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Multiple mechanisms explain loss of anthocyanins from betalain‐pigmented Caryophyllales, including repeated wholesale loss of a key anthocyanidin synthesis enzyme

Summary In this study, we investigate the genetic mechanisms responsible for the loss of anthocyanins in betalain‐pigmented Caryophyllales, considering our hypothesis of multiple transitions to betalain pigmentation. Utilizing transcriptomic and genomic datasets across 357 species and 31 families, we scrutinize 18 flavonoid pathway genes and six regulatory genes spanning four transitions to betalain pigmentation. We examined evidence for hypotheses of wholesale gene loss, modified gene function, altered gene expression, and degeneration of the MBW (MYB‐bHLH‐WD40) trasnscription factor complex, within betalain‐pigmented lineages. Our analyses reveal that most flavonoid synthesis genes remain conserved in betalain‐pigmented lineages, with the notable exception of TT19 orthologs, essential for the final step in anthocyanidin synthesis, which appear to have been repeatedly and entirely lost. Additional late‐stage flavonoid pathway genes upstream of TT19 also manifest strikingly reduced expression in betalain‐pigmented species. Additionally, we find repeated loss and alteration in the MBW transcription complex essential for canonical anthocyanin synthesis. Consequently, the loss and exclusion of anthocyanins in betalain‐pigmented species appear to be orchestrated through several mechanisms: loss of a key enzyme, downregulation of synthesis genes, and degeneration of regulatory complexes. These changes have occurred iteratively in Caryophyllales, often coinciding with evolutionary transitions to betalain pigmentation.

59 BASIC BIOLOGICAL SCIENCES↗

Selective formation of metastable polymorphs in solid-state synthesis

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface energy in promoting the nucleation of metastable phases. Through in situ characterization and density functional theory calculations on two distinct synthesis pathways targeting LiTiOPO 4 , we demonstrate how precursor selection and its effect on reaction energy can effectively be used to control which polymorph is obtained from solid-state synthesis. A general approach is outlined to quantify the conditions under which metastable polymorphs are experimentally accessible. With comparison to historical data, this approach suggests that using appropriate precursors could enable targeted materials synthesis across diverse chemistries through selective polymorph nucleation.

36 MATERIALS SCIENCE↗

Reductive pathways in molten inorganic salts enable colloidal synthesis of III-V semiconductor nanocrystals

Colloidal quantum dots, with their size-tunable optoelectronic properties and scalable synthesis, enable applications in which inexpensive high-performance semiconductors are needed. Synthesis science breakthroughs have been key to the realization of quantum dot technologies, but important group III-group V semiconductors, including colloidal gallium arsenide (GaAs), still cannot be synthesized with existing approaches. The high-temperature molten salt colloidal synthesis introduced in this work enables the preparation of previously intractable colloidal materials. We directly nucleated and grew colloidal quantum dots in molten inorganic salts by harnessing molten salt redox chemistry and using surfactant additives for nanocrystal shape control. Synthesis temperatures above 425°C are critical for realizing photoluminescent GaAs quantum dots, which emphasizes the importance of high temperatures enabled by molten salt solvents. We generalize the methodology and demonstrate nearly a dozen III-V solid-solution nanocrystal compositions that have not been previously reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refinement

Agentic Retrieval-Augmented Code Synthesis with Iterative RefinementIn supercomputing, efficient and optimized code generation is essential to leverage high-performance systems effectively. We have developed Agentic Retrieval-Augmented Code Synthesis (ARCS), an advanced framework for accurate, robust, and efficient code generation, completion, and translation. ARCS integrates Retrieval-Augmented Generation (RAG) with Chain-of-Thought (CoT) reasoning to systematically break down and iteratively refine complex programming tasks. An agent-based RAG mechanism retrieves relevant code snippets, while real-time execution feedback drives the synthesis of candidate solutions. This process is formalized as a state-action search tree optimization, balancing code correctness with editing efficiency. Evaluations on the Geeks4Geeks and HumanEval benchmarks demonstrate that ARCS significantly outperforms traditional prompting methods in translation and generation quality. By enabling scalable and precise code synthesis, ARCS offers transformative potential for automating and optimizing code development in supercomputing applications, enhancing computational resource utilization

Bhattarai, Manish [Los Alamos National Labs]↗

Myocardial Reloading after Extracorporeal Membrane Oxygenation Alters Substrate Metabolism While Promoting Protein Synthesis

Extracorporeal membrane oxygenation (ECMO) unloads the heart providing a bridge to recovery in children after myocardial stunning. Mortality after ECMO remains high.Cardiac substrate and amino acid requirements upon weaning are unknown and may impact recovery. We assessed the hypothesis that ventricular reloading modulates both substrate entry into the citric acid cycle (CAC) and myocardial protein synthesis. Fourteen immature piglets (7.8-15.6 kg) were separated into 2 groups based on ventricular loading status: 8 hour-ECMO (UNLOAD) and post-wean from ECMO (RELOAD). We infused [2-13C]-pyruvate as an oxidative substrate and [13C6]-L-leucine, as a tracer of amino acid oxidation and protein synthesis into the coronary artery. RELOAD showed marked elevations in myocardial oxygen consumption above baseline and UNLOAD. Pyruvate uptake was markedly increased though RELOAD decreased pyruvate contribution to oxidative CAC metabolism.RELOAD also increased absolute concentrations of all CAC intermediates, while maintaining or increasing 13C-molar percent enrichment. RELOAD also significantly increased cardiac fractional protein synthesis rates by >70% over UNLOAD. Conclusions: RELOAD produced high energy metabolic requirement and rebound protein synthesis. Relative pyruvate decarboxylation decreased with RELOAD while promoting anaplerotic pyruvate carboxylation and amino acid incorporation into protein rather than to the CAC for oxidation. These perturbations may serve as therapeutic targets to improve contractile function after ECMO.

Environmental Molecular Sciences Laboratory↗

Comparative Study of Differentially Private Data Synthesis Methods

When sharing data among researchers or releasing data for public use, there is a risk of exposing sensitive information of individuals in the data set. Data synthesis is a statistical disclosure limitation technique for releasing synthetic data sets with pseudo individual records. Traditional data synthesis techniques often rely on strong assumptions of a data intruder’s behaviors and background knowledge to assess disclosure risk. Differential privacy (DP) formulates a theoretical approach for a strong and robust privacy guarantee in data release without having to model intruders’ behaviors. Efforts have been made aiming to incorporate the DP concept in the data synthesis process. Here, we examine current DIfferentially Private Data Synthesis (DIPS) techniques for releasing individual-level surrogate data for the original data, compare the techniques conceptually and evaluate the statistical utility and inferential properties of the synthetic data via each DIPS technique through extensive simulation studies. Our work sheds light on the practical feasibility and utility of the various DIPS approaches, and suggests future research directions for DIPS.

97 MATHEMATICS AND COMPUTING↗

Multiscale Modeling of Metabolism and Macromolecular Synthesis in E. coli and Its Application to the Evolution of Codon Usage

Biological systems are inherently hierarchal and multiscale in time and space. A major challenge of systems biology is to describe biological systems as a computational model, which can be used to derive novel hypothesis and drive experiments leading to new knowledge. The constraint-based reconstruction and analysis approach has been successfully applied to metabolism and to the macromolecular synthesis machinery assembly. Here, we present the first integrated stoichiometric multiscale model of metabolism and macromolecular synthesis for Escherichia coli K12 MG1655, which describes the sequence-specific synthesis and function of almost 2000 gene products at molecular detail. We added linear constraints, which couple enzyme synthesis and catalysis reactions. Comparison with experimental data showed improvement of growth phenotype prediction with the multiscale model over E. coli’s metabolic model alone. Many of the genes covered by this integrated model are well conserved across enterobacters and other, less related bacteria. We addressed the question of whether the bias in synonymous codon usage could affect the growth phenotype and environmental niches that an organism can occupy. We created two classes of in silico strains, one with more biased codon usage and one with more equilibrated codon usage than the wildtype. The reduced growth phenotype in biased strains was caused by tRNA supply shortage, indicating that expansion of tRNA gene content or tRNA codon recognition allow E. coli to respond to changes in codon usage bias. Our analysis suggests that in order to maximize growth and to adapt to new environmental niches, codon usage and tRNA content must co-evolve. These results provide further evidence for the mutation-selection-drift balance theory of codon usage bias. This integrated multiscale reconstruction successfully demonstrates that the constraintbased modeling approach is well suited to whole-cell modeling endeavors.

59 BASIC BIOLOGICAL SCIENCES↗

Functionalized Block-Copolymer Templates for Synthesis and Shape Control of Quantum Dots

In this paper, a new quantum dot synthesis method based on metallic-block copolymer precursors was developed. The synthesis produced CdS QDs assembled into chains. This method provides a new model for the study of 1D QD chains to determine its effect on charge transport and optoelectronic coupling. This synthesis method was readily extended to other semiconductor materials including PbS and perovskites producing QDs of various shapes. Finally, it evidenced further promise of this synthesis method to assist in the assembly, shape and size control of various nanomaterials.

36 MATERIALS SCIENCE↗

Modernist materials synthesis: Finding thermodynamic shortcuts with hyperdimensional chemistry

Synthesis remains a challenge for advancing materials science. A key focus of this challenge is how to enable selective synthesis, particularly as it pertains to metastable materials. This perspective addresses the question: how can “spectator” elements, such as those found in double ion exchange (metathesis) reactions, enable selective materials synthesis? By observing reaction pathways as they happen (in situ) and calculating their energetics using modern computational thermodynamics, we observe transient, crystalline intermediates that suggest that many reactions attain a local thermodynamic equilibrium dictated by local chemical potentials far before achieving a global equilibrium set by the average composition. Furthermore, using this knowledge, one can thermodynamically “shortcut” unfavorable intermediates by including additional elements beyond those of the desired target, providing access to a greater number of intermediates with advantageous energetics and selective phase nucleation. Ultimately, data-driven modeling that unites first-principles approaches with experimental insights will refine the accuracy of emerging predictive retrosynthetic models for complex materials synthesis.

36 MATERIALS SCIENCE↗

Use of Modern Chemical Protein Synthesis and Advanced Fluorescent Assay Techniques to Experimentally Validate the Functional Annotation of Microbial Genomes

The objective of this research program was to prototype methods for the chemical synthesis of predicted protein molecules in annotated microbial genomes. High throughput chemical methods were to be used to make large numbers of predicted proteins and protein domains, based on microbial genome sequences. Microscale chemical synthesis methods for the parallel preparation of peptide-thioester building blocks were developed; these peptide segments are used for the parallel chemical synthesis of proteins and protein domains. Ultimately, it is envisaged that these synthetic molecules would be ‘printed’ in spatially addressable arrays. The unique ability of total synthesis to precision label protein molecules with dyes and with chemical or biochemical ‘tags’ can be used to facilitate novel assay technologies adapted from state-of-the art single molecule fluorescence detection techniques. In the future, in conjunction with modern laboratory automation this integrated set of techniques will enable high throughput experimental validation of the functional annotation of microbial genomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Association Mapping of Cell Wall Synthesis Regulatory Genes and Cell Wall Quality in Switchgrass

Inefficient conversion of biomass to biofuels is one of the main barriers for biofuel production from such materials. Approximately half of polysaccharides in biomass remain unused by typical biochemical conversion methods. Conversion efficiency is influenced by the composition and structure of cell walls of biomass. Grasses such as wheat, maize, and rice, as well as dedicated perennial bioenergy crops, like switchgrass, make up ~55% of biomass that can be produced in the United States. Grass cell walls have a different composition and patterning compared with dicotyledonous plants, including the well-studied model plant, Arabidopsis. This project identified genetic determinants of cell wall composition in grasses using both naturally occurring genetic variation of switchgrass and gene network reconstruction and functional assays in rice. In addition, the project linked functional data in rice and other species to switchgrass improvement efforts through curation of the most abundant class of regulators in the switchgrass genome. Characterizing natural diversity of switchgrass for variation in cell wall composition and properties, also known as quality, provides an unbiased avenue for identifying biologically viable diversity in switchgrass cell walls. To characterizing natural diversity, this project generated cell wall composition and enzymatic deconstruction data for ~450 genotypes of the Switchgrass Southern Association Collection (SSAC), a diverse collection composed of 36 switchgrass accessions from the southern U.S. distribution of switchgrass. Comparing these data with other measures of cell wall quality for the same samples demonstrated the complementary nature of the diverse characterization platforms now being used for biomass characterization. Association of the composition data with ~3.2K single nucleotide variant markers identified six significant single nucleotide variant markers co-associated with digestibility and another compositional trait. These markers might be used to select switchgrass genotypes with improved composition in breeding programs for biofuel and forage production. Because the SSAC continues to be characterized by collaborators in the bioenergy community, the data generated will be used to identify additional markers in higher resolution genotyping data to approach identifying the genes and alleles that cause natural variation in switchgrass cell wall quality. For example, these markers can be surveyed in the 2100-member Oklahoma Southern and Northern Lowland switchgrass collections that this project also characterized. An orthogonal approach to biodiversity studies, using comparative functional genomics permits systematic querying of how much regulatory information is likely to be transferable from dicots to grasses and use of accumulated functional genomics resources for better-characterized grass species, such as rice, itself a biomass source in global agriculture and in certain regions. The project generated and tested a number of specific hypotheses regarding cell wall transcription factors and enzymes of grasses. To aid identification of cell wall regulators, the project assembled a novel, highdepth and -quality gene association network using a general linearized model scoring system to combine rice gene network data. Using known or putative orthologs of Arabidopsis cell wall biosynthesis genes and regulators, the project pulled from this network a cell wall sub-network that includes 96 transcription factors. Reverse genetics of a co-ortholog of the Arabidopsis MYB61 transcription factor in rice revealed that this regulatory node has evolved the ability to regulate grass-specific cell wall synthesis enzymes. A transcription factor with such activity has not been previously characterized to our knowledge, representing a major conclusion of this work. Changes in gene expression in a protoplast-based assay demonstrated positive or negative roles in cell wall regulation for eleven other transcription factors from the rice gene network. Eight of fifteen (53%) of these have not previously been examined for this function. Some of these may represent novel grass-diverged cell wall regulators, while others are likely to have this function across angiosperms. A parallel effort of this project to expand knowledge of enzymes that have evolved to function in grass cell wall synthesis, revealed that a grass-diverged enzyme in rice, OsAT 5 , ferulates monolignols that are naturally incorporated into grass cell walls. This finding opens potential natural selection avenues for improving biomass composition for downstream processing by weak base pretreatment. Thus, this project has significantly expanded knowledge of cell wall synthesis and regulation in rice, information that can be used in reverse genetics and synthetic biology approaches to re-engineer cell walls for improved production of biofuel and high-value products. To lay the foundation for translating these results directly for switchgrass improvement, the project employed a comparative phylogenetic analysis of the major group of cell wall transcription factors that have been found to function in cell wall regulation, the R 2 R 3 MYBs. This analysis concluded that known cell wall regulators are largely conserved across switchgrass, rice, maize, poplar, and Arabidopsis. This interpretation is also largely consistent with the gene network analysis described above, though both approaches provide evidence that some co-orthologs of Arabidopsis regulators have diminished or increased in importance based on gene expression patterns. Also, several clades containing dicot cell wall regulators have expanded, consistent with the evolution of new cell wall regulators. This latter result is supported by functional analysis of the R 2 R 3 MYB protein SWAM 1 in a collaboration between this project and the DOE-funded group of Dr. S. Hazen at the University of Massachusettes. The curation of the switchgrass genome through this project provides specific targets for future engineering of switchgrass cell wall regulation and may also facilitate identification of regulators that underlie the molecular markers that are genetically linked to differences in cell wall quality. With the goal of spurring further research and technological developments in lignocellulosic biofuel production, this work has been communicated to the bioenergy and cell wall communities though various presentations and publications. To date, three manuscripts have been published, two others are near to publication, three others are in an advanced state, and two to four more are likely to be written based on analyses still in progress. In addition, project participants have presented thirteen posters and talks at regional, national, and international meetings about aspects of this project. In sum, the work supported by this funding has made and communicated significant progress in identifying the genes that grasses use for cell wall synthesis and regulation, information that will be used by project participants and others to improve the efficiency of conversion of lignocellulosic biomass to biofuels.

09 BIOMASS FUELS↗

A Better Understanding of Protein Structure and Function by the Synthesis and Incorporation of Selenium- and Tellurium Containing Tryptophan Analogs

Unnatural heavy metal-containing amino acid analogs have shown to be very important in the analysis of protein structure, using methods such as X-ray crystallography, mass spectroscopy, and NMR spectroscopy. Synthesis and incorporation of selenium-containing methionine analogs has already been shown in the literature however with some drawbacks due to toxicity to host organisms. Thus synthesis of heavy metal tryptophan analogs should prove to be more effective since the amino acid tryptophan is naturally less abundant in many proteins. For example, bioincorporation of β-seleno[3,2-b]pyrrolyl-L-alanine ([4,5]SeTrp) and β-selenolo[2,3-b]pyrrolyl-L-alanine ([6,7]SeTrp) has been shown in the following proteins without structural or catalytic perturbations: human annexin V, barstar, and dihydrofolate reductase. The reported synthesis of these Se-containing analogs is currently not efficient for commercial purposes. Thus a more efficient, concise, high-yield synthesis of selenotryptophan, as well as the corresponding, tellurotryptophan, will be necessary for wide spread use of these unnatural amino acid analogs. This research will highlight our progress towards a synthetic route of both [6,7]SeTrp and [6,7]TeTrp, which ultimately will be used to study the effect on the catalytic activity of Lignin Peroxidase (LiP).

59 BASIC BIOLOGICAL SCIENCES↗

A Novel Catalytic Membrane Reactor for DME Synthesis from Renewable Resources

Production of liquid fuels or chemicals from CO 2 (captured from the air or flue gases) and renewable hydrogen presents a new approach to producing clean fuels domestically. While significant progress has been made in the area of renewable electricity generation from solar and wind, a large gap remains with respect to the production of renewable liquid fuels/chemicals. Other processes for producing liquid fuels/chemicals from renewable electricity are constrained by thermodynamic limitations, making them prohibitively expensive and impractical. The team is overcoming these limitations and developing catalytic membrane reactor processes with high yields and low energy penalties. Supported by the Advanced Research Projects Agency-Energy (ARPA-E) of the US Department of Energy (DOE), GTI Energy and partners have been developing a technology for the production of renewable dimethyl ether (DME) from carbon dioxide (CO 2 ) and renewable hydrogen (H 2 ) using a novel catalytic membrane reactor and demonstration of this system at a scale of 1 kg/day. DME is a clean-burning, non-toxic fuel with a high cetane value (55-60), making it an excellent diesel alternative. DME can be stored as a liquid under moderate pressure, eliminating the need for the high-pressure containers used for CNG or cryogenics, as in the case of LNG. DME is also approved as a renewable fuel under the U.S. Environmental Protection Agency’s Renewable Fuels Standard (RFS), making it eligible for Renewable Identification Numbers (RINs) credits. By producing DME through the catalytic conversion of captured CO 2 and renewable H 2 , this process will produce renewable liquid transportation fuel and a means of large-scale utilization of captured CO 2 . In the DME synthesis process, CO 2 and H 2 are fed to a hollow fiber catalytic membrane reactor at 300-600 psig that contains a bi-functional catalyst that combines two reactions, methanol synthesis (CO 2 + 3H 2 → CH 3 OH + H 2 O) and methanol dehydration (2CH 3 OH → CH 3 OCH 3 + H 2 O), into a one-step process to produce DME. The bifunctional catalyst converts methanol to DME, enabling higher overall CO 2 conversion. A Cu/ZnO/ZrO 2 /Al 2 O 3 (CZZA) catalyst is used for methanol synthesis and is coupled with a zeolite catalyst H-ZSM-5 for dehydration. This one-step process intensifies a process that would otherwise require multiple reaction steps. However, combining these two reactions results in increased water production which inhibits catalytic activity. Here, the Na + -gated, water-transport membrane (Science, vol. 367, pp. 667, 2020), removes water in situ, shifting the thermodynamic equilibrium towards product formation while decreasing kinetic inhibition from water adsorption onto the catalyst surface. The Na + gated, water-transport nanochannel membrane showed H 2 O/CO 2 selectivity of 560 at 250 °C and 300 psig for H 2 O/CO 2 /CO/H 2 /MeOH gas mixtures. The selectivities of H 2 O/H 2 , H 2 O/CO, and H 2 O/MeOH were 190, 170, and 80, respectively. In a laboratory-scale membrane reactor, DME synthesis testing using this membrane, a DME production rate of 440 g DME /kg cat /h was achieved at 260 °C and 550 psig. Compared to the packed bed reactor, the CO 2 conversion and DME production rate in the membrane reactor were 80% and three times higher, respectively. A prototype test system (1 kg/day) was designed, constructed, and tested. A DME production rate of 1.31 kg/day and a DME productivity of 360 g/h/kg were achieved in the prototype membrane reactor. Good stability was demonstrated during 150-h continuous operation and multiple startups/shutdowns tests.

10 SYNTHETIC FUELS↗

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗

Segmented Microfluidic Flow Reactors for Nanomaterial Synthesis

Microfluidic reactors have remarkably promoted the synthesis and investigation of advanced nanomaterials due to their continuous mode and accelerated heat/mass transfer. Notably, segmented microfluidic flow reactors (SMFRs) are an important class of microfluidic reactors that have been developed to accurately manipulate nanomaterial synthesis by further improvement of the residence time distributions and unique flow behaviors. This review provided a survey of the nanomaterial synthesis in SMFRs for the aspects of fluid dynamics, flow patterns, and mass transfer among and within distinct phases and provided examples of the synthesis of versatile nanomaterials via the use of different flow patterns.

36 MATERIALS SCIENCE↗

Synthesis of optical birefringent networks.

Outline of synthesis procedures, with description of the birefringent networks which result from their use. Optical compensators are employed in synthesis procedures in two different ways. The first role is simply the practical one of compensating for slightly incorrect crystal lengths. The second role occurs because some synthesis procedures require different fractional retardations for the stages of the network. Lyot and Solc filters are described, and an attempt is made to show how birefringent networks function. Experimental results are presented, and the application of synthesis procedures to electrooptic networks is discussed.

Ammann, E. O.↗

Synthesis of oscillating adaptive feedback systems

A synthesis theory is developed which allows system design to proceed from practical specifications on system command and/or disturbance response to a design which is very nearly optimal in terms of feedback sensor noise effects. The approach taken is to replace the nonlinear element by a mean square error minimizing approximation (dual-input describing function), and then use linear frequency domain synthesis techniques subject to additional constraints imposed by the limit cycle and the approximator. Synthesis techniques are also developed for a similar system using an externally excited oscillating signal with the above approach. The results remove the design of the systems considered from the realm of simulation and experimentation, permitting true synthesis and the optimization that accompanies it.

Smay, J. W.↗

Synthesis of multiple shaped beam antenna patterns

Results are presented of research into the problem of finding an excitation of a given antenna such that the desired radiation pattern is approximated to within acceptable limits. This is to be done in such a fashion that boundary conditions involving hardware limitations may be inserted into the problem. The intended application is synthesis of multiple shaped beam antennas. Since this is perhaps the most difficult synthesis problem an antenna engineer is likely to encounter, the approach taken was to include as a by-product capability for synthesizing simpler patterns. The synthesis technique has been almost totally computerized. The class of antennas which may be synthesized with the computer program are those which may be represented as planar (continuous or discrete) current distributions. The technique is not limited in this sense and could indeed by extended to include, for example, the synthesis of conformal arrays or current distributions on the surface of reflectors. The antenna types which the program is set up to synthesize are: line source, rectangular aperture, circular aperture, linear array, rectangular array, and arbitrary planar array.

Stutzman, W. L.↗