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At least 289 records · Page 16

Soot Formation and Ignition Characteristics of Ethanol/Gasoline Blends in a Rapid Compression Machine

With the ever-increasing demand for sustainable energy, alcohol fuels have garnered interest for use in heavy duty engines. The significant infrastructure for ethanol production and blending of ethanol with gasoline make these fuels/fuel blends desirable candidates. However, development of heavy duty engine technology that is capable of burning alcohol fuels while retaining the advantages of traditional diesel combustion requires an improved understanding of the soot formation for these fuels under conditions relevant to mixing-controlled combustion. This work uses an extinction diagnostic to study the sooting tendency of ethanol and gasoline/ethanol blends ranging from E10 to E98 during ignition in a homogeneous environment. Experiments were conducted in a rapid compression machine (RCM) for compressed conditions of 20 ± 1 bar and an approximately constant temperature (± 10K) which was unique for each fuel. For a given soot volume fraction, a linear relationship was observed between ethanol content and the equivalence ratio in which that soot volume fraction was formed. Accounting for the oxygenated nature of ethanol, E85 and E98 fuels produced similar amounts of soot at a given Φ ox, , suggesting other factors outside of fuel oxygen content, such as fuel morphology, impact soot formation. Ignition delay data is reported for compressed pressures of 20 ± 1 bar and compressed temperatures ranging from 633 – 670 K for E10 and 771 – 789 K for E98. Varying pressures for E10 and E98 at conditions producing similar soot volume fractions demonstrated a linear dependence of soot formation on pressure, regardless of if the pressure considered was at top dead center or peak combustion pressure. Furthermore, the data gleaned from this work will be used to select soot models and chemical kinetic mechanisms for RCM simulations to ultimately model heavy duty engine technology with the studied fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Surface Chemistry and Particle Morphology Changes in Pine Biomass under Indirect Thermal Gradients: Implications for Feed Screw Design

The conversion of biomass feedstocks into fuels and chemicals using fast pyrolysis is a promising approach to renewable energy. Feed screws that convey biomass to pyrolysis reactors, however, often encounter plugging. Indirect heating of the feed screw occurs due to contact with the pyrolysis chamber, resulting in a heating gradient ranging from ambient temperature (22 °C) to reactor temperature (500 °C). Given that major cell wall macromolecules, such as lignin, cellulose, and hemicellulose, begin to produce bio-oils and volatile resin acid compounds within this temperature gradient, we hypothesized that indirect heating during feed screw conveyance is sufficient to cause premature degradation of biomass. We characterized this degradation by observing increases in surface roughness, changes in overall particle morphology, and the production and deposition of bio-oils on biomass particle surfaces. Correlative analysis between optical in situ hot-stage microscopy, confocal Raman spectroscopy, and SEM analysis revealed that heating at temperatures as low as 375 °C caused significant increases in surface roughness, with large fissures forming between and within cell walls. Additionally, droplets of bio-oil were observed on particles, especially in the bark and cambium samples. This work suggests that these phenomena contribute to particle agglomeration, leading to feed screw plugging, and that engineering a solution to cool the feed screw could prevent particle agglomeration and reduce plugging incidents, thereby increasing biomass processing efficiency.

09 BIOMASS FUELS↗

Hardware, methodology and applications of 2 + D backscatter Mössbauer spectroscopy with simultaneous x-ray and γ-ray detection

Abstract A unique method is presented for the acquisition and analysis of 57 Fe backscatter Mössbauer spectra with simultaneous detection of the resonant 14.4 keV γ -rays and the characteristic 6.4 keV x-rays, using a custom-built multi-parameter analyser constructed on the basis of commercial analogue to digital converters and high-speed digital latches. The system allows for the simultaneous registration of Doppler-modulation velocities and photon energies, with up to 4096 and 8192 digital channels respectively. This arrangement is in contrast to most related systems, which detect at a single narrow energy window per detector. Samples of arbitrary atomic structure, morphology and surface topography can be studied without altering the setup or the analysis procedure, provided that the samples are at least micrometre sized. The hardware and software that are used to acquire data with minimal dead time are described and the custom and self-contained methods for post-measurement energy discrimination, background correction and velocity-axis folding are discussed. The data are fit using a general Hamiltonian model for the nuclear energy levels of 57 Fe and a quantum mechanical description of the angular momentum coupling is utilised, with consideration of the crystalline and chemical disorder of the sample under examination. Three examples of distinct magnetic systems, with thicknesses ranging from 5 μ m to 6 mm, that were studied using this method are presented, these are: an amorphous CoFeB-based ribbon with ultra-soft coercivity for high-frequency applications, magnetically hard Nd-Fe-B thick films on Si substrates, examined in both as-deposited and annealed states, and a sample from the nickel-rich iron meteorite NWA 6259 that contains the atomically ordered, elevated coercivity, L 1 0 phase of FeNi, tetrataenite. The wide applicability and usefulness of this method is thus demonstrated on three distinct sample morphologies that required little to no surface preparation prior to examination.

Engineering↗

Tailored PEDOT:PSS hole transport layer for higher performance in perovskite solar cells: Enhancement of electrical and optical properties with improved morphology

Precise control over the charge carrier dynamics throughout the device can result in outstanding performance of perovskite solar cells (PSCs). Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is the most actively studied hole transport material in p-i-n structured PSCs. However, charge transport in the PEDOT:PSS is limited and inefficient because of its low conductivity with the presence of the weak ionic conductor PSS. In addition, morphology of the underlying PEDOT:PSS layer in PSCs plays a crucial role in determining the optoelectronic quality of the active perovskite absorber layer. This work is focused on realization of a non-wetting conductive surface of hole transport layer suitable for the growth of larger perovskite crystalline domains. This is accomplished by employing a facile solvent-engineered (ethylene glycol and methanol) approach resulting in removal of the predominant PSS in PEDOT:PSS. The consequence of acquiring larger perovskite crystalline domains was observed in the charge carrier dynamics studies, with the achievement of higher charge carrier lifetime, lower charge transport time and lower transfer impedance in the solvent-engineered PEDOT:PSS-based PSCs. Use of this solvent-engineered treatment for the fabrication of MAPbI3 PSCs greatly increased the device stability witnessing a power conversion efficiency of 18.18%, which corresponds to ~37% improvement compared to the untreated PEDOT:PSS based devices.

14 SOLAR ENERGY↗

Replacement of Calcium Carbonate Polymorphs by Cerussite

Calcium carbonate (CaCO 3 ) polymorphs, calcite, aragonite, and vaterite, serve as a major sink to retain various metal ions in natural and engineered systems. Here, we visualize the systematic trends in reactivities of calcite, vaterite, and aragonite to Pb 2+ dissolved in acidic aqueous solutions using in situ optical microscopy combined with ex situ scanning electron and transmission X-ray microscopies. All three polymorphs undergo pseudomorphic replacement by cerussite (PbCO 3 ) but with distinct differences in the evolution of their morphologies. The replacement of calcite and aragonite occurs through the formation of a pseudomorphic cerussite shell (typically 5–10 μm thick) followed by a slower inward propagation of reaction fronts through a thin solution gap (~0.1 μm wide) between the shell and the CaCO 3 substrate. The replacement of vaterite is characterized by the formation of a thinner cerussite shell (≤1 μm thick) and a larger cavity between the shell and the host mineral. These systematic differences in cerussite morphology for different CaCO 3 polymorphs are explained by the relative dissolution and precipitation rates of the reactant and product minerals, coupled with the role of ion transport through the cerussite shells. We also find that the replacement of calcite by cerussite is the slowest when all three polymorphs coexisted. Furthermore, our results provide mechanistic insights into the growth mode of cerussite on dissolving calcium carbonate and demonstrate these CaCO 3 polymorphs as promising substrate materials for removal and recycling of Pb from acidic polluted water and industrial effluents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystalline Peptoid Nanofibers with a Single-Unit Cell Cross Section

Ultranarrow crystalline one-dimensional nanostructures formed from soft materials facilitate precise structural control in nanomaterial design, which is essential for biomedicine and nanotechnology applications. Systematic control of their hierarchical structure is challenging due to the complexities of simultaneously manipulating multiple noncovalent interactions at such small scales. We employed a polypeptoid crystal motif as a supramolecular synthon to engineer ultranarrow crystalline nanofibers constrained to a single lattice axis by incorporating a single ionizable side chain into the hydrophobic core of a nanosheet-forming peptoid. Cryogenic transmission electron microscopy of the nanofibers revealed detailed molecular arrangements of a unit-cell cross-section and the presence of distinct pH-dependent lattice isoforms that resulted in morphological transformations. Molecular dynamics simulations demonstrated that the ionizable side chain plays a critical role in changing the local conformation of the unit cell, which further impacts the dimensionality of hierarchical structures. Moreover, these fibers were readily functionalized with biological ligands to afford one-dimensional (1D) protein arrays. This approach for the high-precision bottom-up assembly of ultranarrow 1D nanostructures offers significant potential for developing novel biomimetic nanostructures.

Lee, Yen Jea↗

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗

Tailoring Fibre Structure Enabled by X-ray Analytics for Targeted Biomedical Applications

The rising interest in designing fibres via spinning techniques combining the properties of various polymeric materials into advanced functionalised materials is directed towards targeted biomedical applications such as drug delivery, wearable sensors or tissue engineering. Understanding how these functional polymers exhibit multiscale structures ranging from the molecular level to nano-, micro-and millimetre scale is a key prerequisite for their challenging applications that can be addressed by a non-destructive X-ray based analytical approach. X-ray multimodalities combining X-ray imaging, scattering and diffraction allow the study of morphology, molecular structure, and the analysis of nano-domain size and shape, crystallinity and preferential orientation in 3D arrangements. The incorporation of X-ray analytics in the design process of polymeric fibers via their nanostructure under non-ambient conditions (i.e. temperature, mechanical load, humidity…) allows for efficient optimization of the fabrication process as well as quality control along the product lifetime under operating environmental conditions. Here, we demonstrate the successful collaboration between the laboratory of Biomimetic Textiles and Membranes and the Center of X-ray Analytics at Empa for the design, characterisation and optimisation of advanced functionalised polymeric fibrous material systems.

60 APPLIED LIFE SCIENCES↗

Exposure of Stainless Steel 316 to Subcritical, Transition, and Near-Supercritical Water

This work investigates the oxidation of austenitic stainless steel 316 at temperatures close to the critical point of water: subcritical water at 330°C and 27 MPa, the transition between subcritical and supercritical water at 374°C and 27 MPa, and supercritical water (SCW) at 380°C and 27 MPa. The surfaces of the samples were characterized using x-ray diffraction, Raman spectroscopy, scanning electron microscopy, and x-ray photoelectron spectroscopy before and after exposure. Magnetite (Fe3O4) was found to be present on all surfaces of all samples. The samples exposed to subcritical water also showed the presence of a nickel-iron chromium mixed spinel Ni(Fe2-xCrx)O4. The oxide morphology was observed to vary based on exposure temperature; an increased nucleation and growth rate, and an increased generation of Fe2+ was observed on samples exposed to the transition region and SCW.

Materials Science↗

Fundamentals of Scalable Nanoparticle Assembly in Engineering Polymres

Systematically improving the properties of polymer nanocomposites is contingent on effectively controlling nanoparticle (NP) dispersion; further, it is necessary to attain this at scale if these methods are to impact practical applications. While most past work has focused on amorphous polymers, ≈ 70% of all polymers sold annually are semicrystalline. Inspired by this apparent disconnect, our work in the current DOE funded grant and this renewal proposal employs a novel handle, polymer crystallization, to organize NPs into the various amorphous zones of the lamellar semicrystalline morphology (interlamellar, interfibrillar and interspherulitic domains) of stereoregular polymers. We hypothesize that the isothermal crystallization rate of a polymer host, G, and NP diffusivity, are the two relevant control parameters in this context. In the case where the NPs are miscible in the melt, they remain spatially well-dispersed when the polymer is crystallized at a rate that is fast relative to NP diffusion. In contrast, monolayer-thick NP sheets with intersheet spacing of ~10-100nm form in slowly crystallized samples. This sheet stacking is remarkably similar to that seen in natural materials, e.g., Nacre. There is also ordering of the NPs at the larger interfibrillar scale. Importantly, the relative fraction of engulfed, interlamellar and interfibrillar NPs is determined by G. Further, the modulus of these materials can increase by a factor of 2-3 due to the organization state of the NPs, while leaving fracture toughness unaffected. We have established the broad applicability of this approach in two polymers, polyethylene (PE) and polyethyleneoxide (PEO). To achieve this goal we developed a method for grafting long PE chains from NPs with controlled graft density and molecular weight, giving us the ability to tailor their dispersion in the PE melt prior to crystallization. In this renewal proposal, we will develop the fundamental, quantitative understanding that will allow us to independently tailor polymer crystallization rate, NP diffusivity and NP agglomeration state in semicrystalline polymers so as to facilely control NP ordering and hence properties. A program that tightly integrates experiment and theory is proposed, and a key outcome of this research will be a three-dimensional design map for different regimes of NP organization (and hence properties) that can be achieved by polymer crystallization. A second independent outcome is the role of directional solidification and how it competes with the rates of polymer crystallization and NP mobility to affect the organization of the NP.

36 MATERIALS SCIENCE↗

Tunable structural, morphological and optical properties of undoped, Mn, Ni and Ag-doped CuInS 2 thin films prepared by AACVD

The preparation of high-quality copper indium sulphide, CuInS 2 photo-absorber material with tunable properties for efficient, low-cost, thin film solar cells using scalable methods remains a challenge. In order to address this, high quality off-stoichiometric undoped and Mn, Ni and Ag-doped CuInS 2 (CIS) thin films have been deposited onto glass substrates by aerosol-assisted chemical vapour deposition (AACVD) using metal diethyldithiocarbamate precursors at temperatures of 350, 400 and 450 °C. Data from powder X-ray diffraction (p-XRD), Raman spectroscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS) suggest a correlation of morphology and composition of tetragonal phase (chalcopyrite and copper-gold-type) sulphur-deficient microcrystalline CIS thin films. For undoped thin films, near-infrared optical absorption and emission with tunable band gap between 1.32 and 1.42 eV are likely associated with donor-acceptor pairs involving deep or shallow electronic states such as sulphur vacancies (V S •• ), indium-copper anti-sites (In Cu •• ) and indium interstitials (In i ••• ) as donors and copper vacancies (V Cu ') as acceptors. Whilst Mn-doped thin films exhibit minimal tunable properties, Ni and Ag-doped films exhibit tunable morphology, composition and near-infrared absorption for small dopant content. Here, though further studies are required to explore the defect chemistry, these results show the utility of AACVD in tuning structural, morphological and optical properties of undoped, Mn, Ni and Ag-doped CIS thin films.

36 MATERIALS SCIENCE↗

Application of a Distributed Element Roughness Model to Additively Manufactured Internal Cooling Channels

Abstract Design for cooling effectiveness in turbine blades relies on accurate models for dynamic losses and heat transfer of internal cooling passages. Metal additive manufacturing (AM) has expanded the design space for these configurations, but can give rise to large-scale roughness features. The range of roughness length scales in these systems makes morphology resolved computational fluid dynamics (CFD) impractical. However, volumetric roughness models can be leveraged, as they have computational costs orders of magnitude lower. In this work, a discrete element roughness model (DERM), based on the double-averaged Navier–Stokes equations, is presented and applied to additively manufactured rough channels, representative of gas turbine blade cooling passages. Unique to this formulation of DERM is a generalized sheltering-based treatment of drag, a two-layer model for spatially averaged Reynolds stresses, and explicit treatment of dispersion. Six different AM rough surface channel configurations are studied, with roughness trough to peak sizes ranging from 15% to 60% nominal channel passage half-width, and the roughness Reynolds number ranges from Rek = 60 to 300. DERM predictions for spatially and temporally averaged mean flow quantities are compared to previously reported direct numerical simulation results. Good agreement in the mean velocity profiles, stress balances, and drag partitions are observed. While DERM models are typically calibrated to specific deterministic roughness morphologies at comparatively small roughness Reynolds numbers, the present more generalized DERM formulation has wider applicability. Here, it is demonstrated that the model can accommodate random roughness of large scale, typical of AM.

Engineering↗

Lattice-Oxygen-Driven Selective Oxidation Strategy for Stable Argyrodite Solid-State Lithium Metal Batteries

All-solid-state lithium metal batteries (ASSLMBs) with Li6PS5Cl argyrodite electrolytes and high-voltage LiNi0.8Mn0.1Co0.1O2 (NMC811) cathodes offer high energy density but suffer from rapid capacity fading due to the layered-to-rock-salt transition of NMC811 and structural degradation of Li6PS5Cl from parasitic interfacial reactions. Here, we demonstrate a catholyte engineering strategy using a Li2S scavenging additive to suppress interfacial reactivity and preserve the structural and electrochemical stability of both NMC811 and Li6PS5Cl. Incorporating 0.10 wt.% Li2S enables exceptional cycling stability, achieving 76% capacity retention after 550 cycles at C/10 and 88% retention after 800 cycles at C/3 at 60 degrees C, compared with rapid failure in pristine cells. Spectroscopic, electrochemical, and morphological analyses confirm that Li2S maintains electrode integrity by sustaining particle contact and suppressing phase decomposition. This work elucidates interfacial degradation pathways in NMC811/argyrodite systems and introduces a low-cost, scalable strategy to stabilize nickel-rich oxide cathodes in ASSLMBs, advancing their practical viability.

25 ENERGY STORAGE↗

Appendices for Geothermal Exploration Artificial Intelligence Report

The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especially regarding finding locations for viable EGS sites. This submission includes the appendices and reports formerly attached to the Geothermal Exploration Artificial Intelligence Quarterly and Final Reports. The appendices below include methodologies, results, and some data regarding what was used to train the Geothermal Exploration AI. The methodology reports explain how specific anomaly detection modes were selected for use with the Geo Exploration AI. This also includes how the detection mode is useful for finding geothermal sites. Some methodology reports also include small amounts of code. Results from these reports explain the accuracy of methods used for the selected sites (Brady Desert Peak and Salton Sea). Data from these detection modes can be found in some of the reports, such as the Mineral Markers Maps, but most of the raw data is included the DOE Database which includes Brady, Desert Peak, and Salton Sea Geothermal Sites.

15 GEOTHERMAL ENERGY↗

Long-Life, Ultrahigh-Nickel Cathodes with Excellent Air Storage Stability for High-Energy Density Lithium-Based Batteries

With increased energy density and cost advantage, ultrahigh-nickel layered oxides (LiNi x M 1-x O 2 , x = 0.9 - 1.0) are becoming front-runner as cathodes for next-generation lithium-based batteries, yet their commercialization is blocked both by severe capacity fade and exponentially aggravated air degradation. Thus, it is imperative to find effective solutions to address these issues simultaneously. Here, a significant enhancement in both the cycling and air storage stability of the ultrahigh-Ni cathode LiNi 0.94 Co 0.06 O 2 is achieved via a distinctive phosphoric acid treatment strategy. The modified cathode displays remarkably improved capacity retention (from 36 % to 80 % after 1,000 cycles) and rate capability (from 0 to 105 mA h g -1 at 30C rate) in pouch cells. Impressively, the modified cathode, after air storage for 450 days, maintains the morphology and 92% of the initial capacity of the fresh sample with excellent cyclability. Comprehensive interphase and structural analyses reveal that the enhanced electrochemical performance is due to a highly stabilized electrode/electrolyte interphase that suppresses electrode corrosion and lattice reconstruction. The excellent air stability results from an adsorption-buffering effect enabled by phosphoric acid to air attack. Finally, the study demonstrates an engineering pathway to improve the cycling and air stability, facilitating the practical viability of high-capacity, affordable, ultrahigh-Ni cathodes in lithium-based batteries.

25 ENERGY STORAGE↗

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗

Improved Performance of Cu(InGa)(SeS) 2 PV Modules Using the Reaction of Metal Precursors. Final Report

This project “Improved Performance of Cu(InGa)(SeS) 2 PV Modules using the Reaction of Metal Precursors” was a partnership led by the Institute of Energy Conversion (IEC) at the University of Delaware with Columbia University and the Molecular Foundry at the Lawrence Berkeley National Laboratory. The aim was to develop pathways to improve Cu(InGa)(SeS) 2 (CIGSS) thin film photovoltaic modules using processes compatible with low manufacturing cost. The CIGSS approach investigated was a two-step process including deposition of metal precursor films following by reaction in hydride gases utilizing IEC’s novel reactor. The process was similar to that under commercial development by the project’s industry partner Stion. When Stion went out of business mid-project the focus changed to a rapid thermal process considered more commercially viable. Approaches to improve the performance of solar cells using the reacted films focused on two material innovations. First, the overall Ga content was increased to increase the operating voltage, which is desirable for scale-up to commercial modules. Second, the processing and performance advantages arising from Ag alloying were investigated. Advanced characterization guided process and material development including control of relative composition gradients. Research on the formation of Cu-Ga-In metal precursors utilized sputtering deposition which is normally used in commercial applications. The work resulted in processes for deposition of precursor stacks with increased relative Ga content and effects of deposition parameters on morphology and phase composition were established. It was shown that the metal precursor films have comparable phase composition and morphology so subsequent reaction follows from the same starting point. The addition of Ag to the metal precursors gave more uniform morphology and improved adhesion of reacted films which enable higher reaction temperature for faster processing. A novel outcome was the discovery of a previously undocumented material phase in sputter-deposited and evaporated Ag-Cu-In-Ga thin films. Hydride gas reaction processes including time-temperature-concentration profiles were developed for different precursor compositions. This enables control of composition profiles to engineer through-film gradients for solar cell optimization with characterization and simulations used to correlate measured film composition profiles to measurements of devices. In particular, the gradient of sulfur at the front of the CIGSS film was found to be critical. The simulations guided process development leading to improved reproducibility of devices improved performance with higher Ga content and higher voltage. With Ag-alloyed precursors, the reaction pathways leading were determined. A significant finding was that Ag-alloying increases the reaction rate to completely convert precursor films to the final chalcopyrite which could enable reduced reaction time to benefit manufacturability. To maintain potential commercial viability, the process under investigation was refocused to a rapid thermal process that could potentially be incorporated into an in-line process for manufacturing. Precursors with different composition were capped with an extra selenium layer and reacted in hydrogen sulfide 5-15 minutes, compared to typically 2 hours in the previous multi-step batch process. Critical RTP parameters were identified to control the reaction. Further optimization would be needed for high efficiency solar cells but pathways to high quality devices with further optimization and improved heating uniformity were developed. The project also developed new optoelectronic characterization approaches with a focus on development and application of spatial- and time-resolved photoluminescence and a custom mapping photoluminescence microscope built. It was shown how critical electronic transport properties strongly depend on the chemical composition of the material and that a wide range of samples show inhomogeneity on a length scale larger than the grains in the films. Additionally, two-photon excitation capability was developed to distinguish bulk vs surface losses. The project advances the state-of-the -art for precursor reaction processes in several ways that could impact manufacturing. This includes validation of approaches to increase voltage and establishment of model-guided control to form optimal composition profiles. The application of process control approaches with knowledge of phase formation and reaction pathways can be critically valuable in designing a large-scale process.

14 SOLAR ENERGY↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗