pseudotyped SARS-CoV-2 virus with IC50 values <1 μg/mL. Effectiveness was demonstrated in vivo using hACE2–transgenic mice. Intranasal administration of FSjRPI-27 showed protection when dosed 6 h prior to and at infection, and then every 2 days post-infection, with 100 % survival and no toxicity at 104 plaque-forming units per mouse vs. buffer control. At 5-fold higher virus dose, FSjRPI-27 reduced mortality and yielded reduced viral titers in bronchioalveolar fluid and lung homogenates vs. buffer control. Furthermore, these findings suggest the potential application of seaweed-based sulfated polysaccharides as promising anti-SARS-CoV-2 prophylactics.
Some electrochemical systems are known to have higher average efficiency when operated under an oscillatory regime. Given the compromise between activity and stability, the stability of electrochemical interfaces in a self-organized, oscillatory state must be taken into account. Here we evaluate the electro-oxidation of methanol and formic acid on platinum under regular and oscillatory conditions, and study the stability by following the Pt dissolution rates in situ with a stationary probe rotating disk electrode (SPRDE) coupled to an inductively coupled plasma mass spectrometer (ICP-MS). Generally speaking, as the electro-oxidation reaction proceeds, the platinum dissolution rate increases considerably. To guarantee Pt stability, the potential must be kept below 1.0 V vs. RHE. Interestingly, no dissolution is detectable when the electrode potential undergoes temporary self-organization, ensuring a stable and active interface.
The contractor requirements document for DOE O 226.1B, Implementation of Department of Energy Oversight Policy, requires DOE/NNSA contractors to establish an assurance system that includes, among other things, “Rigorous, risk-informed, and credible self-assessment and feedback and improvement activities. Assessment programs must be risk-informed, formally described and documented, and appropriately cover potentially high consequence activities” and “Contains an issues management process that is capable of categorizing the significance of findings based on risk and priority and other appropriate factors….” However, the term “risk-informed” is not defined in this or any other DOE order, and no formal guidance on how to integrate the two concepts currently exists. The Risk Management Guide for Defense Programs released by NA-18, Office of Systems Engineering and Integration (SE&I), states it is “a framework and general guidance to program office personnel on the effective management of program risks and issues”, however it then defines issues as “events with 100% likelihood of affecting program objectives” and states “unless specified otherwise, the term “risk” will also serve to represent issues for the remainder of this plan,” severally limiting its ability to provide adequate guidance on this topic. Outside of DOE scope, the U.S. Nuclear Regulatory Commission (U.S. NRC) imposes similar requirements. ASME NQA-1-2015 Requirement 16 states “Conditions adverse to quality shall be identified promptly and corrected as soon as practicable. In the case of a significant condition adverse to quality, the cause of the condition shall be determined, and corrective action taken to preclude recurrence. The identification, cause, and corrective action for significant conditions adverse to quality shall be documented and reported to appropriate levels of management. Completion of corrective actions shall be verified”. The purpose of this document is to provide a best-in-class framework for an integrated risk and issues management process. This process would provide a robust feedback loop between risk management and issues management to: Enhance risk identification and characterization, use risk handling principles to improve corrective action planning, and ensure regulatory compliance.
Newly acquired magnetotelluric data and passive seismic data collected with tightly spaced geophone arrays are combined with historic drilling, active seismic, and potential fields data to generate 3-D permeability maps. A cooperative inversion methodology has been developed using active seismic, magnetotelluric, and gravity data in order to produce more robust velocity models for passive seismic data processing without requiring expensive 3-D active seismic surveys. The cooperative inversion estimates velocities from other geophysical data where no prior seismic velocity information is available at two geothermal sites in Nevada: San Emidio and Crescent Valley.
The carboxylation status of Osteocalcin (Ocn) not only influences formation and structure in bones but also has important endocrine functions affecting energy metabolism and expenditure. In this study, the role of γ-carboxylation of the glutamate residues in the structure-dynamics-function relationship in Ocn is investigated. Three forms of Ocn, differentially carboxylated at the Glu-17, 21 and 24 residues, along with a mutated form of Ocn carrying Glu/Ala mutations, are modeled and simulated using molecular dynamics (MD) simulation in the presence of calcium ions. Characterization of the global conformational dynamics of Ocn, described in terms of the orientational variations within its 3-helical domain, highlights large structural variations in the non-carboxylated osteocalcin (nOcn). The bi-carboxylated Ocn (bOcn) and tri-carboxylated (tOcn) species, in contrast, display relatively rigid tertiary structures, with the dynamics of most regions strongly correlated. Radial distribution functions calculated for both bOcn and tOcn show long-range ordering of the calcium ion distribution around the carboxylated glutamate (γGlu) residues, likely playing an important role in promoting stability of these Ocns. Additionally, the same calcium ions are observed to coordinate with neighboring γGlu, better shielding their negative charges and in turn stabilizing these systems more than do the singly coordinating calcium ions observed in the case of nOcn. bOcn is also found to exhibit a more helical C-terminal structure, that has been shown to activate its cellular receptor GPRC6A, highlighting the allosteric role of Ocn carboxylation in modulating the stability and binding potential of the active C-terminal. Furthermore, the carboxylation status of Ocn as well and its calcium coordination appear to have a direct influence on Ocn structure and dynamics, possibly leading to the known differences in Ocn biological function.
The Pourbaix diagrams of p-block Pb, Sb, and Bi establish a robust stability for their oxides in acidic solutions. Such oxides have found utility as stable frameworks to support metals that are active for oxygen evolution reaction (OER) catalysis, but they also possess two-electron redox couples, which can potentially engender OER activity. Thus, the use of p-block oxide supports provides an imperative for understanding the OER activity of the unary oxides. Toward this end, we report BiO x films that are able to perform OER catalysis at moderate overpotentials for extended periods of operation (>110 h) in highly acidic solutions (pH 1.0–2.25) with no sign of decreased OER activity during operation at current densities of 1–5 mA cm –2 . X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), and UV-vis spectroelectrochemistry reveal a change in the Bi oxidation state prior to OER catalysis, from predominantly Bi 3+ in the as-deposited films to primarily Bi 5+ in the catalytically active films. Furthermore, this transformation is accompanied by a prominent color change from orange to dark brown. Simulations of the cyclic voltammogram catalytic profiles suggest two OER pathways for BiO x involving Bi IV O x and Bi V O x catalysts with the Bi V O x pathway prevailing after catalyst activation. Together, these results demonstrate the ability of BiO x to facilitate OER in acid with high functional stability and underscore the noninnocent role that p-block metal oxides may play in OER catalysis in acidic media.
In the United States, agricultural production is both a significant source of greenhouse gases (GHGs) (Environmental Protection Agency (EPA), 2022) and uniquely susceptible to climate change impacts (Vermeulen et al., 2012). Decarbonization solutions have been proposed for addressing agricultural GHGs; however, research has been limited in synthesizing qualitative and quantitative analysis of potential GHG mitigation solutions in the United States. In this report, we review U.S. agricultural GHG sources by activity and quantify potential mitigation solutions based on a comprehensive data and literature analysis. We also discuss agricultural carbon sequestration options to offset GHG emissions. In our analysis, we identified two significant and hard-to-abate GHG sources (N 2 O from soil management, and CH 4 from enteric fermentation from livestock) as well as high-impact GHG mitigation solutions (e.g. agroforestry, reforestation, and biochar application) and cross-cutting GHG mitigation solutions (renewable energy production, precision agriculture, no-till, integrated nutrient management, and biochar). This report is meant to provide initial analysis and establish a foundation for future agricultural decarbonization research - it is not an exhaustive analysis of all available studies. However, to our knowledge this report is the most comprehensive assessment of agricultural GHG emissions and associated mitigation opportunities in the United States to date. Future empirical research is recommended to close research gaps in different climates, soils, and agricultural systems. Meta-analyses for all mitigation solutions would increase confidence in the estimated GHG mitigation potentials. To conclude this report, we discuss short-term and long-term pathways for agricultural decarbonization in the United States, the importance of accounting for total GHG fluxes, potential co-benefits of agricultural decarbonization, analysis of study data confidence, and research gaps.
The synthesis of a piano-stool ruthenium hydride, [(η 5 -C 5 Me 5 )Ru(PmIm)H] (PmIm = (N-(1,3,5-trimethylphenyl)-1-(pyrimidin-2-yl)ethan-1-imine) for the dual purpose of catalytic dihydrogen activation and subsequent hydrogen atom transfer for the formation of weak chemical bonds is described. Introduction of a neutral, potentially redox-active PmIm supporting ligand was designed to eliminate the possibility of deleterious C(sp 2 )–H reductive coupling and elimination that has been identified as a deactivation pathway with related rhodium and iridium catalysts. Treatment of [(η 5 -C 5 Me 5 )RuCl 2 ] n with one equivalent PmIm ligand in the presence of zinc and sodium methoxide resulted in isolation of the diruthenium complex, [(η 5 -C 5 Me 5 )Ru(PmIm)] 2 , arising from C–C bond formation between two PmIm chelates. Addition of H 2 to the ruthenium dimer under both thermal and blue light irradiation conditions furnished the targeted hydride, [(η 5 -C 5 Me 5 )Ru(PmIm)H] which has a relatively weak DFT-calculated Ru–H bond dissociation free energy (BDFE) of 47.9 kcal/mol. Addition of TEMPO to [(η 5 -C 5 Me 5 )Ru(PmIm)H] generated the 17-electron metalloradical, [(η 5 -C 5 Me 5 )Ru(PmIm)], which was characterized by EPR spectroscopy. The C–C bond forming process was reversible as irradiation of [(η 5 -C 5 Me 5 )Ru(PmIm)] 2 generated [(η 5 -C 5 Me 5 )Ru(PmIm)H] and a piano-stool ruthenium complex containing an enamide ligand derived from H-atom ab-straction from the PmIm chelate. Equilibration studies were used to establish an experimental estimate of the effective Ru–H BDFE and a value of 50.8 kcal/mol was obtained, in agreement with the observed loss of H 2 and the DFT-computed value. Here, the ruthenium hydride was an effective catalyst for the thermal catalytic hydrogenation of TEMPO, acridine and a cobalt-imido complex and for the selective reduction of azobenzene to diphenylhydrazine using H 2 as the terminal reductant, highlighting the role of this complex is catalytic weak bond formation using H 2 as the stoichiometric reductant.
Silicon nitride (Si 3 N 4 ) is an extensively used material in the automotive, aerospace, and semiconductor industries. However, its widespread use is in contrast to the scarce availability of reliable interatomic potentials that can be employed to study various aspects of this material on an atomistic scale, particularly its amorphous phase. In this work, we developed a machine learning interatomic potential, using an efficient active learning technique, combined with the Gaussian approximation potential (GAP) method. Our strategy is based on using an inexpensive empirical potential to generate an initial dataset of atomic configurations, for which energies and forces were recalculated with density functional theory (DFT); thereafter, a GAP was trained on these data and an iterative re-training algorithm was used to improve it by learning on-the-fly. When compared to DFT, our potential yielded a mean absolute error of 8 meV/atom in energy calculations for a variety of liquid and amorphous structures and a speed-up of molecular dynamics simulations by 3–4 orders of magnitude, while achieving a first-rate agreement with experimental results. Our potential is publicly available in an open-access repository.
Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.
Achieving sufficient substrate-metal catalyst affinity is a fundamental challenge for developing synthetically useful C–H activation reactions of weakly coordinating native substrates. While hydrogen bonding has been harnessed to bias site selectivity in existing C(sp 2 )–H activation reactions, the potential for designing catalysts with hydrogen bond donors (HBDs) to enhance catalyst substrate affinity, and thereby facilitate otherwise unreactive C(sp 3 )–H activation, remains to be demonstrated. Herein, we report the discovery of a ligand scaffold containing a remote amide motif that can form a favorable meta-macrocyclic hydrogen bonding interaction with the aliphatic acid substrate. The utility of this ligand scaffold is demonstrated through the development of an unprecedented C(sp 3 )–H bromination of α-tertiary and α-quaternary free carboxylic acids, which proceeds in exceedingly high mono-selectivity. Furthermore, the geometric relationship of the NHAc hydrogen bond donor and the coordinating quinoline ligand is crucial for forming the meta-macrocyclophane-like hydrogen bonding interaction, providing a guideline for the future design of catalysts employing secondary interactions.
Enhanced biological phosphorus removal (EBPR) systems often rely on exogenous carbon sources, such as volatile fatty acids (VFAs), to achieve higher P removal. Here, we employed DNA quantitative stable isotope probing (qSIP) using two VFAs, acetate and propionate, in cyclic anaerobic/aerobic incubations to assess their effects on P cycling and microbial activity with biomass from two full-scale EBPR water resource-recovery facilities that utilize VFA addition. We found that anaerobic VFA uptake preferences differed within known groups of PAOs, such as Candidatus Accumulibacter and Tetrasphaera-affiliated members (e.g., Ca. Phosphoribacter), between the two biomasses. The combination of qSIP with metagenomics identified isotopically labeled phages that were linked to active PAOs, highlighting their potential roles in modulating EBPR community composition and activity. The highest levels of anaerobic labeling from acetate were in genomes belonging to Saccharimonadales and Rickettsiales, which are generally host-associated with bacteria and eukaryotes, respectively. Furthermore, this finding highlights the possibility of cross-feeding between PAO hosts and their parasites or predators, as well as the role of so-far uncharacterized organisms participating in carbon cycling under EBPR conditions. Collectively, these results expand our understanding of the ecological interactions involved in communities anaerobically uptaking VFAs and cycling P that are central to EBPR.
Abstract A novel polysaccharide EtGIPL1a was purified from fruiting bodies of Echinodontium tinctorium , a fungus unique to western North America. EtGIPL1a has an estimated weight average molecular weight of 275 kDa and is composed of glucose (54.3%), galactose (19.6%), mannose (11.1%), fucose (10.3%), glucuronic acid (4%), and rhamnose (0.6%). It has multiple glycosidic linkages, with 3-Glc p (28.9%), 6-Glc p (18.3%), 3,6-Glc p (13%), 4-Glc p A (9.2%), 6-Gal p (3.9%), 2,6-Gal p (2.6%), 3-Fuc p (2.5%), 6-Man p (2.4%) being the most prominent, and unsubstituted glucose (15.3%), mannose (1.3%) and fucose (0.9%) as major terminal sugars. EtGIPL1a has a backbone containing mostly 3-substituted β -glucopyranose with 4-substituted glucopyranosyluronic acid. EtGIPL1a showed anti-proliferative activity against multiple cancer cell lines, with IC 50 ranging from 50.6 to 1446 nM. Flow cytometry analyses confirmed that apoptosis induction is one mechanism for its anti-proliferative activity. EtGIPL1a should be further investigated for its potential anti-cancer activity in animal models, and for its possible utility in differentiation cancer therapy.
Logic operations performed by semiconductor-based transistors are the basis of modern computing. There is considerable interest in creating autonomous materials systems endowed with the capability to make decisions. In this work, we introduce the concept of using topological defects in active matter to perform logic operations. When an extensile active stress in a nematic liquid crystal is turned on, +1/2 defects can self-propel, in analogy to electron transport under a voltage gradient. By relying on hydrodynamic simulations of active nematics, we demonstrate that patterns of activity, when combined with surfaces imparting certain orientations, can be used to control the formation and transport of +1/2 defects. We further show that asymmetric high- and low-activity patterns can be used to create effective defect gates, tunnels, and amplifiers. The proposed active systems offer the potential to perform computations and transmit information in active soft materials, including actin-, tubulin-, and cell-based systems.
The measurement of electrical activity across systems of excitable cells underlies current progress in neuroscience, cardiac pharmacology, and neurotechnology. However, bioelectricity spans orders of magnitude in intensity, space, and time, posing substantial technological challenges. The development of methods permitting network-scale recordings with high spatial resolution remains key to studies of electrogenic cells, emergent networks, and bioelectric computation. Here, for this work, we demonstrate single-shot and label-free imaging of extracellular potentials with high resolution across a wide field-of-view. The critically coupled waveguide-amplified graphene electric field (CAGE) sensor leverages the field-sensitive optical transitions in graphene to convert electric potentials into the optical regime. As a proof-of-concept, we use the CAGE sensor to detect native electrical activity from cardiac action potentials with tens-of-microns resolution, simultaneously map the propagation of these potentials at tissue-scale, and monitor their modification by pharmacological agents. This platform is robust, scalable, and compatible with existing microscopy techniques for multimodal correlative imaging.