College of Chemistry

Various theoretical approaches, including big data and high-throughput screening techniques, have been explored in developing new materials due to their significant potential time-saving advantages. However, it remains a significant challenge to experimentally realize new materials that are predicted. In this study, we propose a novel materials design strategy that utilizes machine-learning (ML) techniques to predict new porous materials that show promise for hydrogen storage and are likely to be feasible to synthesize. By leveraging ML techniques and metal–organic framework (MOF) databases, we are able to predict the synthesizability of MOF structures. This is evidenced by the successful synthesis of a new vanadium-based MOF that exhibits excellent performance for cryogenic H2 storage. Notably, the total gravimetric and volumetric H2 uptakes are as high as 9.0 wt% and 50.0 g/L at 77 K and 150 bar. This ML-assisted materials design offers an efficient and promising approach for developing hydrogen storage materials.

Soft X-ray absorption spectroscopy of first row transition elements at their respective L-edges provides important information about the oxidation and spin states of the metal centers. However, the associated sample damage in radiation-sensitive samples substantially alters the electronic and chemical structures of redox-active metal centers. Here, we measure the soft X-ray spectrum of the model MnIII(acac)3 complex containing a redox-active MnIII metal center in an octahedral environment with a superconducting transition-edge sensor detector. To reduce the secondary damage resulting primarily from the diffusion of radicals and electrons, the spectra are collected at 30 K and 80 K on solid samples. Starting from the first scan, we detect the contribution of X-ray induced sample damage leading to a change in the MnII intensity. However, at low temperatures, particularly at 30 K, we do not observe a gradual increase in the radiation damage with successive scans with the X-ray beam at the same spot. At our estimated dose of 90 kGy, we find 62% of MnIII(acac)3 is still intact at 30 K. However, at room temperature, we see a gradual increase in radiation damage with increasing numbers of scans at the same spot, which is consistent with the possibility of increased diffusion rates of secondary radicals and electrons as noted in other studies.

Nanoribbons, nanometre-wide strips of a two-dimensional material, are a unique system in condensed matter. They combine the exotic electronic structures of low-dimensional materials with an enhanced number of exposed edges, where phenomena including ultralong spin coherence times1,2, quantum confinement3 and topologically protected states4,5 can emerge. An exciting prospect for this material concept is the potential for both a tunable semiconducting electronic structure and magnetism along the nanoribbon edge, a key property for spin-based electronics such as (low-energy) non-volatile transistors6. Here we report the magnetic and semiconducting properties of phosphorene nanoribbons (PNRs). We demonstrate that at room temperature, films of PNRs show macroscopic magnetic properties arising from their edge, with internal fields of roughly 240 to 850 mT. In solution, a giant magnetic anisotropy enables the alignment of PNRs at sub-1-T fields. By leveraging this alignment effect, we discover that on photoexcitation, energy is rapidly funnelled to a state that is localized to the magnetic edge and coupled to a symmetry-forbidden edge phonon mode. Our results establish PNRs as a fascinating system for studying the interplay between magnetism and semiconducting ground states at room temperature and provide a stepping-stone towards using low-dimensional nanomaterials in quantum electronics.

Despite tremendous efforts to engineer translational machinery, replacing the encoded peptide backbone with new-to-nature structures remains a significant challenge. C, H, O, and N are the elements of life, yet ribosomes are capable of forming only C-N bonds as amides, C-O bonds as esters, and C-S bonds as thioesters. There is no current strategy to site-selectively form C-C bonds as ketones embedded in the backbones of ribosomal products. As an alternative to direct ribosomal C-C bond formation, here we report that peptides containing a dehydrolactic acid motif rapidly isomerize to generate backbone-embedded α,γ-diketoamides via a spontaneous formal O to C acyl shift rearrangement. The dehydrolactic acid motif can be introduced into peptides ribosomally or via solid-phase synthesis using α-hydroxyphenylselenocysteine followed by oxidation. Subsequent incubation at physiological pH produces an α,γ-diketoamide that can be diversified using a variety of nucleophiles, including hydrazines and hydroxylamines, to form pyrazoles and oximes, respectively. All of these groups remain embedded directly within the polypeptide backbone. This general strategy for peptide backbone editing, predicated on an intricate cascade of acyl rearrangements, provides the first nonenzymatic example of a C-C bond forming reaction to take place within a peptide backbone. The products so-produced are easily diversified into protein-like materials with backbone-embedded heterocycles. Application of this peptide editing strategy should accelerate the discovery of genetically encoded molecules whose properties more closely resemble those of bioactive natural products.

Urban areas are major contributors to greenhouse gas emissions, necessitating effective monitoring systems to evaluate mitigation strategies. A dense sensor network, such as the Berkeley Environmental Air-quality & CO2 Observation Network (BEACO2N), offers a unique opportunity to monitor urban emissions at high spatial resolution. Here, we describe a simple approach to quantifying urban emissions with sufficient precision to constrain seasonal and annual trends. Measurements from 12 BEACO2N sites in Los Angeles (called the USC Carbon Census) are analyzed within a box model framework. By combining CO2 and CO observations, we partition total CO2 emissions into fossil fuel and biogenic emissions. We infer temporal changes in biogenic emissions that correspond to the MODIS enhanced vegetation index (EVI) and show that net biogenic exchange can consume up to 60% of fossil fuel emissions in the growing season during daytime hours. While we use the first year of observations to describe seasonal variation, we demonstrate the feasibility of this approach to constrain annual and longer trends.

The prevalence of saturated azacycles within pharmaceuticals, natural products, and agrochemicals has prompted the development of many methods that modify their periphery. In contrast, technologies that interconvert distinct saturated azacyclic frameworks, which would uniquely facilitate access to underexplored chemical space, are highly limited. Existing approaches for modifying the core of azacycles usually require either the installation of reactive functionality, which must later be removed in subsequent steps, or the use of tailored substrates, limiting applicability to drug discovery. Herein, we report a borane-catalyzed contraction of saturated N-hydroxy azacycles. This transformation is uniquely enabling, allowing reorganization of the connectivity of the substrate without altering the molecular formula and generating products without vestigial functionality derived from auxiliary groups. The outcome of the reductive Stieglitz-type contraction can be attributed to a key stereoelectronic interaction enforced by geometric constraints, the mechanism of which we investigate using density functional theory. The method developed here enables the rapid late-stage reorganization of bioactive molecules featuring cyclic and linear amines. Overall, a general platform for saturated amine constitutional isomerization has been achieved.

Deployment of large numbers of low capital cost sensors to increase the spatial density of air quality measurements enables applications that build on mapping air at neighborhood scales. Effective deployment requires not only low capital costs for observations but also a simultaneous reduction in labor costs. The Berkeley Environmental Air Quality and CO2 Network (BEACO2N) is a sensor network measuring O3, CO, NO, and NO2, particulate matter (PM2.5), and CO2 at dozens of locations in cities where it is deployed. Here, we describe a low labor cost in situ field calibration for the BEACO2N O3, CO, NO, and NO2 sensors. This method identifies and leverages uniform periods in concentrations across the network for calibration. The calibration achieves high accuracy and low biases with respect to temperature, humidity, and concentration, with coefficients of determination and root mean square errors of 0.88 and 3.70 ppb for O3, 0.66 and 3.16 ppb for NO2, and 0.79 and 1.58 ppb for NO. Performance of the CO sensor is 0.90 and 33.3 ppb at a site colocated with reference measurements. The method is a crucial step toward lowering operational costs of delivering accurate measurements in dense networks employing large numbers of inexpensive air quality sensors.

Photoelectrochemistry (PEC) presents a direct pathway to solar fuel synthesis by integrating light absorption and catalysis into compact electrodes. Yet, PEC hydrocarbon production remains elusive due to high catalytic overpotentials and insufficient semiconductor photovoltage. Here we demonstrate ethane and ethylene synthesis by interfacing lead halide perovskite photoabsorbers with suitable copper nanoflower electrocatalysts. The resulting perovskite photocathodes attain a 9.8% Faradaic yield towards C2 hydrocarbon production at 0 V against the reversible hydrogen electrode. The catalyst and perovskite geometric surface areas strongly influence C2 photocathode selectivity, which indicates a role of local current density in product distribution. The thermodynamic limitations of water oxidation are overcome by coupling the photocathodes to Si nanowire photoanodes for glycerol oxidation. These unassisted perovskite–silicon PEC devices attain partial C2 hydrocarbon photocurrent densities of 155 µA cm−2, 200-fold higher than conventional perovskite–BiVO4 artificial leaves for water and CO2 splitting. These insights establish perovskite semiconductors as a versatile platform towards PEC multicarbon synthesis. (Figure presented.)

Sciences broader impacts and the historic social, political, and geographic implications of these impacts are rarely discussed in graduate STEM curricula. A new required Scientific Responsibility and Citizenship course for first year chemistry graduate students was developed and taught at UC Berkeley. The course examined a series of case studies in which basic chemistry research led to societal impacts and discussed the diversity and equity of the research process and resulting consequences. The impact of the course was examined through pre- and post-surveys and interviews with participants. The course was found to have raised students awareness and sense of responsibility for the impacts of their research and the importance of diversity, equity, and inclusion. Students also expressed an increased sense of identity and value alignment with the community as a result of the course. This study shows that even a relatively low-commitment intervention (6 hours in total), can have a large positive impact on students awareness of the social context of science and their perceptions of department values.