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At least 271 records · Page 15

Numerical Circuit Synthesis and Compilation for Multi-State Preparation

Near-term quantum computers have significant error rates and short coherence times, so compilation of circuits to be as short as possible is essential. Two types of compilation problems are typically considered: circuits to prepare a given state from a fixed input state, called 'state preparation'; and circuits to implement a given unitary operation, for example by 'unitary synthesis'. In this paper we solve a more general problem: the transformation of a set of m states to another set of m states, which we call 'multi-state preparation'. State preparation and unitary synthesis are special cases; for state preparation, m=1, while for unitary synthesis, m is the dimension of the full Hilbert space. We generate and optimize circuits for multi-state preparation numerically. In cases where a top-down approach based on matrix decompositions is also possible, our method finds circuits with substantially (up to 40 %) fewer two-qubit gates. We discuss possible applications, including efficient preparation of macroscopic superposition ('cat') states and synthesis of quantum channels.

Szasz, Aaron↗

Sparse Control Synthesis for Uncertain Responsive Loads With Stochastic Stability Guarantees

In this report, recent studies have demonstrated the potential of flexible loads in providing frequency response services, predominantly due to their availability and cost-effectiveness. However, uncertainty and variability in various weather-related and end-use behavioral factors often impact the reliability of demand-side control performance. This work addresses this problem with the design of a demand-side control to achieve frequency response under load uncertainties. Our approach involves modeling the load uncertainties via stochastic processes that appear as both multiplicative and additive in the power system dynamics. Recently developed mean square exponential stability (MSES) results for continuous-time linear stochastic systems are applied to pose the control synthesis problem which results in an LMI-based optimization problem. Additional costs and constraints are added to the LMI-based controller synthesis to ensure MSES, improve closed-loop transient performance, maximize tolerable uncertainties, and promote sparsity in the controller. Additionally, the fundamental limitations between the tolerable uncertainties and control efforts while ensuring MSES are discussed. Further, the control synthesis problem for the case of the full-state measurement is generalized to the case of partial-state measurements. The proposed control synthesis is illustrated on an IEEE 39 bus system with rigorous studies to demonstrate the role of sparsity, closed-loop transient performance, tolerable uncertainties, and control efforts while ensuring MSES and achieving frequency response.

42 ENGINEERING↗

Porous Ti 3 AlC 2 MAX phase enables efficient synthesis of Ti 3 C 2 T x MXene

Abstract MXenes, a large family of two‐dimensional carbides and/or nitrides, are among the most studied materials worldwide due to their great diversity of structures and compositions. Their unique properties find use in several applications. Typically, they are manufactured by selective wet‐chemical etching of layered MAX phase ceramics, which are produced nowadays primarily for MXene synthesis. However, the synthesis of MAX phases has not been changed since the time of their use in structural and high‐temperature applications, and it has not been optimized for MXene manufacturing. The main purpose of this study is to develop a porous Ti 3 AlC 2 MAX phase that can be easily ground into individual grains without time‐consuming, harsh, and tedious crushing and milling steps. Moreover, we also demonstrate the synthesis of highly porous Ti 3 AlC 2 from an inexpensive titanium sponge instead of a highly pure titanium powder and explain the mechanisms of reaction sintering and formation of porous MAX phase. MXene obtained from this MAX phase, Ti 3 C 2 Tx, shows larger flake size and higher electrical conductivity in thin films, compared to the materials produced from the costly fine titanium powder. The proposed approach may apply to the synthesis of other MAX phases as well.

Materials Science↗

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]↗

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↗

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↗

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 High Surface Area VS2 for Nitrogen Reduction

Ammonia synthesis from dinitrogen provides a critical chemical feedstock to agriculture worldwide. The dominant process for ammonia synthesis is the Haber-Bosch process, which is fossil-fuel dependent and energy intensive. The electrochemical nitrogen reduction reaction (NRR) could provide a more environmentally friendly route to industrial ammonia synthesis. We have worked to realize electrochemical NRR by developing transition metal dichalcogenide NRR catalysts. In the first part of this presentation, a VS2-based NRR electrocatalyst, which has shown promising activity and selectivity, will be presented. The synthesis of this VS2-based catalyst is straightforward and results in few-layer VS2 or VSx, (x < 2) nanoflakes. Additionally, the proposed mechanism of NRR on VS2 will be discussed, and we will discuss DFT simulation of NRR on VS2 and MoS2 as well as planned in-situ Raman experiments to probe this mechanism. In the second part of this presentation, we will share several lessons learned during our early NRR research including important points of electrochemical cell design and experimental controls to reduce environmental ammonia contamination of experiments. Finally, we will address areas of opportunity for electrochemical NRR.

dichalcogenide↗

Wet chemical synthesis and properties of argyrodite sulfide solid electrolytes for solid state lithium batteries

The commercialization of the lithium-ion battery (LIB) in 1991 was responsible for the explosion in portable electronic technologies that has been seen over the past 30 years. With the advent of electric vehicles and other high-powered technologies, there is tremendous demand for LIBs with higher energy density and high safety. To achieve this, new electrode materials must be explored. The obvious choice of anode material would be pure metal lithium, which has a theoretical specific capacity of 3860 mAh g-1 . Unfortunately, metal lithium anodes have not been widely commercialized due to their tendency to react violently with the flammable liquid electrolytes used in today’s batteries. Battery safety can best be achieved by adopting solid electrolytes in place of liquid electrolytes. Solid electrolytes are nonvolatile and nonflammable, safely allowing for the combination of high-capacity cathode materials with a Li metal anode. Argyrodite sulfide solid electrolytes such as halogen-doped Li6PS5X (X = Cl, Br, I) are noted for their high ionic conductivity. But before sulfides can be commercially adopted, they possess several disadvantages which must be addressed, including time- and energy-consuming synthesis processes, poor electrochemical stability, and intrinsically poor air stability. This dissertation seeks to address each of these challenges through materials design an synthesis strategies. In this work, we pioneer a solvent-based approach for the synthesis of argyrodite solid electrolytes Li7PS6 and Li6PS5Xinstead of a stringent solid-state synthesis. Nontoxic ethanol is employed as the solvent, enabling a rapid synthetic approach to produce argyrodite solid electrolytes with high phase purity and compositional flexibility. Compared with Li7PS6, halogen doping (i.e. X = F, Cl, Br, I) not only increases the ionic conductivity, but also enhances the electrochemical stability at the interface towards Li metal. Specifically, F-doped argyrodites produce a robust SEI layer containing LiF, contributing to enhanced interfacial stability. Finally, to address the air instability challenge, argyrodite-incorporated composite solid electrolytes (CSEs) are designed and prepared to produce stable and flexible membranes that are demonstrated in solid-state Li metal batteries. These advances push argyrodite sulfide solid electrolyte research further and pave the way for the proliferation of next generation lithium metal batteries.

25 ENERGY STORAGE↗

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium-Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition-metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. In this report, we show that an ab initio predictive synthesis strategy can be used to produce multi-gram-scale products of various MgV x O y -type phases (δ-MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg-ion battery cathodes. Characterization of these phases using 25 Mg solid-state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor-assisted population transfer (RAPT) is used as a much-needed signal-to-noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Online Bayesian State Estimation for Real-Time Monitoring of Growth Kinetics in Thin Film Synthesis

Rapid validation of newly predicted materials through autonomous synthesis requires real-time adaptive control methods that exploit physics knowledge, a capability that is lacking in most systems. Here, in this study, we demonstrate an approach to enable real-time control of thin film synthesis by combining in situ optical diagnostics with a Bayesian state estimation method. We developed a physical model for film growth and applied the direct filter (DF) method for real-time estimation of nucleation and growth rates during pulsed laser deposition (PLD). We validated the approach using simulated and experimental reflectivity data for WSe 2 growth and ultimately deployed the algorithm on an autonomous PLD system during the growth of 1T'-MoTe 2 . The DF robustly estimates growth parameters in real time at early stages of growth, down to 15% monolayer area coverage. This fusion of in situ diagnostics, data assimilation, and physical modeling opens new opportunities in adaptive control of synthesis trajectories toward desired material states.

36 MATERIALS SCIENCE↗

Room-Temperature Eutectic Synthesis for Upcycling of Cathode Materials

Ni-rich LiNixMnyCo1−x−yO2 (NMC) materials have been adopted in a range of applications, including electric vehicles. The recycled NMC material from a spent cell would be much more valuable if it could be upgraded to a Ni-rich, more energy-dense version of the material. This work demonstrates a simple, inexpensive, and facile method to upcycle LiNi1/3Mn1/3Co1/3O2 (NMC111, 160 mAh∙g−1), a cathode used in early generations of electric vehicle batteries, to LiNi0.8Mn0.1Co0.1O2 (NMC811, 190 mAh∙g−1), a more energy-dense cathode material. In this study, a preliminary investigation into a room-temperature eutectic synthesis of NMC811 is performed using NMC111, LiOH, and nickel nitrate as precursors. The synthesized material showed the desired crystal structure and stoichiometry, though the cycle life and Li diffusion coefficient need improvement when compared to commercially available NMC811. This study demonstrates an interesting proof of concept of the room-temperature eutectic synthesis process for LIB cathodes and could be improved by tuning the synthesis conditions.

lithium-ion battery↗

Ten Years of Progress in the Synthesis and Development of MXenes

Since their discovery in 2011, the number of 2D transition metal carbides and nitrides (MXenes) has steadily increased. Currently more than 40 MXene compositions exist. The ultimate number is far greater and in time they may develop into the largest family of 2D materials known. MXenes’ unique properties, such as their metal-like electrical conductivity reaching ≈20 000 S cm –1 , render them quite useful in a large number of applications, including energy storage, optoelectronic, biomedical, communications, and environmental. The number of MXene papers and patents published has been growing quickly. The first MXene generation is synthesized using selective etching of metal layers from the MAX phases, layered transition metal carbides and carbonitrides using hydrofluoric acid. Since then, multiple synthesis approaches have been developed, including selective etching in a mixture of fluoride salts and various acids, non-aqueous etchants, halogens, and molten salts, allowing for the synthesis of new MXenes with better control over their surface chemistries. In this paper, a brief historical overview of the first 10 years of MXene research and a perspective on their synthesis and future development are provided. The fact that their production is readily scalable in aqueous environments, with high yields bodes well for their commercialization.

2D materials↗