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At least 739 records · Page 41

Crop diversification improves water-use efficiency and regional water sustainability

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s improvements to WUE, with direct implications for climate adaptation. More broadly, our framework offers a tool to evaluate other sustainable practices and guide policy and farm-scale decision-making.

climate-resilient agriculture↗

Cold compressor performance and energy consumption improvements at Jefferson Lab’s Central Helium Liquefiers

Abstract Jefferson Lab operates two central helium liquefiers (CHLs) which both utilize full cold compression from the saturation pressure at operating temperature (approximately 2.1 K) to just over atmospheric pressure. The original plant, CHL1, was recently outfitted with a replacement subatmospheric cold box (SC1R) containing state-of-the-art cold compressor technology, while the newer plant, CHL2, uses an older cold compressor system. In both cases, the heat of compression is absorbed at low temperature at the expense of electrical power consumed by the warm compressors. Due to the superior efficiency and turndown capabilities of SC1R, a new operating mode has been identified for CHL1 in which the required number of operating warm compressors is reduced by one. A cost-based method for optimizing cold compressor stability and efficiency has been developed and applied to CHL2, improving its turndown and lowering the warm compressor discharge pressure. As a result of these efforts, power consumption of the combined CHLs during normal operations has been reduced by nearly 10%, or a total of 650 kW. The observed performance of CHL1 with SC1R, as well as the cold compressor optimization method, leading to this improved energy consumption rate will be discussed in detail.

Mastracci, B [Thomas Jefferson National Accelerato↗

Network science can improve the sustainable development of solar energy

Abstract The recent emergence of agrivoltaic and ecovoltaic approaches to ground-mounted photovoltaic (PV) energy provides a much-needed alternative to the environmentally disruptive practices employed in utility-scale solar development. Research on such land-sharing approaches has grown rapidly, with an emphasis on characterizing how PV arrays impact ecosystem processes and agricultural productivity. Although these studies have done well to quantify a variety of dual-use solar practices by employing site-specific sampling designs, this approach has limited our ability to synthesize results across sites, regions, and globally. We call for a network science approach for improved cross-site synthesis of dual-use solar research. We contend that a common approach for data collection and synthesis will facilitate a more rigorous investigation of the agricultural and ecological impacts of PV development across space and over time. The products of this scientifically informed approach can be directly applied to improve sustainable land management.

Bacon, Taylor (ORCID:0009000518578569)↗

Increased seminal root number associated with domestication improves nitrogen and phosphorus acquisition in maize seedlings

Abstract Background and Aims Domesticated maize (Zea mays ssp. mays) generally forms between two and six seminal roots, while its wild ancestor, Mexican annual teosinte (Zea mays ssp. parviglumis), typically lacks seminal roots. Maize also produces larger seeds than teosinte, and it generally has higher growth rates as a seedling. Maize was originally domesticated in the tropical soils of southern Mexico, but it was later brought to the Mexican highlands before spreading to other parts of the continent, where it experienced different soil resource constraints. The aims of this study were to understand the impacts of increased seminal root number on seedling nitrogen and phosphorus acquisition and to model how differences in maize and teosinte phenotypes might have contributed to increased seminal root number in domesticated maize. Methods Seedling root system architectural models of a teosinte accession and a maize landrace were constructed by parameterizing the functional–structural plant model OpenSimRoot using plants grown in mesocosms. Seedling growth was simulated in a low-phosphorus environment, multiple low-nitrogen environments, and at variable planting densities. Models were also constructed to combine individual components of the maize and teosinte phenotypes. Key Results Seminal roots contributed ~35 % of the nitrogen and phosphorus acquired by maize landrace seedlings in the first 25 d after planting. Increased seminal root number improved plant nitrogen acquisition under low-nitrogen environments with varying precipitation patterns, fertilization rates, soil textures and planting densities. Models suggested that the optimal number of seminal roots for nutrient acquisition in teosinte is constrained by its limited seed carbohydrate reserves. Conclusions Seminal roots can improve the acquisition of both nitrogen and phosphorus in maize seedlings, and the increase in seed size associated with maize domestication may have facilitated increased seminal root number.

59 BASIC BIOLOGICAL SCIENCES↗

Natural variation and improved genome annotation of the emerging biofuel crop field pennycress ( Thlaspi arvense )

The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.

59 BASIC BIOLOGICAL SCIENCES↗

SCOPe: improvements to the structural classification of proteins – extended database to facilitate variant interpretation and machine learning

Abstract The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).

59 BASIC BIOLOGICAL SCIENCES↗

Strategies to identify and edit improvements in synthetic genome segments episomally

Genome engineering projects often utilize bacterial artificial chromosomes (BACs) to carry multi-kilobase DNA segments at low copy number. However, all stages of whole-genome engineering have the potential to impose mutations on the synthetic genome that can reduce or eliminate the fitness of the final strain. Here, we describe improvements to a multiplex automated genome engineering (MAGE) protocol to improve recombineering frequency and multiplexability. This protocol was applied to recoding an Escherichia coli strain to replace seven codons with synonymous alternatives genome wide. Ten 44 402–47 179 bp de novo synthesized DNA segments contained in a BAC from the recoded strain were unable to complement deletion of the corresponding 33–61 wild-type genes using a single antibiotic resistance marker. Next-generation sequencing (NGS) was used to identify 1–7 non-recoding mutations in essential genes per segment, and MAGE in turn proved a useful strategy to repair these mutations on the recoded segment contained in the BAC when both the recoded and wild-type copies of the mutated genes had to exist by necessity during the repair process. Finally, two web-based tools were used to predict the impact of a subset of non-recoding missense mutations on strain fitness using protein structure and function calls.

59 BASIC BIOLOGICAL SCIENCES↗

Improving neutrino-nuclei interaction models: Recommendations and case studies on Peelle’s Pertinent Puzzle

Improving the modeling of neutrino-nuclei interactions using data-driven methods is crucial for high-precision neutrino oscillation experiments. This paper investigates Peelle’s Pertinent Puzzle (PPP) in the context of neutrino measurements, a longstanding challenge to fitting theoretical models to experimental data. Inconsistencies in data-model comparisons hinder efforts to enhance the accuracy and reliability of model predictions. We analyze various sources contributing to these inconsistencies and propose strategies to address them, supported by practical case studies. We advocate for incorporating model fitting exercises as a standard practice in cross section publications to enhance the robustness of results. We use a common analysis framework to explore PPP-related challenges with MicroBooNE and T2K data in an unified manner. Our findings offer valuable insights for improving the accuracy and reliability of neutrino-nuclei interaction models, particularly by systematically tuning models using data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving missing transverse momentum estimation with a deep neural network

At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $^→_𝑝$$^{miss}_{T}$) is a crucial observable in many analyses. In the standard model, $^→_𝑝$$^{miss}_{T}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel deep neural network based $^→_𝑝$$^{miss}_{T}$ estimator, DeepMET, developed by the CMS Collaboration at the LHC. The DeepMET algorithm produces a weight for each reconstructed particle based on its properties. The estimator is based on the negative vector sum of the weighted transverse momenta of all reconstructed particles in an event. Compared with other estimators currently employed by CMS, DeepMET improves the $^→_𝑝$$^{miss}_{T}$ resolution by 10%–30%, shows improvement for a wide range of final states, is easier to train, and is more resilient against the effects of additional proton-proton interactions accompanying the collision of interest.

artificial neural networks↗

Improved high-gradient performance for medium-velocity superconducting half-wave resonators: Surface preparation and trapped flux mitigation

A development effort to improve the performance of superconducting radio-frequency half-wave resonators (SRF HWRs) is underway at the Facility for Rare Isotope Beams (FRIB), where 220 such resonators are in operation. Our goal was to achieve an intrinsic quality factor (𝑄 0 ) of ≥ 2 × 10 10 at an accelerating gradient (𝐸 acc ) of 12 MV/m. FRIB production resonators were prepared with buffered chemical polishing. First trials of electropolishing (EP) and post-EP low-temperature baking of FRIB HWRs allowed us to reach higher gradient (15 MV/m, limited by quench) with a higher quality factor at high gradient, but 𝑄 0 was still below our goal. Trapped magnetic flux during the Dewar test was found to be a source of 𝑄 0 reduction. Three strategies were used to reduce the trapped flux: (i) adding a local magnetic shield (LMGS) to supplement the “global” magnetic shield around the Dewar for reduction of the ambient magnetic field; (ii) performing a “uniform cooldown” (UC) to reduce the thermoelectric currents; and (iii) using a compensation coil to further reduce the ambient field with active field cancellation (AFC). The LMGS improved the 𝑄 0 , but not enough to reach our goal. With UC and AFC, we exceeded our goal, reaching 𝑄 0 = 2.8 ×10 10 at 𝐸 acc = 12 MV/m.

Cryogenics & vacuum technology↗

Efficient frequency allocation for superconducting quantum processors using improved optimization techniques

Building on previous research on frequency allocation optimization for superconducting circuit quantum processors, this work incorporates several techniques to improve overall solution quality. Here, we introduce constraints and imposed edgewise differences help to improve the optimization results. We also introduce optimization variables for the orientation of each edge, defined as the direction from the control qubit to the target qubit, to be chosen during optimization. To scale up to larger processors, multimodule designs are employed with various boundary conditions, thereby enhancing the collective yield. These enhancements allow for greater flexibility in processor design by eliminating the need for handpicked orientations. We support the efficient assembly of large processors with dense connectivity by choosing the best boundary conditions. Examples demonstrate that, at low computational cost, this optimization approach finds a frequency configuration for a square chip with over 1000 qubits and over 10% yield at much larger dispersion levels than required by previous approaches.

Zhang, Zewen [Argonne National Laboratory (ANL), A↗

Charge lifetime improvement of the Continuous Electron Beam Accelerator Facility photogun with a biased anode

GaAs photocathodes in dc high-voltage photoguns are highly susceptible to ion back-bombardment, which reduces the photocathode quantum efficiency and limits the useful operating lifetime for producing polarized electron beams. This paper demonstrates that applying a small positive bias to the photogun anode can significantly suppress ion back-bombardment and increase charge lifetime. This technique was studied extensively using the Continuous Electron Beam Accelerator Facility photogun, where highly polarized electron beams created using a strained-superlattice GaAs / GaAsP photocathode were used and charge lifetimes improved by almost a factor of 2. A new simulation code was developed to model ion production and tracking in order to better understand and explain the factors that led to the performance improvement. Results of the experiments and simulations are discussed in detail. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Improved Vertical Carrier Transport for Green III-Nitride LEDs Using ( In , Ga ) N Alloy Quantum Barriers

We report on experimental and simulation-based results using ( In , Ga ) N alloy quantum barriers in c -plane green light-emitting diode (LED) structures as a means to improve vertical carrier transport and reduce forward voltage ( V F ) . Three-dimensional device simulations that include random alloy fluctuations are used to understand carrier behavior in a disordered potential. The simulated current density–voltage ( J - V ) characteristics and modified electron-hole overlap | F mod | 2 indicate that increasing the indium fraction in the ( In , Ga ) N quantum barriers leads to a reduced polarization discontinuity at the interface between the quantum barrier and quantum well, thereby reducing V F and improving | F mod | 2 . Maps of electron and hole current through the device show a relatively homogenous distribution in the X Y plane for structures using Ga N quantum barriers; in contrast, preferential pathways for vertical transport are identified in structures with ( In , Ga ) N barriers as regions of high and low current. A positive correlation between hole (electron) current in the p -side ( n -side) barrier and indium fraction reveals that preferential pathways exist in regions of high indium content. Furthermore, a negative correlation between the strain ε z z and indium fraction shows that high indium content regions have reduced strain-induced piezoelectric polarization in the Z direction due to the mechanical constraint of the surrounding lower indium content regions. Experimentally, multiple quantum well green LEDs with ( In , Ga ) N quantum barriers exhibit lower V F and blue-shifted wavelengths relative to LEDs with Ga N quantum barriers, consistent with simulation data. These results can be used to inform heterostructure design of low V F , long-wavelength LEDs and provide important insight into the nature of carrier transport in III-nitride alloy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reducing Spontaneous Orientational Polarization via Semiconductor Dilution Improves OLED Efficiency and Lifetime

Spontaneous orientational polarization (SOP) in the electron-transport layer (ETL) of organic light-emitting diodes (OLEDs) is increasingly recognized as a key factor influencing their performance. Here, we show that SOP is dramatically reduced in the common electron-transport material 2,2',2"-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) by coevaporating it together with medium-density polyethylene. Eliminating SOP from the ETL of blue fluorescent OLEDs in this manner reduces their operating voltage by 0.5 V, increases their external quantum efficiency (EQE) by 30%, and leads to a threefold increase in device lifetime. We show that the EQE and lifetime improvements both originate from reduced exciton-polaron annihilation in the emissive layer, and that this leads to a functional relationship between the two quantities that can be used to quantify the rate of annihilation-induced degradation in the device. Furthermore, these results highlight a substantial opportunity to improve OLED performance by controlling SOP through semiconductor dilution and suggest that this capability can be used to systematically isolate and understand exciton-polaron degradation in the pursuit of stable blue OLEDs.

36 MATERIALS SCIENCE↗

Comprehensive model for evaluating voltage losses and performance improvements in thin-film photovoltaic devices

Progress of state-of-the-art and next-generation thin-film photovoltaic devices is often stymied by open-circuit voltage (𝑉 oc ) that is significantly lower than theoretical and practical limits. Yet, effectively diagnosing the primary sources of voltage loss remains challenging. Herein, a sequence of device-level characterization techniques and simulations are employed to identify and rank loss mechanisms. For the research-based Cd⁡(Se,Te) device under study, most of the loss was at the front semiconductor heterointerface due to a clifflike conduction-band offset that lowered the recombination activation energy. Additional losses due to band tails were quantified by photoluminescence analysis. The latter provided the absorption coefficient and activation energy reduction associated with band tails as inputs to device models. Simulations showed that alleviating front-interface issues would improve 𝑉 oc , but it would then be limited by bulk recombination. Further improvement of the bulk would then lead to back-contact limitations. Reducing band tails is beneficial in any circumstance. In conclusion, this analysis provides guidance for reaching toward the radiative 𝑉 oc limit.

14 SOLAR ENERGY↗

Thermal hybrid exchange-correlation density functional for improving the description of warm dense matter

Finite-temperature density functional theory (FT-DFT) has become a standard tool for first principles calculations of the properties of warm dense matter (WDM) relevant to high-energy density physics (HEDP) applications. In this work we introduce theoretical grounds of thermal hybrid exchange-correlation (XC) functionals within the generalized Mermin-Kohn-Sham scheme for an improved description of WDM. Building on the previously developed KSDT (Karasiev-Sjostrom-Dufty-Trickey) [Karasiev et al., Phys. Rev. Lett. 112, 076403 (2014)] local density approximation (LDA) and the KDT16 (Karasiev-Dufty-Trickey 2016) [Karasiev et al., Phys. Rev. Lett. 120, 076402 (2018)] generalized-gradient approximation (GGA) XC free-energy density functionals, we construct a new thermal hybrid XC functional, referred to here as KDT0. The KDT0 model at low temperature reduces to the popular ground-state PBE0 hybrid due to properties of the used KDT16 density functional approximation. Application to static calculations of electronic band gap and band structure at a wide range of temperatures for various systems of interest to HEDP show that KDT0 provides a significant improvement to the lower LDA and GGA rung XC functionals and to the ground-state PBE0 hybrid.

36 MATERIALS SCIENCE↗

Improved naive Bayesian probability classifier in predictions of nuclear mass

Recently, novel statistical methods such as neural networks and Bayesian learning methods are implemented to describe the nuclear masses. Based on previous studies, an improved naive Bayesian probability (iNBP) classifier is proposed to study the nuclear masses by refining the results of sophisticated nuclear models. In the iNBP method, the prediction for nuclear masses is treated as a classification problem. The residuals are classified into several groups to generate prior and conditional probabilities, and the posterior probabilities are further determined by the Bayesian formula. We choose the expectation with maximum probability as the final prediction. Reliability of the iNBP method is assessed by analyzing the global optimizations and the extrapolating capabilities. Here, the iNBP method exhibits impressive improvements on global descriptions for different mass models. Moreover, the method shows robust extrapolating capabilities. Results demonstrate the iNBP method can be applied to predict the nuclear masses of unknown regions. Considering the local mass relations, the iNBP method can offer considerable fine-tuning of the mass descriptions from nuclear models. The methodology proposed in this paper can also be applied to other model-based extrapolations of nuclear observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improved structure of calcium isotopes from ab initio calculations

The in-medium similarity renormalization group (IMSRG) is a powerful and flexible many-body method to compute the structure of nuclei starting from nuclear forces. Recent developments have extended the IMSRG from its standard truncation at the normal-ordered two-body level, the IMSRG(2), to a precision approximation including normal-ordered three-body operators, the IMSRG(3)-N 7 . This improvement provides a more precise solution to the many-body problem and makes it possible to quantify many-body uncertainties in IMSRG calculations. We explore the structure of 44,48,52 Ca using the IMSRG(3)-N 7 , focusing on understanding existing discrepancies of the IMSRG(2) to experimental results. We find a significantly better description of the first 2 + excitation energy of 48 Ca, improving the description of the shell closure at N=28. At the same time, we find that the IMSRG(3)-N 7 corrections to charge radii do not resolve the systematic underprediction of the puzzling large charge radius difference between 52 Ca and 48 Ca. We present estimates of many-body uncertainties of IMSRG(2) calculations applicable also to other systems based on the size extensivity of the method.

39 ≤ A ≤ 58↗