Search NASA⌕ Search

SEARCH · Search NASA

Results for “combinatorial optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

Enhanced mRNA delivery into lymphocytes enabled by lipid-varied libraries of charge-altering releasable transporters

We report a strategy for generating a combinatorial library of oligonucleotide transporters with varied lipid domains and their use in the efficient transfection of lymphocytes with mRNA in vitro and in vivo. This library is based on amphiphilic charge-altering releasable transporters (CARTs) that contain a lipophilic block functionalized with various side-chain lipids and a polycationic α-amino ester mRNA-binding block that undergoes rearrangement to neutral small molecules, resulting in mRNA release. We show that certain binary mixtures of these lipid-varied CARTs provide up to a ninefold enhancement in mRNA translation in lymphocytes in vitro relative to either a single-lipid CART component alone or the commercial reagent Lipofectamine 2000, corresponding to a striking increase in percent transfection from 9–12% to 80%. Informed by the results with binary mixtures, we further show that CARTs consisting of optimized ratios of the two lead lipids incorporated into a single hybrid-lipid transporter molecule maintain the same delivery efficacy as the noncovalent mixture of two CARTs. The lead lipid CART mixtures and hybrid-lipid CARTs show enhanced lymphocyte transfection in primary T cells and in vivo in mice. This combinatorial approach for rapidly screening mRNA delivery vectors has provided lipid-varied CART mixtures and hybrid-lipid CARTs that exhibit significant improvement in mRNA delivery to lymphocytes, a finding of potentially broad value in research and clinical applications.

59 BASIC BIOLOGICAL SCIENCES↗

Carbon-negative production of acetone and isopropanol by gas fermentation at industrial pilot scale

Many industrial chemicals that are produced from fossil resources could be manufactured more sustainably through fermentation. In this work, we describe the development of a carbon-negative fermentation route to producing the industrially important chemicals acetone and isopropanol from abundant, low-cost waste gas feedstocks, such as industrial emissions and syngas. Using a combinatorial pathway library approach, we first mined a historical industrial strain collection for superior enzymes that we used to engineer the autotrophic acetogen Clostridium autoethanogenum. Next, we used omics analysis, kinetic modeling and cell-free prototyping to optimize flux. Finally, we scaled-up our optimized strains for continuous production at rates of up to ~3 g/L/h and ~90% selectivity. Life cycle analysis confirmed a negative carbon footprint for the products. Unlike traditional production processes, which result in release of greenhouse gases, our process fixes carbon. These results show that engineered acetogens enable sustainable, high-efficiency, high-selectivity chemicals production. We expect that our approach can be readily adapted to a wide range of commodity chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Combinatorial Discovery of Lanthanum–Tantalum Oxynitride Solar Light Absorbers with Dilute Nitrogen for Solar Fuel Applications

© 2017 American Chemical Society. Oxynitrides with the photoelectrochemical stability of oxides and desirable band energetics of nitrides comprise a promising class of materials for solar photochemistry. Challenges in synthesizing a wide variety of oxynitride materials has limited exploration of this class of functional materials, which we address using a reactive cosputtering combined with rapid thermal processing method to synthesize multi-cation-multi-anion libraries. We demonstrate the synthesis of a LaxTa1-xOyNzthin film composition spread library and its characterization by both traditional thin film materials characterization and custom combinatorial optical spectroscopy and X-ray absorption near edge spectroscopy (XANES) techniques, ultimately establishing structure-chemistry-property relationships. We observe that over a substantial La-Ta composition range the thin films crystallize in the same perovskite LaTaON2structure with significant variation of anion chemistry. The relative invariance in optical band gap demonstrates a remarkable decoupling of composition and band energetics so that the composition can be optimized while retaining the desirable 2 eV band gap energy. We also demonstrate the intercalation of diatomic nitrogen into the La3TaO7structure, which gives rise to a direct-allowed optical transition at 2.2 eV, less than half the value of the oxide's band gap. These findings motivate further exploration of the visible light response of this material that is predicted to be stable over a wide range of electrochemical potential.

Suram, Santosh K.↗

Accelerated development of CuSbS 2 thin film photovoltaic device prototypes

Development of alternative thin film photovoltaic technologies is an important research topic because of the potential of low-cost, high-efficiency solar cells to produce terawatt levels of clean power. However, this development of unexplored yet promising absorbers can be hindered by complications that arise during solar cell fabrication. Here, a high-throughput combinatorial method is applied to accelerate development of photovoltaic devices, in this case, using the novel CuSbS2 absorber via a newly developed three-stage self-regulated growth process to control absorber purity and orientation. Photovoltaic performance of the absorber, using the typical substrate CuInxGa1 - xSe2 (CIGS) device architecture, is explored as a function of absorber quality and thickness using a variety of back contacts. This study yields CuSbS2 device prototypes with ~1% conversion efficiency, suggesting that the optimal CuSbS2 device fabrication parameters and contact selection criteria are quite different than for CIGS, despite the similarity of these two absorbers. The CuSbS2 device efficiency is at present limited by low short-circuit current because of bulk recombination related to defects, and a small open-circuit voltage because of a theoretically predicted cliff-type conduction band offset between CuSbS2 and CdS. Overall, these results illustrate both the potential and limits of combinatorial methods to accelerate the development of thin film photovoltaic devices using novel absorbers.

14 SOLAR ENERGY↗

Embedding Equality Constraints of Optimization Problems into a Quantum Annealer

Quantum annealers such as D-Wave machines are designed to propose solutions for quadratic unconstrained binary optimization (QUBO) problems by mapping them onto the quantum processing unit, which tries to find a solution by measuring the parameters of a minimum-energy state of the quantum system. While many NP-hard problems can be easily formulated as binary quadratic optimization problems, such formulations almost always contain one or more constraints, which are not allowed in a QUBO. Embedding such constraints as quadratic penalties is the standard approach for addressing this issue, but it has drawbacks such as the introduction of large coefficients and using too many additional qubits. In this paper, we propose an alternative approach for implementing constraints based on a combinatorial design and solving mixed-integer linear programming (MILP) problems in order to find better embeddings of constraints of the type Σ x i = k for binary variables x i . Our approach is scalable to any number of variables and uses a linear number of ancillary variables for a fixed k.

97 MATHEMATICS AND COMPUTING↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

Combinatorial Cu-Ni Alloy Thin-Film Catalysts for Layer Number Control in Chemical Vapor-Deposited Graphene

We synthesized a combinatorial library of CuxNi1−x alloy thin films via co-sputtering from Cu and Ni targets to catalyze graphene chemical vapor deposition. The alloy morphology, composition, and microstructure were characterized via scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDS), and X-ray diffraction (XRD), respectively. Subsequently, the CuxNi1−x alloy thin films were used to grow graphene in a CH4-Ar-H2 ambient at atmospheric pressure. The underlying rationale is to adjust the CuxNi1−x composition to control the graphene. Energy dispersive x-ray spectroscopy (EDS) analysis revealed that a continuous gradient of CuxNi1−x (25 at. % < x < 83 at.%) was initially achieved across the 100 mm diameter substrate (~0.9%/mm composition gradient). The XRD spectra confirmed a solid solution was realized and the face-centered cubic lattice parameter varied from ~3.52 to 3.58 A˙, consistent with the measured composition gradient, assuming Vegard’s law. Optical microscopy and Raman analysis of the graphene layers suggest single layer growth occurs with x > 69 at.%, bilayer growth dominates from 48 at.% < x < 69 at.%, and multilayer (≥3) growth occurs for x < 48 at.%, where x is the Cu concentration. Finally, a large area of bi-layer graphene was grown via a CuxNi1−x catalyst with optimized catalyst composition and growth temperature.

2D materials↗

Combinatorial Insights into Doping Control and Transport Properties of Zinc Tin Nitride

ZnSnN 2 is an Earth-abundant semiconductor analogous to the III–nitrides with potential as a solar absorber due to its direct bandgap, steep absorption onset, and disorder-driven bandgap tunability. Despite these desirable properties, discrepancies in the fundamental bandgap and degenerate n-type carrier density have been prevalent issues in the limited amount of literature available on this material. We we use a combinatorial RF co-sputtering approach, we explored a growth-temperature-composition space for Zn 1+x Sn 1-x N 2 over the ranges 35–340 °C and 0.30–0.75 Zn/(Zn + Sn). In this way, we identified an optimal set of deposition parameters for obtaining as-deposited films with wurtzite crystal structure and carrier density as low as 1.8 × 10 18 cm -3 . Films grown at 230 °C with Zn/(Zn + Sn) = 0.60 were found to have the largest grain size overall (70 nm diameter on average) while also exhibiting low carrier density (3 × 10 18 cm -3 ) and high mobility (8.3 cm 2 V -1 s -1 ). Using this approach, we establish the direct bandgap of cation-disordered ZnSnN 2 at 1.0 eV. Moreover, we report tunable carrier density as a function of cation composition, in which lower carrier density is observed for higher Zn content. Consequently, this relationship manifests as a Burstein–Moss shift widening the apparent bandgap as cation composition moves away from Zn-rich. Collectively, these findings provide important insight into the fundamental properties of the Zn–Sn–N material system and highlight the potential to utilize ZnSnN 2 for photovoltaics.

14 SOLAR ENERGY↗

Application of Peracetic Acid in Poultry Processing: Effects of Treatment Dynamics and Emerging Risk of Resistance Development in Salmonella spp.

Nontyphoidal Salmonella is a leading cause of foodborne illness, with poultry representing a major source. Peracetic acid (PAA), a widely adopted antimicrobial in poultry processing, offers advantages over traditional disinfectants but has sparked interest in its combined use with other antimicrobials and potential resistance. This review evaluates the efficacy of PAA in mitigating Salmonella in combination with other food-grade antimicrobials, explores possible synergism, efficacy under varying treatment parameters, resistance development against PAA, and its role in resistance evolution. While PAA demonstrates broad-spectrum efficacy, its performance varies with environmental parameters; higher temperatures generally enhance antimicrobial action but also accelerate PAA degradation. Organic matter diminishes PAA efficacy by reactive quenching. Variability in concentration and contact time further influences outcomes. Despite its oxidative mode of action and presumed low risk for resistance, emerging studies indicate that Salmonella can develop adaptive tolerance and potential cross/coresistance following repeated or sublethal exposure to PAA. These adaptations may involve genetic upregulation of oxidative stress response pathways, efflux systems, and modifications in cell membrane integrity, raising concerns about the long-term sustainability of PAA use. Additionally, combinatorial treatments (e.g., PAA with UV-C, enzymes, or organic acids) show promise in enhancing efficacy while mitigating resistance risks. Despite recognition of PAA's safety and effectiveness, knowledge gaps remain regarding standardized resistance definitions, serotype-specific tolerance, and optimal intervention strategies in commercial settings. Therefore, there is a need for standardized testing protocols, robust studies on potential resistance, and further exploration of synergistic PAA applications to ensure sustained poultry product safety and public health protection.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

High-Throughput Combinatorial Development of High-Entropy Alloys For Light-Weight Structural Applications

The primary limitation of today’s lightweight structural alloys is that specific yield strengths (SYS) higher than 200MPa x cc/g (typical value for titanium alloys) are extremely difficult to achieve. This holds true especially at a cost lower than 5dollars/kg (typical value for magnesium alloys). Recently, high-entropy alloys (HEA) have shown promising SYS, yet the large composition space of HEA makes screening compositions complex and time-consuming. Over the course of this 2-year project we started from 150 billion compositions and reduced the number of potential low-density (<5g/cc), low-cost (<5dollars/kg) high-entropy alloy (LDHEA) candidates that are single-phase, disordered, solid-solution (SPSS) to a few thousand compositions. This was accomplished by means of machine learning to guide design for SPSS LDHEA based on a combination of recursive partitioning, an extensive, experimental HEA database compiled from 24 literature sources, and 91 calculated parameters serving as phenomenological selection rules. Machine learning shows an accuracy of 82% in identifying which compositions of a separate, smaller, experimental HEA database are SPSS HEA. Calculation of Phase Diagrams (CALPHAD) shows an accuracy of 71-77% for the alloys supported by the CALPHAD database, where 30% of the compiled HEA database is not supported by CALPHAD. In addition to machine learning, and CALPHAD, a third tool was developed to aid design of SPSS LDHEA. Phase diagrams were calculated by constructing the Gibbs-free energy convex hull based on easily accessible enthalpy and entropy terms. Surprisingly, accuracy was 78%. Pursuing these LDHEA candidates by high-throughput experimental methods resulted in SPSS LDHEA composed of transition metals (e.g. Cr, Mn, Fe, Ni, Cu) alloyed with Al, yet the high concentration of Al, necessary to bring the mass density below 5.0g/cc, makes these materials hard and brittle, body-centered-cubic (BCC) alloys. A related, yet multi-phase BCC alloy, based on Al-Cr-Fe-Ni, shows compressive strain >10% and specific compressive yield strength of 229 MPa x cc/g, yet does not show ductility in tensile tests due to cleavage. When replacing Cr in Al-Cr-Fe-based 4- and 5-element LDHEA with Mn, hardness drops 2x. Combined with compression test results, including those on the ternaries Al-Cr-Fe and Al-Mn-Fe suggest that Al-Mn-Fe-based LDHEA are still worth pursuing. These initial results only represent one compressive stress-strain curve per composition without any property optimization. As such, reproducibility needs to be followed by optimization to show their full potential. When including Li, Mg, and Zn, single-phase Li-Mg-Al-Ti-Zn LDHEA has been found with a specific ultimate compressive strength of 289MPa x cc/g. Al-Ti-Mn-Zn showed a specific ultimate compressive strength of 73MPa x cc/g. These initial results after hot isostatic pressing (HIP) of the ball-milled powders represent the lower end of what is possible, since no secondary processing (e.g. extrusion) has been performed to optimize strength and ductility. Compositions for multi-phase (e.g. dual-phase) LDHEA were identified largely by automated searches through CALPHAD databases, while screening for large face-centered-cubic (FCC) volume fractions, followed by experimental verification. This resulted in several new alloys. Li-Mg-Al-Mn-Fe and Mg-Mn-Fe-Co ball-milled powders upon HIP show specific ultimate compressive strengths of 198MPa x cc/g and 45MPa x cc/g, respectively. Several malleable quarternary Al-Zn-based alloys have been found upon arc/induction melting, yet with limited specific compressive yield strength (<75 MPa x cc/g). These initial results are all without any optimization for strength and/or ductility. High-throughput experimentation allowed us to triple the existing experimental HEA database as published in the past 10 years in less than 2 years which happened at a rate 10x higher than previous methods. Furthermore, we showed that high-throughput thin-film combinatorial methods can be used to get insight in isothermal phase diagram slices. Although it is straightforward to map hardness as a function of composition for sputtered, thin-film, compositional gradients by nano-indentation and compare the results to micro-indentation on bulk samples, the simultaneous impact of composition, roughness, film density, and microstructure on hardness requires monitoring all these properties as a function of location on the compositional gradient, including dissecting the impact of these 4 factors on the hardness map. These additional efforts impact throughput significantly. This work shows that a lot of progress has been made over the years in predicting phase formation that aids the discovery of new alloys, yet that a lot of work needs to be done to predict phases more accurately for LDHEA, whether done by CALPHAD or by other means. More importantly, more work needs to be done to predict mechanical properties of novel alloys, like yield strength, and ductility. Furthermore, this work shows that there is a need for the generation of an empirical alloy database covering strategic points in a multi-dimensional composition space to allow for faster and more accurate predictive interpolations to identify the oasis in the dessert more quickly. Finally, this work suggests that it is worth pursuing a ductile alloy with a SYS > 300 MPa x cc/g in a mass density range of 6-7 g/cc, since the chances for a single-phase or majority-phase FCC increase significantly. Today’s lightweight steels are in this density range.

36 MATERIALS SCIENCE↗

Micellar Surfactant Association in the Presence of a Glucoside-based Amphiphile Detected via High-Throughput Small Angle X-ray Scattering

The interactions of mixtures of anionic and amphoteric surfactants with sugar amphiphiles were studied via high throughput small angle x-ray scattering (SAXS). The sugar amphiphile was composed of Caprate, Caprylate, and Oleate mixed ester of methyl glucoside, MeGCCO. Optimal surfactant interactions are sought which have desirable physical properties, which must be identified in a cost effective manner that can access the large phase space of possible molecular combinations. X-ray scattering patterns obtained via high throughput SAXS can probe a combinatorial sample space and reveal the incorporation of MeGCCO into the micelles and the molecular associations between surfactant molecules. Such data make it possible to efficiently assess the effects of the new amphiphiles in the formulation. A specific finding of this study is that formulations containing comparatively monodisperse and homogeneous surfactant mixtures can be reliably tuned by addition of NaCl, which swells the surfactant micelles with a monotonic dependence on salt concentration. In contrast, the presence of multiple different surfactants destroys clear correlations with NaCl concentration, even in otherwise similar series of formulations.

36 MATERIALS SCIENCE↗

The Evolution of Software and Its Impact on Complex System Design in Robotic Spacecraft Embedded Systems

The growth in computer hardware performance, coupled with reduced energy requirements, has led to a rapid expansion of the resources available to software systems, driving them towards greater logical abstraction, flexibility, and complexity. This shift in focus from compacting functionality into a limited field towards developing layered, multi-state architectures in a grand field has both driven and been driven by the history of embedded processor design in the robotic spacecraft industry.The combinatorial growth of interprocess conditions is accompanied by benefits (concurrent development, situational autonomy, and evolution of goals) and drawbacks (late integration, non-deterministic interactions, and multifaceted anomalies) in achieving mission success, as illustrated by the case of the Mars Reconnaissance Orbiter. Approaches to optimizing the benefits while mitigating the drawbacks have taken the form of the formalization of requirements, modular design practices, extensive system simulation, and spacecraft data trend analysis. The growth of hardware capability and software complexity can be expected to continue, with future directions including stackable commodity subsystems, computer-generated algorithms, runtime reconfigurable processors, and greater autonomy.

software↗

Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

Sawhill, Bruce↗

The Effect of Membrane Structure Prepared from Carboxymethyl Cellulose and Cellulose Nanofibrils for Cationic Dye Removal

Water-stable and eco-friendly membranes were fabricated from carboxymethyl cellulose (CMC) acting as anionic adsorbent and cellulose nanofibrils (CNFs) as strengthening filler by solvent- and unidirectional freeze-casting processes, both supported with simultaneous citric acid (CA) mediated cross-linking. Spectroscopic, thermogravimetric and potentiometric titration techniques were applied to evaluate the efficacy of the cross-linking as well as to quantify the processing-dependant surface charge. In addition, the CMC/CNF assembling and membrane porosity were identified microscopically as the combinatorial effect of components ratio and the applied fabrication technique. Finally, the membrane’s cationic dyes adsorption capacity and kinetic were evaluated depending on the dyes ionization constants, solution pH, and the contact time using batch equilibrium experiment, and further evaluated for filtration performance at optimal pH. The resulting, freeze-casted membranes demonstrate anisotropic to isotropic and highly (> 90%) porous structures with gradient pore sizes (from few nm up to 200 µm range). This provides relatively high and stable flux rates (150–190 kL/m{sup 2} h MPa) with ~ 100% cationic dye adsorption, fast dynamic (8.536–5.446 kg/g min) and capacity (1828–1398 g/kg), which highlight their potential in dead-end filtration technologies without need for additional separation step. The similar dye adsorption capacity was assessed for denser and nano-porous (< 50 nm) solvent-casted membranes, however, with much lower and time-declining flux rates (100–10 L/m{sup 2} h MPa), demonstrating their potential usage in spiral wound-cross-flow modules. Both types of membranes anyhow showed high dye removal capacity (≥ 90%) even after 4th (solvent-casted) and 50th (freeze-casted) reusing cycle, present a high-value alternative to commercial activated carbons or other bio-nano-absorbents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

COHORT: Coordination of Heterogeneous Thermostatically Controlled Loads for Demand Flexibility

Demand flexibility is increasingly important for power grids. Careful coordination of thermostatically controlled loads (TCLs) can modulate energy demand, decrease operating costs, and increase grid resiliency. We propose a novel distributed control framework for the Coordination Of HeterOgeneous Residential Thermostatically controlled loads (COHORT). COHORT is a practical, scalable, and versatile solution that coordinates a population of TCLs to jointly optimize a grid-level objective, while satisfying each TCL’s end-use requirements and operational constraints. To achieve that, we decompose the grid-scale problem into subproblems and coordi- nate their solutions to find the global optimum using the alternating direction method of multipliers (ADMM). The TCLs’ local problems are distributed to and computed in parallel at each TCL, making COHORT highly scalable and privacy-preserving. While each TCL poses combinatorial and non-convex constraints, we characterize these constraints as a convex set through relaxation, thereby making COHORT computationally viable over long planning horizons. After coordination, each TCL is responsible for its own control and tracks the agreed-upon power trajectory with its preferred strategy. In this work, we translate continuous power back to discrete on/off actuation, using pulse width modulation. COHORT is generalizable to a wide range of grid objectives, which we demonstrate through three distinct use cases: generation following, minimizing ramping, and peak load curtailment. In a notable experiment, we validated our approach through a hardware-in-the-loop simulation, including a real-world air conditioner (AC) controlled via a smart thermostat, and simulated instances of ACs modeled after real-world data traces. During the 15-day experimental period, COHORT reduced daily peak loads by an average of 12.5% and maintained comfortable temperatures.

demand response↗

Systematic Process Intensification involving Zeotropic Distillation

Distillation is commonly used for separating homogeneous fluid mixtures. While it is based on a simple thermally driven vapor-liquid equilibrium phenomenon at the two-phase region, different variants of distillation systems exist. These include simple distillation, dividing wall columns, pressure swing distillation, thermally coupled distillation and reactive distillation. Complex separation may also involve multiple distillation in a sequence to achieve the desired products. These sequences can be constructed as direct sequence, indirect sequence or thermally coupled columns. Even when a sequence is fixed, each column in the sequence can have a plethora of design alternatives to consider. All these make the design and intensification of distillation systems a challenging task. The large number of plausible design alternatives increases the combinatorial complexity for screening. Although significant efforts have been made in the past, we still lack a method for systematic identification of novel pathways for process intensification of distillation system. This is due to the lack of a generalized representation of all plausible alternatives in a single modeling and optimization framework. In this work, we first present a general representation of thermally driven vapor-equilibrium phenomenon using abstract building blocks. Specifically, each tray in a distillation column is represented by a liquid block and a vapor block with a shared semi-restricted boundary representing the interface. The arrangement of these building blocks in a two-dimensional grid gives rise to all plausible variants of distillation systems. These systems range from simple distillation, dividing wall columns to task-integrated columns. This enables us to systematically identify both classic and out-of-the-box intensified designs at the column and flowsheet levels. The overall distillation-based separation process synthesis problem is formulated as a single mixed-integer nonlinear programming (MINLP) model. In conclusion, the proposed approach is applied to multi-component zeotropic systems to show the capability of identifying promising intensified alternatives.

42 ENGINEERING↗

Machine Learning Applied to Zeolite Synthesis: The Missing Link for Realizing High-Throughput Discovery

Zeolites are microporous crystalline materials with well-defined cavities and pores, which can be prepared under different pore topologies and chemical compositions. Their preparation is typically defined by multiple interconnected variables (e.g., reagent sources, molar ratios, aging treatments, reaction time and temperature, among others), but unfortunately their distinctive influence, particularly on the nucleation and crystallization processes, is still far from being understood. Thus, the discovery and/or optimization of specific zeolites is closely related to the exploration of the parametric space through trial-and-error methods, generally by studying the influence of each parameter individually. In the past decade, machine learning (ML) methods have rapidly evolved to address complex problems involving highly nonlinear or massively combinatorial processes that conventional approaches cannot solve. Considering the vast and interconnected multiparametric space in zeolite synthesis, coupled with our poor understanding of the mechanisms involved in their nucleation and crystallization, the use of ML is especially timely for improving zeolite synthesis. Indeed, the complex space of zeolite synthesis requires drawing inferences from incomplete and imperfect information, for which ML methods are very well-suited to replace the intuition-based approaches traditionally used to guide experimentation. In this Account, we contend that both existing and new ML approaches can provide the “missing link” needed to complete the traditional zeolite synthesis workflow used in our quest to rationalize zeolite synthesis. Within this context, we have made important efforts on developing ML tools in different critical areas, such as (1) data-mining tools to process the large amount of data generated using high-throughput platforms; (2) novel complex algorithms to predict the formation of energetically stable hypothetical zeolites and guide the synthesis of new zeolite structures; (3) new “ab initio” organic structure directing agent predictions to direct the synthesis of hypothetical or known zeolites; (4) an automated tool for nonsupervised data extraction and classification from published research articles. ML has already revolutionized many areas in materials science by enhancing our ability to map intricate behavior to process variables, especially in the absence of well-understood mechanisms. Undoubtedly, ML is a burgeoning field with many future opportunities for further breakthroughs to advance the design of molecular sieves. For this reason, this Account includes an outlook of future research directions based on current challenges and opportunities. We envision this Account will become a hallmark reference for both well-established and new researchers in the field of zeolite synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Codesigning Alloy Compositions of CdSe y Te 1− y Absorbers and Mg x Zn 1− x O Contacts to Increase Solar Cell Efficiency

Thin‐film solar cells such as CdTe are a major commercial photovoltaic technology, with more than 25 GW installed worldwide and levelized costs of electricity competitive with fossil fuels. Further progress may result from integrating CdSe y Te 1− y absorbers with Mg x Zn 1− x O contacts, but the device efficiency is difficult to maximize due to coupled dependence on chemical composition of both alloys. Herein, a high‐throughput approach is demonstrated to codesign chemical compositions in alloyed Mg x Zn 1− x O/CdSe y Te 1− y thin‐film solar cells, using combinatorial libraries of PV devices with orthogonal composition gradients in CdSe y Te 1− y absorbers and Mg x Zn 1− x O contacts. It is found that the solar cell performance is a strong and coupled function of both elemental compositions, with efficiency up to 17.7% ( V OC = 836 mV, fill factor = 69%, J SC = 30.6 mA cm −2 ) at atomic compositions of Mg/(Mg + Zn) ≈18% and average Se/(Se + Te) ≈4%. These performance trends among >100 devices are explained by >100 ns lifetime of photoexcited charge carriers at the Mg x Zn 1− x O/CdSe y Te 1− y interface where strong Se accumulation is also observed. This study reports the optimal compositions of the commercially relevant Mg x Zn 1− x O/CdSe y Te 1− y solar cells and demonstrates a general approach to codesigning performance of alloyed thin‐film solar cells and other optoelectronic devices.

14 SOLAR ENERGY↗