The Crystal Structure of Cysteamine Dioxygenase Reveals the Origin of the Large Substrate Scope of T
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The synthesis of heteroleptic [Ni(P 2 N 2 )(diphosphine)][BF 4 ] 2 complexes and the cleavage of P–C and C–H bonds of the P 2 N 2 ligand in those complexes are reported here. The products are five-coordinate complexes in which Ni–C and P–H bonds have formed to give a cyclic moiety containing Ni–CH$=$NR 2 . The reactivity of [Ni(P 2 N 2 )(diphosphine)][BF 4 ] 2 complexes is influenced by the rigidity of the diphosphine, the steric effect of the substituents, and length of the carbon linker of the diphosphine ligands. Diphosphine ligands bearing a rigid backbone (e.g., dmpbz, 1,2-bis(dimethylphosphino)benzene) or aromatic substituents (e.g., dppe, 1,2-bis(diphenylphosphino)ethane) react with [Ni(P t Bu 2 N Bn 2 )(CH 3 CN) 2 ][BF 4 ] 2 to give P–C/C–H bond cleavage products. Both [Ni(P t Bu 2 N Bn 2 )(dmpe)(MeCN)][BF 4 ] 2 and [Ni(P t Bu 2 N Bn 2 )(dmpm)(MeCN)][BF 4 ] 2 (dmpm = 1,2-bis(dimethylylphosphino)methane) were prepared by the reaction of [Ni(P t Bu 2 N Bn 2 )(CH 3 CN) 2 ][BF 4 ] 2 with the corresponding diphosphine ligands. [Ni(P t Bu 2 N Bn 2 )(dmpe)(MeCN)][BF 4 ] 2 readily undergoes P–C/C–H bond cleavage in nitromethane. In sharp contrast, [Ni(P t Bu 2 N Bn 2 )(dmpm)][BF 4 ] 2 is stabilized by dmpm, a diphosphine with small bite angle, and does not show P–C/C–H bond cleavage reactivity. Computational results show that for complexes bearing less bulky diphosphine ligands, such as dmpm, the barriers for the rate-determining transition states are in some examples higher than 30 kcal/mol with the M06 functional, higher than those for complexes bearing more rigid or more bulky ligands, consistent with experimental studies. The calculated barriers for the first transition state correlated with increased values of the dihedral angle formed by the two NiP 2 planes.
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The functionality of many materials is critically dependent on the integration of dissimilar components and on the interfaces that arise between them. The description of such heterogeneous components requires the development and deployment of first principles methods, coupled to appropriate dynamical descriptions of matter and advanced sampling techniques, in order to capture all the relevant length and time scales of importance to the materials’ performance. It is thus essential to build simple, streamlined computational schemes for the prediction and design of multiple properties of broad classes of materials, by developing interoperable codes which can be efficiently coupled to each other to perform complex tasks. We discuss the use of interoperable codes to simulate the structural and spectroscopic characterization of materials, including chemical reactions for catalysis, the description of defects for quantum information science, and heat and charge transport.
The absence of orthogonal aminoacyl-transfer RNA (tRNA) synthetases that accept non-L-α-amino acids is a primary bottleneck hindering the in vivo translation of sequence-defined hetero-oligomers and biomaterials. Here we report that pyrrolysyl-tRNA synthetase (PylRS) and certain PylRS variants accept α-hydroxy, α-thio and N-formyl-L-α-amino acids, as well as α-carboxy acid monomers that are precursors to polyketide natural products. These monomers are accommodated and accepted by the translation apparatus in vitro; those with reactive nucleophiles are incorporated into proteins in vivo. High-resolution structural analysis of the complex formed between one PylRS enzyme and a m-substituted 2-benzylmalonic acid derivative revealed an active site that discriminates prochiral carboxylates and accommodates the large size and distinct electrostatics of an α-carboxy substituent. This work emphasizes the potential of PylRS-derived enzymes for acylating tRNA with monomers whose α-substituent diverges substantially from the α-amine of proteinogenic amino acids. These enzymes or derivatives thereof could synergize with natural or evolved ribosomes and/or translation factors to generate diverse sequence-defined non-protein heteropolymers.
We present a new heteroditopic ligand (3pyCCMoid) that contains the typical skeleton of a curcuminoid (CCMoid) decorated with two 3-pyridyl groups. The coordination of 3pyCCMoid with ZnII centres results in a set of novel coordination polymers (CPs) that display different architectures and dimensionalities (from 1D to 3D). Our work analyses how synthetic methods and slight changes in the reaction conditions affect the formation of the final materials. Great efforts have been devoted toward understanding the coordination entities that provide high dimensional systems, with emphasis on the characterization of 2D materials, including analyses of different types of substrates, stability and exfoliation in water. Here, we foresee the great use of CCMoids in the field of CPs and emphasize 3pyCCMoid as a new-born linker.
In this paper, we used radio frequency (RF) full wave simulation to explore the feasibility of generating a density beat oscillation formed by high harmonic fast waves (HHFWs) in the National Spherical Tokamak Experiment-Upgrade (NSTX-U) and of measuring it numerically with 2D beam emission spectroscopy (BES). This oscillation is of interest as it can be used to determine the injected RF fields. We began by computing HHFW fields in NSTX-U under a variety of experimental conditions and antenna configurations with Petra-M, a 3D RF wavefield solver. These fields were then used to evaluate the amplitude of δne,beat/ne0 in the volume of measurement, which we predict to be between 5 × 10−10 and 10−9, although it is highly dependent on plasma parameters. Trends in magnetic field, core temperature, core density, and antenna phasing are presented, and the parameters most suitable to this measurement are identified. Finally, we developed a synthetic BES diagnostic to compare the experimental BES signal against.
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With the forecasted increase in the construction and operation of nuclear reactors, there will be a corresponding increase in the quantity of spent nuclear fuel (SNF) that requires long-term storage. In SNF, transuranic isotopes contribute the most to the long-term radiotoxicity of the fuel and pose a proliferation risk. One option that has been explored to address these issues is the removal of the transuranic isotopes from SNF and the conversion of these isotopes into transuranic fuel (TRU fuel). Here, this work sought to determine how effective a micro-modular Pebble-Bed High-Temperature Gas-Cooled Reactor (PB-HTGR); the 10-MW High Temperature Gas-cooled Test Reactor (HTR-10); and a salt-cooled small-modular pebble-bed reactor (PBR), i.e. the generic Fluoride-cooled High-temperature Reactor (gFHR), are at reducing the inventory of transuranic isotopes while still maintaining the intrinsic safety features of the PBR designs, such as negative temperature coefficients of reactivity. Optimized pebble designs utilizing TRU fuel were found for both reactors through the adjustment for the packing fraction of fuel in each pebble. The Axial Zone Equilibrium Modeling (A-ZEM) method was used in this work to help select the optimized pebble design. Once an optimized pebble design was selected and an equilibrium model was produced, the results from the deep burn (DB) HTR-10 and gFHR designs were compared to the results of two models from the literature. While both the DB gFHR and the DB HTR-10 were able to reduce the weapons-usable transuranic inventory, the performance of these reactors did not match that of the small-modular PB-HTGRs in the literature. Therefore, a need was identified for further refinement of the gFHR design using TRU fuel, as the results for this model were more promising than those of the DB HTR-10, which was strongly limited by the high leakage intrinsic to micro-modular PB-HTGRs.
The paper assesses the applicability of lower hybrid current drive (LHCD) for two potential operating scenarios for the China Fusion Engineering Test Reactor (CFETR): the “hybrid” scenario in which some of the plasma current is sustained by the Ohmic transformer, and the fully non-inductive “steady state” scenario. Here, the πScope workflow engine was used to set up a large number of ray tracing/Fokker-Planck simulations (> 10 4 ) with parametric scans in the antenna poloidal position and launched parallel refractive index (n || ) for both the hybrid and steady state scenarios. Modeling predicts efficient off-axis current drive (1.3 MA for 20 MW launched power) with a peak near ρ of 0.6-0.65 for waves launched from the high field side (HFS). Waves launched from the low field side (LFS) damp at larger radius (ρ > 0.73) with similar efficiency to HFS launch. Stability analysis of the CFETR scenarios favors current drive profiles peaked near the mid-radius, suggesting that HFS launch is preferable due to the current drive location. The effect of wave scattering from density blobs in the edge/scrape-off-layer region was assessed through rotation of the perpendicular wavenumber at the ray origin. Simulations show that this effect can be quite large both in efficiency and damping location, however by adjusting the launched n|| much of the unperturbed performance can be recovered.
On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.
Abstract Underlying policy efforts to address global climate change is the scientific need to develop the methods to accurately measure and model carbon stocks and fluxes across the wide range of spatial and temporal scales in the Earth system. Initiated in 2010, the NASA Carbon Monitoring System is one of the most ambitious relevant science initiatives to date, exploiting the satellite remote sensing resources, computational capabilities, scientific knowledge, airborne science capabilities, and end-to-end system expertise that are major strengths of the NASA Earth Science program. Here we provide a synthesis of ‘Phase 2’ activities (2011–2019), encompassing 79 projects, 482 publications, and 136 data products. Our synthesis addresses four key questions: What has been attempted? What major results have been obtained? What major gaps and uncertainties remain? and What are the recommended next steps? Through this review, we take stock of what has been accomplished and identify future priorities toward meeting the nation’s needs for carbon monitoring reporting and verification.
Photosynthesis is the primary energy input to plants, but most plant metabolic processes are powered much or all of the time by ATP and NAD(P)H that come from respiratory oxidation of photosynthetically produced carbohydrates, that is, “dark respiration” (Amthor, 1994). The processes of growth, nutrient uptake and assimilation, active transport, and maintenance are thus all clients of respiration and compete for their share of a respiratory energy budget that is capped by photosynthate income. The economic principle of opportunity cost applies to these clients’ competing demands: spending respiratory energy on process A means missing the benefit of investing that energy in process B (Mahmoudabadi et al., 2019). This principle is key to assessing prospects for crop improvement by metabolic engineering. As de Lorenzo (2015) put it: “metabolism…frames and ultimately resolves whether a given genetic program (existing…or engineered) can be deployed or not.” Foreign or reconfigured native processes bolted on to a crop-plant’s metabolic chassis must compete for respiratory energy with native ones without crashing the energy economy. A proviso on plant carbon budgets is that photosynthetic carbon fixation (“source activity”) can in certain cases increase to meet increased carbon demand (“sink activity”), that is, budget envelopes are not always fixed (Smith et al., 2018). However, as there is some consensus that productivity is most often limited or co-limited by carbon supply (Ainsworth and Long, 2005; Körner, 2015; Sonnewald and Fernie, 2018), we make this our basal assumption in the analyses below.
Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.
Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.
The aim of this study is to determine the threshold wave energy converter (WEC) type and size to charge a fleet of U.S. Navy autonomous underwater vehicles (AUVs) in various geographic locations of interest. The U.S. Navy deploys AUVs in locations around the world that must be charged manually, decreasing their operational endurance and creating operational limitations. Ocean waves are a potential power source that can be converted into electricity using a WEC and stored using a battery. It would be beneficial to develop a WEC that could autonomously charge AUVs offshore. Numerous locations were analyzed to determine the minimum size of a WEC capable of providing sufficient charging power and offering a strategic advantage. By predicting the WEC efficiency (based on empirical equations) and wave resource (based on available data), electrical power generation across numerous WEC types and locations was compared in MATLAB. The generalized process developed here could be used to determine the required size and type of WECs to charge a fleet of AUVs in different locations around the world.
Summary Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction‐diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf‐level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.