Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery.

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better understanding of electro/photocatalytic processes are essential for improving catalyst effectiveness. Recent advances in data science and artificial intelligence have great potential to accelerate electrocatalysis and photocatalysis research, particularly the rapid exploration of large materials chemistry spaces through machine learning. Here a comprehensive introduction to, and critical review of, machine learning techniques used in electrocatalysis and photocatalysis research are provided. Sources of electro/photocatalyst data and current approaches to representing these materials by mathematical features are described, the most commonly used machine learning methods summarized, and the quality and utility of electro/photocatalyst models evaluated. Illustrations of how machine learning models are applied to novel electro/photocatalyst discovery and used to elucidate electrocatalytic or photocatalytic reaction mechanisms are provided. The review offers a guide for materials scientists on the selection of machine learning methods for electrocatalysis and photocatalysis research. The application of machine learning to catalysis science represents a paradigm shift in the way advanced, next-generation catalysts will be designed and synthesized.

Synthesis of Layered Lead-Free Perovskite Nanocrystals with Precise Size and Shape Control and Their Photocatalytic Activity.

Halide perovskites have attracted enormous attention due to their potential applications in optoelectronics and photocatalysis. However, concerns over their instability, toxicity, and unsatisfactory efficiency have necessitated the development of lead-free all-inorganic halide perovskites. A major challenge in designing efficient halide perovskites for practical applications is the lack of effective methods for producing nanocrystals with precise size and shape control. In this work, a layered perovskite, Cs4ZnSb2Cl12 (CZS), is found from calculations to exhibit size- and facet-dependent optoelectronic properties in the nanoscale, and thus, a colloidal method is used to synthesize the CZS nanoparticles with size-tunable morphologies: zero- (nanodots), one- (nanowires and nanorods), two- (nanoplates), and three-dimensional (nanopolyhedra). The growth kinetics of the CZS nanostructures, along with the effects of surface ligands, reaction temperature, and time were investigated. The optoelectronic properties of the nanocrystals varied with size due to quantum confinement effects and with shape due to anisotropy within the crystals and the exposure of specific facets. These properties could be modulated to enhance the visible-light photocatalytic performance for toluene oxidation. In particular, the 9.7 nm CZS nanoplates displayed a toluene to benzaldehyde conversion rate of 1893 µmol g-1 h-1 (95% selectivity), 500 times higher than the bulk synthesized CZS, and comparable with the reported photocatalysts. This study demonstrates the integration of theoretical calculations and synthesis, revealing an approach to the design and fabrication of novel, high-performance colloidal perovskite nanocrystals for optoelectronic and photocatalytic applications.

Rational Atom Substitution to Obtain Efficient, Lead-Free Photocatalytic Perovskites Assisted by Machine Learning and DFT Calculations.

Inorganic lead-free halide perovskites, devoid of toxic or rare elements, have garnered considerable attention as photocatalysts for pollution control, CO2 reduction and hydrogen production. In the extensive perovskite design space, factors like substitution or doping level profoundly impact their performance. To address this complexity, a synergistic combination of machine learning models and theoretical calculations were used to efficiently screen substitution elements that enhanced the photoactivity of substituted Cs2 AgBiBr6 perovskites. Machine learning models determined the importance of d10 orbitals, highlighting how substituent electron configuration affects electronic structure of Cs2 AgBiBr6 . Conspicuously, d10 -configured Zn2+ boosted the photoactivity of Cs2 AgBiBr6 . Experimental verification validated these model results, revealing a 13-fold increase in photocatalytic toluene conversion compared to the unsubstituted counterpart. This enhancement resulted from the small charge carrier effective mass, as well as the creation of shallow trap states, shifting the conduction band minimum, introducing electron-deficient Br, and altering the distance between the B-site cations d band centre and the halide anions p band centre, a parameter tuneable through d10 configuration substituents. This study exemplifies the application of computational modelling in photocatalyst design and elucidating structure-property relationships. It underscores the potential of synergistic integration of calculations, modelling, and experimental analysis across various applications.

Developing sustainable, high-performance perovskites in photocatalysis: design strategies and applications.

Solar energy is attractive because it is free, renewable, abundant and sustainable. Photocatalysis is one of the feasible routes to utilize solar energy for the degradation of pollutants and the production of fuel. Perovskites and their derivatives have received substantial attention in both photocatalytic wastewater treatment and energy production because of their highly tailorable structural and physicochemical properties. This review illustrates the basic principles of photocatalytic reactions and the application of these principles to the design of robust and sustainable perovskite photocatalysts. It details the structures of the perovskites and the physics and chemistry behind photocatalytic reactions and describes the advantages and limitations of popular strategies for the design of photoactive perovskites. This is followed by examples of how these strategies are applied to enhance the photocatalytic efficiency of oxide, halide and oxyhalide perovskites, with a focus on materials with potential for practical application, that is, not containing scarce or toxic elements. It is expected that this overview of the development of photocatalysts and deeper understanding of photocatalytic principles will accelerate the exploitation of efficient perovskite photocatalysts and bring about effective solutions to the energy and environmental crisis.

Trace-Level Fluorination of Mesoporous TiO2 Improves Photocatalytic and Pb(II) Adsorbent Performances.

Fluorination is an effective way of tuning the physicochemical property and activity of TiO2 nanocrystallites, which usually requires a considerable amount of hydrofluoric acid (or NH4F) for a typical F/Ti molar ratio, RF, of 0.5-69.0 during synthesis. This has consequential environmental issues due to the high toxicity and hazard of the reactants. In the present work, an environmentally benign fluorination approach is demonstrated that uses only a trace amount of sodium fluoride with an RF of 10-6 during synthesis. While it maintained the desirable high surface area (102.4 m2/g), the trace-level fluorination enabled significant enhancements on photocatalytic activities (e.g., a 56% increase on hydrogen evolution rate) and heavy metal Pb(II) removal (31%) of the mesoporous TiO2. This can be attributed to enriched Ti3+ and localized spatial charge separation due to fluorination as proved by X-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance spectroscopy (EPR), and density functional theory (DFT) analyses.

Cell Adhesion, Elasticity, and Rupture Forces Guide Microbial Cell Death on Nanostructured Antimicrobial Titanium Surfaces.

Naturally occurring and synthetic nanostructured surfaces have been widely reported to resist microbial colonization. The majority of these studies have shown that both bacterial and fungal cells are killed upon contact and subsequent surface adhesion to such surfaces. This occurs because the presence of high-aspect-ratio structures can initiate a self-driven mechanical rupture of microbial cells during the surface adsorption process. While this technology has received a large amount of scientific and medical interest, one important question still remains: what factors drive microbial death on the surface? In this work, the interplay between microbial-surface adhesion, cell elasticity, cell membrane rupture forces, and cell lysis at the microbial-nanostructure biointerface during adsorptive processes was assessed using a combination of live confocal laser scanning microscopy, scanning electron microscopy, in situ amplitude atomic force microscopy, and single-cell force spectroscopy. Specifically, the adsorptive behavior and nanomechanical properties of live Gram-negative (Pseudomonas aeruginosa) and Gram-positive (methicillin-resistant Staphylococcus aureus) bacterial cells, as well as the fungal species Candida albicans and Cryptococcus neoformans, were assessed on unmodified and nanostructured titanium surfaces. Unmodified titanium and titanium surfaces with nanostructures were used as model substrates for investigation. For all microbial species, cell elasticity, rupture force, maximum cell-surface adhesion force, the work of adhesion, and the cell-surface tether behavior were compared to the relative cell death observed for each surface examined. For cells with a lower elastic modulus, lower force to rupture through the cell, and higher work of adhesion, the surfaces had a higher antimicrobial activity, supporting the proposed biocidal mode of action for nanostructured surfaces. This study provides direct quantification of the differences observed in the efficacy of nanostructured antimicrobial surface as a function of microbial species indicating that a universal, antimicrobial surface architecture may be hard to achieve.

Surface-metastable phase-initiated seeding and ostwald ripening: a facile fluorine-free process towards spherical fluffy core/shell, yolk/shell, and hollow anatase nanostructures.

Versatile synthetic method: Monodisperse anatase microspheres with various complex morphologies have been synthesized by using a versatile fluorine-free solvothermal process in the presence of ammonia. Unambiguous evidence related to surface seeding and a subsequent hollowing process revealed an Ostwald ripening evolution process.

Spiky mesoporous anatase titania beads: a metastable ammonium titanate-mediated synthesis.

A complex titania nanostructure of monodisperse spiky mesoporous anatase beads composed of anatase nanocrystals with diameters of less than 15 nm in the core and much larger hollow-cone shaped spikes on the surface was fabricated using a facile solvothermal process in the presence of ammonia. This proceeded through a controllable phase transformation from an amorphous titania to a metastable amorphous titania/ammonium titanate core-shell structure then finally to anatase titania. The size of the spiky anatase nanostructures can be increased from approximately 55 × 100 nm to 160 × 410 nm (square edge × length) by increasing the ammonia concentration used in the solvothermal treatment step from 2.2 to 17.4 wt. %. Such hollow-cone shaped nanostructures, as revealed by HRTEM characterization, are single crystals elongated along the c axis of the tetragonal anatase titania. The resultant spiky titania beads have high surface areas of up to 112 m(2) g(-1) and pore diameters and pore volumes that vary depending on the ammonia concentration and solvothermal treatment time. The morphological evolution and crystallization process of the spiky titania beads was investigated using SEM and XRD techniques. A metastable amorphous titania/ammonium titanate core-shell structure evolved from the smooth amorphous precursor beads producing a "fluffy" titanate intermediate, on further heating the final spiky mesoporous titania beads were clearly observed. This titanate-phase-mediated approach allows control over the size of the nanocrystals in the core of the bead, as well as the anatase spikes on the surface, and thereby, tuning of the surface area and porosity of the resultant products. The spiky mesoporous titania beads have been used to prepare working electrodes for dye-sensitized solar cells achieving a solar to electric power conversion efficiency of 10.30 %, indicating their potential for application in the photovoltaic field. Such complex titania nanostructures would have a number of other possible applications, such as photocatalysis, lithium ion batteries, and catalysis.

Uranyl-sorption properties of amorphous and crystalline TiO2/ZrO2 millimeter-sized hierarchically porous beads.

Hierarchically porous TiO(2)/ZrO(2) millimeter-sized beads were synthesized using a sol-gel templating technique, and investigated for suitability as radionuclide sorbents using uranyl as a radionuclide-representative probe. The bead properties were varied by altering either composition (22, 36, and 82 wt % Zr in the Ti/Zr composite) or calcination temperature (500 or 700 °C). Uranyl adsorption was higher for the crystalline beads (surface area: 52-59 m(2) g(-1)) than the amorphous beads (surface area: 95-247 m(2) g(-1)), reaching a maximum of 0.170 mmol g(-1) for the 22 wt % Zr sample. This was attributed to the higher surface hydroxyl density (OH nm(-2)), presence of limited microporosity, and larger mesopores in the crystalline beads. Mass transport properties of the crystalline beads were not compromised by the large bead diameter: sorption rates comparable to those reported for powders were achieved and rates were higher than exclusively mesoporous reported systems, thereby highlighting the importance of pore hierarchy in designing materials with improved kinetics. Chemical stability of the sorbent, an important property for processes involving corrosive effluents (e.g., radioactive waste), was also assessed. Crystalline beads displayed superior resistance against matrix leaching in HNO(3). Stability varied with composition: the 22 wt % Zr sample demonstrated the highest stability.

Lyotropic liquid crystalline phase behaviour in amphiphile-protic ionic liquid systems.

Approximate partial phase diagrams for nine amphiphile-protic ionic liquid (PIL) systems have been determined by synchrotron source small angle X-ray scattering, differential scanning calorimetry and cross polarised optical microscopy. The binary phase diagrams of some common cationic (hexadecyltrimethyl ammonium chloride, CTAC, and hexadecylpyridinium bromide, HDPB) and nonionic (polyoxyethylene (10) oleyl ether, Brij 97, and Pluronic block copolymer, P123) amphiphiles with the PILs, ethylammonium nitrate (EAN), ethanolammonium nitrate (EOAN) and diethanolammonium formate (DEOAF), have been studied. The phase diagrams were constructed for concentrations from 10 wt% to 80 wt% amphiphile, in the temperature range 25 °C to >100 °C. Lyotropic liquid crystalline phases (hexagonal, cubic and lamellar) were formed at high surfactant concentrations (typically >50 wt%), whereas at <40 wt%, only micelles or polydisperse crystals were present. With the exception of Brij 97, the thermal stability of the phases formed by these surfactants persisted to temperatures above 100 °C. The phase behaviour of amphiphile-PIL systems was interpreted by considering the PIL cohesive energy, liquid nanoscale order, polarity and ionicity. For comparison the phase behaviour of the four amphiphiles was also studied in water.

Durable CuxO/mesoporous TiO2 photocatalyst for stable and efficient hydrogen evolution.

Heterogeneous structures containing highly dispersed semiconductor nanoparticles on a photoactive support are effective for the photocatalytic hydrogen evolution reaction (HER). In this work, the interlayer ion-exchange and space confining nature of layered titanate nanosheets was used to embed copper ions in titanates, which were then transitioned to mesoporous CuxO/TiO2 with highly dispersed CuxO nanostructures. Both experimental and density functional theory (DFT) studies demonstrated that the fine-decoration of CuxO nanostructures and the reducible valence of the copper species enabled stable superior photocatalytic activity. The HER efficiency was enhanced to 12.45 mmol g-1 h-1 for the mesoporous CuxO/TiO2 composites in comparison to an efficiency of 0.38 mmol g-1 h-1 for the non-modified TiO2. Steady HER performances over 10 h, cyclic HER measurement over 60 h, and testing of the composite kept under ambient conditions for over one year, demonstrated excellent stability of the composite against photochemical and wet-chemical erosion.

Fabrication of a Reusable Carbon Dot/Gold Nanoparticle/Metal-Organic Framework Film for Fluorescence Detection of Lead Ions in Water.

Solid-state sensing platforms are desirable for the development of reusable sensors to promote public health measures such as testing for drinking water contamination. A bioinspired metal-organic framework (MOF)-based material has been developed by imitating metal-protein interactions in biological systems to attain high sensitivity and selectivity to Pb2+ through fluorescence sensing. A zirconium terephthalate-type framework (also known as NH2-UiO-66) was modified with both gold nanoparticles and thiol-functionalized carbon dots to give HS-C/Au(x)/UiO-66 composites with different Au content (x) and were subsequently adapted into films that show extraordinary sensitivity to Pb2+. The HS-C/Au(1.4)/UiO-66 film that consists of 1.4 wt % Au shows a quenching response with the limit of detection of 80 parts per trillion and sustained performance for five cycles. Moreover, the fluorescence response of the HS-C/Au(x)/UiO-66 film to Pb2+ can be reversed from emission quenching to enrichment of fluorescence by increasing the Au content. The performance of the HS-C/Au(x)/UiO-66 film as a solid-state sensor demonstrates its potential for application in reusable sensing devices to ensure public safety from Pb2+ contamination in drinking water.

Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture.

Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress in machine learning has stimulated technological breakthroughs in the discovery, design, and deployment of materials with potential for high-performance and low-cost clean energy applications. This review summarizes basic machine learning methods-data collection, featurization, model generation, and model evaluation-and reviews their use in the development of robust adsorbent materials. Key case studies are provided where these methods are used to accelerate adsorbent materials design and discovery, optimize synthesis conditions, and understand complex feature-property relationships. The review provides a concise resource for researchers wishing to use machine learning methods to rapidly develop effective adsorbent materials with a positive impact on the environment.

Dual-action silver functionalized nanostructured titanium against drug resistant bacterial and fungal species.

HYPOTHESIS: Titanium and its alloys are commonly used implant materials. Once inserted into the body, the interface of the biomaterials is the most likely site for the development of implant-associated infections. Imparting the titanium substrate with high-aspect-ratio nanostructures, which can be uniformly achieved using hydrothermal etching, enables a mechanical contact-killing (mechanoresponsive) mechanism of bacterial and fungal cells. Interaction between cells and the surface shows cellular inactivation via a physical mechanism meaning that careful engineering of the interface is needed to optimse the technology. This mechanism of action is only effective towards surface adsorbed microbes, thus any cells not directly in contact with the substrate will survive and limit the antimicrobial efficacy of the titanium nanostructures. Therefore, we propose that a dual-action mechanoresponsive and chemical-surface approach must be utilised to improve antimicrobial activity. The addition of antimicrobial silver nanoparticles will provide a secondary, chemical mechanism to escalate the microbial response in tandem with the physical puncture of the cells. EXPERIMENTS: Hydrothermal etching is used as a facile method to impart variant nanostrucutres on the titanium substrate to increase the antimicrobial response. Increasing concentrations (0.25 M, 0.50 M, 1.0 M, 2.0 M) of sodium hydroxide etching solution were used to provide differing degrees of nanostructured morphology on the surface after 3 h of heating at 150 °C. This produced titanium nanospikes, nanoblades, and nanowires, respectively, as a function of etchant concentration. These substrates then provided an interface for the deposition of silver nanoparticles via a reduction pathway. Methicillin-resistant Staphylococcous aureus (MRSA) and Candida auris (C. auris) were used as model bacteria and fungi, respectively, to test the effectiveness of the nanostructured titanium with and without silver nanoparticles, and the bio-interactions at the interface. FINDINGS: The presence of nanostructure increased the bactericidal response of titanium against MRSA from âˆ¼ 10 % on commercially pure titanium to a maximum of âˆ¼ 60 % and increased the fungicidal response from âˆ¼ 10 % to âˆ¼ 70 % in C. auris. Introducing silver nanoparticles increased the microbiocidal response to âˆ¼ 99 % towards both bacteria and fungi. Importantly, this study highlights that nanostructure alone is not sufficient to develop a highly antimicrobial titanium substrate. A dual-action, physical and chemical antimicrobial approach is better suited to produce highly effective antibacterial and antifungal surface technologies.

Strong silica monoliths with large mesopores prepared using agarose gel templates.

Mesoporous silica pellets with controllable shape and pore size were prepared using agarose gel templates. Robust (compressive strength of 3.3-25.1 MPa), crack-free silica monoliths have been produced with large mesopores (14-23 nm), high surface areas (410-540 m(2) g(-1)), and large pore volumes (1.1-1.2 cm(3) g(-1)). The synthesis was achieved by infusing preformed agarose gels with tetraethyl orthosilicate and the nonpolar condensation catalyst tetrabutyl ammonium fluoride. The infiltrated gels were transferred to water to initiate hydrolysis and condensation of the silica precursor. Fluoride catalyzed the gelation of silica in a matter of minutes; hence, the oxide maintained the shape of the agarose pellet. The mesopore size could be modified by altering the weight percent of agarose gel used. The method employed here is simple and reproducible. As these materials have such large mesopore dimensions, they could be used as hard templates or could be specifically functionalized for use in environmental remediation, as environmentally responsive materials, biocatalysts, or catalysts.

Monitoring bisphosphonate surface functionalization and acid stability of hierarchically porous titanium zirconium oxides.

To take advantage of the full potential of functionalized transition metal oxides, a well-understood nonsilane based grafting technique is required. The functionalization of mixed titanium zirconium oxides was studied in detail using a bisphosphonic acid, featuring two phosphonic acid groups with high surface affinity. The bisphosphonic acid employed was coupled to a UV active benzamide moiety in order to track the progress of the surface functionalization in situ. Using different material compositions, altering the pH environment, and looking at various annealing conditions, key features of the functionalization process were identified that consequently will allow for intelligent material design. Loading with bisphosphonic acid was highest on supports calcined at 650 °C compared to lower calcination temperatures: A maximum capacity of 0.13 mmol g(-1) was obtained and the adsorption process could be modeled with a pseudo-second-order rate relationship. Heating at 650 °C resulted in a phase transition of the mixed binary oxide to a ternary oxide, titanium zirconium oxide in the srilankite phase. This phase transition was crucial in order to achieve high loading of the bisphosphonic acid and enhanced chemical stability in highly acidic solutions. Due to the inert nature of phosphorus-oxygen-metal bonds, materials functionalized by bisphosphonic acids showed increased chemical stability compared to their nonfunctionalized counterparts in harshly acidic solutions. Leaching studies showed that the acid stability of the functionalized material was improved with a partially crystalline srilankite phase. The materials were characterized using nitrogen sorption, X-ray powder diffraction, and UV-vis spectroscopy; X-ray photoelectron spectroscopy was used to study surface coverage with the bisphosphonic acid molecules.

Hierarchically Porous WO3/CdWO4 Fiber-in-Tube Nanostructures Featuring Readily Accessible Active Sites and Enhanced Photocatalytic Effectiveness for Antibiotic Degradation in Water.

The intentional design and construction of photocatalysts containing heterojunctions with readily accessible active sites will improve their ability to degrade pollutants. Herein, hierarchically porous WO3/CdWO4 fiber-in-tube nanostructures with three accessible surfaces (surface of core fiber and inner and outer surfaces of the porous tube shell) were fabricated by an electrospinning method. This WO3/CdWO4 heterostructure, assembled by interconnected nanoparticles, displays good photocatalytic degradation of ciprofloxacin (CIP, 93.4%) and tetracycline (TC, 81.6%) after 90 min of simulated sunlight irradiation, much higher than the pristine WO3 (<75.3% for CIP and <53.6% for TC) or CdWO4 materials (<58.9% for CIP and <39.5% for TC). The WO3/CdWO4 fiber-in-tube promotes the separation of photoinduced electrons and holes and also provides readily accessible reaction sites for photocatalytic degradation. The dominant active species determined by trapping active species and electron paramagnetic resonance were hydroxyl radicals followed by photogenerated holes and superoxide anions. The WO3/CdWO4 materials formed a Z-scheme heterojunction that generated superoxide anion and hydroxyl radicals, leading to degradation of antibiotics (CIP and TC) via photocatalysis in aqueous solution.

Metal-organic frameworks for chemical sensing devices.

Metal-organic frameworks (MOFs) are exceptionally large surface area materials with organized porous cages that have been investigated for nearly three decades. Due to the flexibility in their design and predisposition toward functionalization, they have shown promise in many areas of application, including chemical sensing. Consequently, they are identified as advanced materials with potential for deployment in analytical devices for chemical and biochemical sensing applications, where high sensitivity is desirable, for example, in environmental monitoring and to advance personal diagnostics. To keep abreast of new research, which signposts the future directions in the development of MOF-based chemical sensors, this review examines studies since 2015 that focus on the applications of MOF films and devices in chemical sensing. Various examples that use MOF films in solid-state sensing applications were drawn from recent studies based on electronic, electrochemical, electromechanical and optical sensing methods. These examples underscore the readiness of MOFs to be integrated in optical and electronic analytical devices. Also, preliminary demonstrations of future sensors are indicated in the performances of MOF-based wearables and smartphone sensors. This review will inspire collaborative efforts between scientists and engineers working within the field of MOFs, leading to greater innovations and accelerating the development of MOF-based analytical devices for chemical and biochemical sensing applications.

Use of metamodels for rapid discovery of narrow bandgap oxide photocatalysts.

New photocatalysts are traditionally identified through trial-and-error methods. Machine learning has shown considerable promise for improving the efficiency of photocatalyst discovery from a large potential pool. Here, we describe a multi-step, target-driven consensus method using a stacking meta-learning algorithm that robustly predicts bandgaps and H2 evolution activities of photocatalysts. Trained on small datasets, these models can rapidly screen a large space (>10 million materials) to identify promising, non-toxic compounds as candidate water splitting photocatalysts. Two effective compounds and two controls possessing optimal bandgap values (∼2 eV) but not photoactivity as predicted by the models were synthesized. Their experimentally measured bandgaps and H2 evolution activities were consistent with the predictions. Conspicuously, the two compounds with strong photoactivities under UV and visible light are promising visible-light-driven water splitting photocatalysts. This study demonstrates the power of machine learning and the potential of big data to accelerate discovery of next-generation photocatalysts.

Synthesis of monodisperse mesoporous titania beads with controllable diameter, high surface areas, and variable pore diameters (14-23 nm).

Monodisperse mesoporous anatase titania beads with high surface areas and tunable pore size and grain diameter have been prepared through a combined sol-gel and solvothermal process in the presence of hexadecylamine (HDA) as a structure-directing agent. The monodispersity of the resultant titania beads, along with the spherical shape, can be controlled by varying the amount of structure-directing agent involved in the sol-gel process. The diameter of the titania beads is tunable from approximately 320 to 1150 nm by altering the hydrolysis and condensation rates of the titanium alkoxide. The crystallite size, specific surface area (from 89 to 120 m(2)/g), and pore size distribution (from 14 to 23 nm) of the resultant materials can be varied through a mild solvothermal treatment in the presence of varied amounts of ammonia. On the basis of the results of small-angle XRD, high-resolution SEM/TEM, and gas sorption characterization, a mechanism for the formation of the monodisperse precursor beads has been proposed to illustrate the role of HDA in determining the morphology and monodispersity during the sol-gel synthesis. The approach presented in this study demonstrates that simultaneous control of the physical properties, including specific surface area, mesoporosity, crystallinity, morphology, and monodispersity, of the titania materials can be achieved by a facile sol-gel synthesis and solvothermal process.