4.6 Article

Synthesis and Micropatterning of Photocatalytically Reactive Self-Assembled Monolayers Covalently Linked to Si(100) Surfaces via a Si-C Bond

Journal

LANGMUIR
Volume 28, Issue 46, Pages 16156-16166

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/la302880v

Keywords

-

Funding

  1. Focus Center Research Program (FCRP) through the Functional Engineered Nano Architectonics (FENA) Center at UCLA
  2. Direct For Mathematical & Physical Scien [0844455] Funding Source: National Science Foundation
  3. Division Of Chemistry [0844455] Funding Source: National Science Foundation

Ask authors/readers for more resources

Selective generation of an amine-terminated selfassembled monolayer bound to silicon wafers via a silicon carbon linkage was realized by photocatalytically reducing the corresponding azide-terminated, self-assembled monolayers (Az-SAMs). The Az-SAM was obtained by thermal deposition of 11-chloroundecene onto a hydrogen-terminated silicon wafer followed by nucleophilic substitution of the chloride with the azide ion in warm N,N'-dimethylformamide (DMF). The presence of the terminal azide group on the SAM was confirmed by reflection absorption infrared spectroscopy (RAIRS), by X-ray photoelectron spectroscopy (XPS), and by detecting the formation of a triazole upon reaction of the azide with an activated alkyne. The desired terminal amine groups were generated by photocatalytic reduction of the Az-SAM with cadmium selenide quantum dots (CdSe Qdots) using lambda > 400 nm. Analysis of the reduced SAM by XPS gave results that were consistent with those obtained with an amine-terminated surface obtained by reducing the Az-SAM with triphenylphosphine. To demonstrate the feasibility of using the Az-SAM for surface patterning, a sample was coated with adsorbed CdSe Qdots and exposed to the output of a diode laser at lambda = 407 nm through a micropatterned mask. Using a SEM, the pattern formed in this manner was revealed after removing the CdSe Qdots and subsequently adsorbing 10 nm gold nanoparticles (AuNPs) to the positively charged terminal-amine groups. The formation of the pattern by CdSe-photocatalyzed reduction of the azide demonstrates a novel route to create features by selective modification of organic monolayers on silicon wafers.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Chemistry, Physical

Explaining the structure sensitivity of Pt and Rh for aqueous-phase hydrogenation of phenol

Isaiah Barth, James Akinola, Jonathan Lee, Oliver Y. Gutierrez, Udishnu Sanyal, Nirala Singh, Bryan R. Goldsmith

Summary: Phenol is an important model compound for understanding the hydrogenation of biomass to biofuels, and the active facets of Pt and Rh catalysts for this reaction have been identified. The study reveals that the activity trends of Pt and Rh nanoparticles in the hydrogenation of phenol are size-dependent, with higher turnover frequencies observed on certain terraces. The increase in experimental turnover frequencies with larger Pt and Rh nanoparticle diameters is attributed to a larger fraction of terraces on the larger particles.

JOURNAL OF CHEMICAL PHYSICS (2022)

Article Biotechnology & Applied Microbiology

Accelerating the structure search of catalysts with machine learning

Eric Musa, Francis Doherty, Bryan R. Goldsmith

Summary: Identifying the structure of heterogeneous catalysts is crucial for understanding catalytic reactions and structure-property relationships. Machine learning is now being used to accelerate the search of catalyst structures, enabling modeling of larger and more complex catalyst structures and aiding catalyst design.

CURRENT OPINION IN CHEMICAL ENGINEERING (2022)

Article Chemistry, Physical

Interpretable machine learning for knowledge generation in heterogeneous catalysis

Jacques A. Esterhuizen, Bryan R. Goldsmith, Suljo Linic

Summary: Most applications of machine learning in heterogeneous catalysis use black-box models, which are not easily interpretable. Interpretable machine learning methods offer an alternative by merging the predictive capacity of black-box models with the interpretability of physics-based models. This Perspective discusses the potential, challenges, and opportunities of interpretable machine learning in catalysis research.

NATURE CATALYSIS (2022)

Editorial Material Materials Science, Multidisciplinary

Recent advances in computational materials design: methods, applications, algorithms, and informatics

Ghanshyam Pilania, Bryan R. Goldsmith, Mina Yoon, Avinash M. Dongare

JOURNAL OF MATERIALS SCIENCE (2022)

Article Chemistry, Physical

Metal Oxynitrides for the Electrocatalytic Reduction of Nitrogen to Ammonia

Samuel D. Young, Bianca M. Ceballos, Amitava Banerjee, Rangachary Mukundan, Ghanshyam Pilania, Bryan R. Goldsmith

Summary: This article discusses the potential of metal oxynitrides as a new material category for e-NRR and compares them with metal nitrides and metal oxides. The article focuses on the challenges faced by metal oxynitrides in e-NRR and provides an outlook for future research.

JOURNAL OF PHYSICAL CHEMISTRY C (2022)

Article Chemistry, Physical

Explaining Kinetic Trends of Inner-Sphere Transition-Metal-Ion Redox Reactions on Metal Electrodes

Harsh Agarwal, Jacob Florian, Daniel Pert, Bryan R. Goldsmith, Nirala Singh

Summary: Transition-metal ions regularly undergo charge transfer reactions by directly interacting with electrodes. The average energy of the d electrons of a transition-metal electrode (d-band center) can rationalize the kinetic trends of inner-sphere charge transfer reactions. This descriptor aids in the design of electrochemical systems with improved kinetics.

ACS CATALYSIS (2023)

Article Physics, Fluids & Plasmas

Modeling plasma-induced surface charge effects on CO2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Francis Doherty, Bryan R. Goldsmith

Summary: Through density functional theory (DFT) modeling, we investigate the effect of plasma-induced surface charging on CO2 activation by atomically dispersed single atom (SA) catalysts on reducible and irreducible metal oxide supports. We find that the accumulated surface charge on the SA increases the CO2 adsorption strength and decreases the CO2 dissociation barrier. This study demonstrates the importance of considering surface charging in strong electric fields for molecule adsorption and bond-breaking on catalytic surfaces.

PLASMA SOURCES SCIENCE & TECHNOLOGY (2023)

Article Multidisciplinary Sciences

Understanding capacity fade in organic redox-flow batteries by combining spectroscopy with statistical inference techniques

Sanat Vibhas Modak, Wanggang Shen, Siddhant Singh, Dylan Herrera, Fairooz Oudeif, Bryan R. R. Goldsmith, Xun Huan, David G. G. Kwabi

Summary: Organic redox-active molecules are attractive as redox-flow battery (RFB) reactants due to their low cost and tunable properties, but material degradation and capacity fade hinder their commercial deployment. In this work, the authors use spectroscopy and statistical inference techniques to elucidate the decay mechanism and establish a quantitative connection between molecular decay and capacity fade in organic redox-flow batteries. The study highlights the potential of using statistical inference to understand the causes of capacity fade and further develop these batteries.

NATURE COMMUNICATIONS (2023)

Article Computer Science, Artificial Intelligence

Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification

Cameron J. Gruich, Varun Madhavan, Yixin Wang, Bryan R. Goldsmith

Summary: This study investigates the application of three uncertainty quantification (UQ) methods in the field of heterogeneous catalysis. By using a crystal graph convolutional neural network to predict adsorption energies on alloys, the effectiveness of the UQ methods, namely k-fold ensembling, Monte Carlo dropout, and evidential regression, is evaluated. The results demonstrate that evidential regression is a powerful and trustworthy approach for obtaining tunable UQ estimates in heterogeneous catalysis applications using neural networks.

MACHINE LEARNING-SCIENCE AND TECHNOLOGY (2023)

Article Chemistry, Physical

Thermodynamic Stability and Anion Ordering of Perovskite Oxynitrides

Samuel D. D. Young, Jiadong Chen, Wenhao Sun, Bryan R. R. Goldsmith, Ghanshyam Pilania

Summary: Perovskiteoxynitrides (PONs) are promising materials for catalysis and photovoltaics, but their full potential has yet to be explored. This study predicts the stability of PON materials using density functional theory modeling and also determines the suitable range of electrochemical operating conditions. However, not all compounds with zero energy above the thermodynamic convex hull can be easily synthesized.

CHEMISTRY OF MATERIALS (2023)

Review Chemistry, Physical

Effects of ions on electrocatalytic hydrogenation and oxidation of organics in aqueous phase

Ankit Mathanker, Wendy Yu, Nirala Singh, Bryan R. Goldsmith

Summary: There is increasing interest in the influence of ions on electrocatalytic reactions. Spectator ions have not been fully explored in their impact on electrocatalytic rates of hydrogenation and oxidation of larger organic molecules. This article discusses various ways in which spectator ions can affect the electrocatalytic reactions of organic molecules and emphasizes the importance of further research in this area to develop more efficient electrocatalytic systems.

CURRENT OPINION IN ELECTROCHEMISTRY (2023)

Article Chemistry, Multidisciplinary

Unveiling the Cerium(III)/(IV) Structures and Charge-Transfer Mechanism in Sulfuric Acid

Nirala Singh, Cailin A. Buchanan, Dylan Herrera, Mahalingam Balasubramanian, Bryan R. Goldsmith

Summary: In this study, the structures and charge transfer (CT) mechanism of Ce3+ and Ce4+ ions in sulfuric acid were determined through experimental and computational methods. It was found that Ce3+ is coordinated by nine water molecules, while Ce4+ forms complexes with water and bisulfate ions. The kinetics of the Ce3+/Ce4+ redox couple were found to be independent of the electrode, indicating outer-sphere electron-transfer behavior. A two-step mechanism was proposed, in which Ce4+ exchanges bisulfate ions with water in a chemical step, followed by a rate-determining electron transfer step.

JACS AU (2022)

Article Chemistry, Physical

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Jacques A. Esterhuizen, Bryan R. Goldsmith, Suljo Linic

Summary: Unsupervised machine learning with principal component analysis offers a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of material properties. These descriptors can predict chemical properties and reveal connections between geometric structure and catalytic properties.

CHEM CATALYSIS (2021)

Article Chemistry, Multidisciplinary

Why halides enhance heterogeneous metal ion charge transfer reactions

Jacob Florian, Harsh Agarwal, Nirala Singh, Bryan R. Goldsmith

Summary: Research shows that the reaction kinetics of metal redox couples on electrode surfaces are enhanced in the presence of halides. Calculated desorption barriers of metal-anion complexes correlate with experimental kinetic measurements, guiding the design of electrolytes and electrocatalysts with faster kinetics for relevant redox reactions in energy and environmental applications.

CHEMICAL SCIENCE (2021)

Article Chemistry, Multidisciplinary

The Effect of Anion Bridging on Heterogeneous Charge Transfer for V2+/V2+

Harsh Agarwal, Jacob Florian, Bryan R. Goldsmith, Nirala Singh

Summary: This study investigates the kinetics of V2+/V3+ reaction in vanadium redox flow batteries, and explores the structures of V2+ and V3+ in different electrolytes. The results suggest that the polarizability of anions affects the kinetics of V2+/V3+ reaction in the batteries.

CELL REPORTS PHYSICAL SCIENCE (2021)

No Data Available