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At least 865 records · Page 48

Selective photo-excitation of molecules enabled by stimulated Raman pre-excitation

Double resonance excitation, where the energies of vibrational and electronic molecular transitions are combined in a single, sequential excitation process, was introduced in the 1970s but has only been recently applied to microscopy due to the immense progress in Raman spectroscopy. The value of the technique is in combining the chemical selectivity of IR or Raman excitation with the much larger cross-sections of electronic transitions. Recently, it has been shown to be particularly suited for the detection and identification of chromophores at low concentrations and in the presence of spectral crosstalk. However, despite its low quantum yield per pulse sequence, we believe the technique has potential for selective photochemical transformations. There are some cases (e.g., the selective excitation of optogenetic switches) where the low yield may be overcome by repeated excitations to build up biochemically relevant concentrations. Here we show that double resonance excitation using general, non-resonant Raman pre-excitation is a viable candidate for selectively promoting molecules to chemically active energy levels. Further, the use of non-resonant Raman pre-excitation is less constraining than resonant Raman (used in previous double resonance microscopy works) since the choice of Raman pump-Stokes frequencies may be rather freely chosen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High throughput single cell multiomics platform [Abstract]

In this collaborative project, PNNL and Scienion will co-develop an integrated microfluidic technology to co-measure the transcriptome and proteome in single cells. The technology will enable us to efficiently separate proteins from mRNA transcripts between two microchips, barcode the molecules, and measure them separately with next-generation sequencing and mass spectrometry, respectively. Multicellular organisms contain diverse cell types and tremendous cell-to-cell heterogeneity that dictates a multitude of biological functions in both physiological and pathological environments. Even in the case of microbes, these genetically identical organisms can randomly differentiate into many subpopulations that assume different roles for the survival of the community. Bulk-scale measurements are insufficient to resolve such complexities. The development and applications of high throughput single-cell omics technologies have transformed our understanding of cellular heterogeneities and their differential responses to internal signaling events or external stimulations. Despite these advances, most current single-cell omic technologies provide information on only one type of biomolecule. Perse, such measurements provide incomplete information because the cell phenotype is determined by multiple layers of biomolecules and the interplay between genome, epigenome, transcriptome, and proteome. For example, mRNA abundance in one cell can not be precisely referred to the corresponding DNA and protein in other cells because of the potential subtle difference in genotype (e.g., somatic mutation or copy number variation) or phenotype (external microenvironment and cell-cell interactions). As such, parallel measurement of multiple biomolecules in the same single cells can offer unique advantages compared with measuring them separately in different single cells. Scienion is a world-leading biotech company focusing on precision liquid handling and its application in single-cell whole-genome sequencing and RNA sequencing. PNNL is the leading institution in ultrasensitive mass spectrometry, microfluidics, and untargeted single-cell proteomics (scProteomics). This collaboration will facilitate a unique fusion between scTranscriptomics capability at Scienion and scProteomics capabilities at PNNL to, for the first time, perform both untargeted transcriptomics and proteomics from the same single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗

In situ visualisation of zeolite anisotropic framework flexibility during catalysis

Zeolites exhibit framework flexibility driving their chemical and catalytic properties. Since the zeolitic pores are extremely small, a slight strain generated in the crystal induces compelling changes in shape, connectivity, accessibility, and the framework chemical properties. These modifications affected the adsorption and desorption of reactants/products and the diffusion within the channels during reaction. Using in situ 3D Bragg coherent X-ray diffraction imaging, we unveil the dynamics of the zeolite structure during catalysis, contraction and/or expansion of its framework also known as zeolite framework flexibility. Here, we imaged three-dimensionally a single faujasite zeolite crystal during the ethanol dehydration reaction revealing anisotropic lattice dynamics simultaneously to guest molecules formation. Understanding zeolite flexibility could permit to tune zeolites properties towards potentially higher adsorption and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma production and composition from hypervelocity impacts on solar cell cover glass

Satellites are subjected to detrimental effects from the space environment, including impacts by orbital debris and meteoroids that can cause mechanical or electrical damage. While mechanical damage is well studied, electrical effects resulting from hypervelocity impact (HVI) remain poorly understood. In HVIs, where the projectile speed exceeds the speed of sound in the target material, the impact energy ionizes the material near the surface, creating a plasma that can cause radio frequency emission. This emission is the main source of electrical anomalies in satellites, but the mechanism behind its creation is still unknown. Ground-based experiments have been used to characterize HVI plasma, including the empirical power law relations that describe the impact charge produced as a function of impactor mass and speed. Quantifying these power law relations gives us a better understanding of the species formed in the impact which can eventually lead to plasma evolution models and help us first, understand the mechanism behind radio frequency emission and second, ways to prevent its damage to the satellites. In this paper, we interpret the results of the HVI experiments on solar cell coverglass targets and identify the potential chemical or molecular reactions that form the impact ion species. This is done by looking simultaneously at multiple data sets for different species within the same impact configuration, and using a new technique for quantifying the power law relations for each emitted species. We use time of flight analysis (TOF) to detect the charged particle compositions and determine their initial speeds. The results suggest that the charge production power law is species specific, with different formation mechanisms involved in a single HVI event, some of which are associated with dissociation and some with ionization of a molecule. Furthermore, our results also show that electrons have different power laws that depend on the spacecraft surface charge. TOF measurements of ions from impact events on solar cell cover glass shows the presence of SiO + and SiO – 2 as the dominant species present in plasmas on positively and negatively charged targets, respectively, as well as the formation of FeO + .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Role of Metal Cocatalysts in the Photocatalytic Production of Hydrogen from Water Revisited

The use of photocatalysts to promote the production of molecular hydrogen from water, following the so-called water splitting reaction, continues to be a promising route for the green production of fuels. The molecular basis of this photocatalysis is the photoexcitation of electrons from the valence band of semiconductors to their conduction band, from which they can be transferred to chemical reactants, protons in the case of water, to promote a reduction reaction. The mechanism by which such a process takes place has been studied extensively using titanium oxide, a simple material that fulfills most requirements for water splitting. However, photocatalysis with TiO 2 tends to be highly inefficient; a cocatalyst, commonly a late transition metal (Au, Pt) in nanoparticle form, needs to be added to facilitate the production of H 2 . The metal is widely believed to help with the scavenging of the excited electrons from the conduction band of the semiconductor in order to prevent their recombination with the accompanying hole formed in the valence band, a step that cancels the initial photon absorption and competes with the photolytic chemical reduction. Here we review and analyze the molecular basis for that mechanism and argue for an alternative explanation, that the role of the metal is to help with the recombination of the atomic hydrogen atoms produced by proton reduction on the semiconductor surface instead. First, we summarize what is known about the electronic structure of these photocatalysts and how the electronic levels need to line up for the reduction of protons in water to be feasible. Next, we review the current understanding of the dynamics of the steps associated with the absorption of photons, the de-excitation via electron–hole pair recombination and fluorescence decay, and the electronic transitions that lead to proton reduction, and contrast those with the rates of the chemical steps required to produce molecular hydrogen. The following section addresses the changes introduced by the addition of the metal cocatalyst, comparatively evaluating its role as either an electron scavenger or a promoter of the recombination of hydrogen atoms. A discussion of the viable chemical mechanisms for the latter pathway is included. Finally, we briefly mention other associated aspects of this photocatalysis, including the possible promotion of H 2 production with visible light via resonant excitation of the surface plasmon of Au nanoparticles, the use of single-metal (Au, Pt) atom catalysts and of yolk–shell nanostructures, and the reduction of organic molecules. We end with a brief personal perspective on the possible generality of the concepts introduced in this Critical Review.

08 HYDROGEN↗

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials Data on C2SNCl2F5 by Materials Project

CF3CF2NSCl2 crystallizes in the monoclinic P2_1/c space group. The structure is zero-dimensional and consists of eight difluoromethane molecules, eight fluoroform molecules, and eight NSCl2 clusters. In each NSCl2 cluster, N1+ is bonded in a distorted single-bond geometry to one S2- atom. The N–S bond length is 1.51 Å. S2- is bonded in a distorted trigonal non-coplanar geometry to one N1+ and two Cl1- atoms. Both S–Cl bond lengths are 2.12 Å. There are two inequivalent Cl1- sites. In the first Cl1- site, Cl1- is bonded in a distorted single-bond geometry to one S2- atom. In the second Cl1- site, Cl1- is bonded in a distorted single-bond geometry to one S2- atom.

36 MATERIALS SCIENCE↗

Materials Data on WSe6ICl6 by Materials Project

WCl6(Se)4Se2I crystallizes in the triclinic P-1 space group. The structure is zero-dimensional and consists of four selenium molecules, one tungsten(vi) chloride molecule, and one Se2I cluster. In the Se2I cluster, Se+0.33+ is bonded in a single-bond geometry to one I1- atom. The Se–I bond length is 2.79 Å. I1- is bonded in a linear geometry to two equivalent Se+0.33+ atoms.

36 MATERIALS SCIENCE↗

Materials Data on ZnFeC5N6O by Materials Project

(FeZnC5N6)2O2 crystallizes in the trigonal R-3 space group. The structure is three-dimensional and consists of three ac1l9mop molecules and one FeZnC5N6 framework. In the FeZnC5N6 framework, Fe2+ is bonded in a distorted single-bond geometry to four C+3.20+ and one N3- atom. There are a spread of Fe–C bond distances ranging from 1.90–1.93 Å. The Fe–N bond length is 1.52 Å. Zn2+ is bonded in a square pyramidal geometry to five N3- atoms. There are a spread of Zn–N bond distances ranging from 1.99–2.10 Å. There are five inequivalent C+3.20+ sites. In the first C+3.20+ site, C+3.20+ is bonded in a linear geometry to one Fe2+ and one N3- atom. The C–N bond length is 1.16 Å. In the second C+3.20+ site, C+3.20+ is bonded in a linear geometry to one Fe2+ and one N3- atom. The C–N bond length is 1.16 Å. In the third C+3.20+ site, C+3.20+ is bonded in a linear geometry to one Fe2+ and one N3- atom. The C–N bond length is 1.17 Å. In the fourth C+3.20+ site, C+3.20+ is bonded in a linear geometry to one Fe2+ and one N3- atom. The C–N bond length is 1.16 Å. In the fifth C+3.20+ site, C+3.20+ is bonded in a single-bond geometry to one N3- atom. The C–N bond length is 1.17 Å. There are six inequivalent N3- sites. In the first N3- site, N3- is bonded in a linear geometry to one Zn2+ and one C+3.20+ atom. In the second N3- site, N3- is bonded in a linear geometry to one Zn2+ and one C+3.20+ atom. In the third N3- site, N3- is bonded in a linear geometry to one Zn2+ and one C+3.20+ atom. In the fourth N3- site, N3- is bonded in a single-bond geometry to one Fe2+ atom. In the fifth N3- site, N3- is bonded in a linear geometry to one Zn2+ and one C+3.20+ atom. In the sixth N3- site, N3- is bonded in a linear geometry to one Zn2+ and one C+3.20+ atom.

36 MATERIALS SCIENCE↗

Materials Data on Re2SnC10(ClO5)2 by Materials Project

ReCl2ReCO2SnC(CO)8 crystallizes in the monoclinic P2_1/c space group. The structure is zero-dimensional and consists of four 7440-31-5 molecules, four dichlororhenium molecules, thirty-two formaldehyde molecules, four methane molecules, and four ReCO2 clusters. In each ReCO2 cluster, Re5+ is bonded in a distorted single-bond geometry to two O2- atoms. There are one shorter (1.74 Å) and one longer (2.29 Å) Re–O bond lengths. C+0.80+ is bonded in a single-bond geometry to one O2- atom. The C–O bond length is 1.22 Å. There are two inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted single-bond geometry to one Re5+ and one C+0.80+ atom. In the second O2- site, O2- is bonded in a single-bond geometry to one Re5+ atom.

36 MATERIALS SCIENCE↗

Materials Data on U2AsS2 by Materials Project

(US)2As crystallizes in the tetragonal P4mm space group. The structure is zero-dimensional and consists of one arsenic molecule and two US clusters. In each US cluster, U+3.50+ is bonded in a single-bond geometry to one S2- atom. The U–S bond length is 2.31 Å. S2- is bonded in a single-bond geometry to one U+3.50+ atom.

36 MATERIALS SCIENCE↗

Materials Data on ReSiTc2 by Materials Project

ReTc2Si is Zincblende, Sphalerite structured and crystallizes in the orthorhombic Immm space group. The structure is zero-dimensional and consists of two rhenium molecules and two Tc2Si clusters. In each Tc2Si cluster, Tc+0.50+ is bonded in a single-bond geometry to one Si4- atom. The Tc–Si bond length is 2.31 Å. Si4- is bonded in a linear geometry to two equivalent Tc+0.50+ atoms.

36 MATERIALS SCIENCE↗

Materials Data on MoBr5N2O by Materials Project

MoOBr5N2 crystallizes in the orthorhombic Pnma space group. The structure is zero-dimensional and consists of eight ammonia molecules and four MoOBr5 clusters. In each MoOBr5 cluster, Mo5+ is bonded in a distorted single-bond geometry to one O2- and five Br1- atoms. The Mo–O bond length is 1.70 Å. There are a spread of Mo–Br bond distances ranging from 2.43–2.90 Å. O2- is bonded in a single-bond geometry to one Mo5+ atom. There are four inequivalent Br1- sites. In the first Br1- site, Br1- is bonded in a distorted single-bond geometry to one Mo5+ atom. In the second Br1- site, Br1- is bonded in a single-bond geometry to one Mo5+ atom. In the third Br1- site, Br1- is bonded in a distorted single-bond geometry to one Mo5+ atom. In the fourth Br1- site, Br1- is bonded in a distorted single-bond geometry to one Mo5+ atom.

36 MATERIALS SCIENCE↗

Materials Data on MnTc2Sb by Materials Project

MnTc2Sb is Cyanogen Chloride-like structured and crystallizes in the orthorhombic Immm space group. The structure is zero-dimensional and consists of two manganese molecules and two Tc2Sb clusters. In each Tc2Sb cluster, Tc+0.50+ is bonded in a single-bond geometry to one Sb3- atom. The Tc–Sb bond length is 2.52 Å. Sb3- is bonded in a linear geometry to two equivalent Tc+0.50+ atoms.

36 MATERIALS SCIENCE↗

Materials Data on IrN7ClO6 by Materials Project

IrNCl(N2)2(NO3)2 crystallizes in the tetragonal I4 space group. The structure is zero-dimensional and consists of eight ammonia molecules, four nitric acid molecules, and two IrNCl clusters. In each IrNCl cluster, Ir4+ is bonded in a distorted single-bond geometry to one N+1.29+ and one Cl1- atom. The Ir–N bond length is 1.74 Å. The Ir–Cl bond length is 2.65 Å. N+1.29+ is bonded in a single-bond geometry to one Ir4+ atom. Cl1- is bonded in a single-bond geometry to one Ir4+ atom.

36 MATERIALS SCIENCE↗

Materials Data on Re3S4O9 by Materials Project

Re3S4O3(O2)3 is High-temperature superconductor structured and crystallizes in the trigonal R-3 space group. The structure is zero-dimensional and consists of nine hydrogen peroxide molecules and three Re3S4O3 clusters. In each Re3S4O3 cluster, Re6+ is bonded in a distorted single-bond geometry to four S and one O2- atom. There are three shorter (2.39 Å) and one longer (2.40 Å) Re–S bond lengths. The Re–O bond length is 1.70 Å. There are two inequivalent S sites. In the first S site, S is bonded in a 3-coordinate geometry to three equivalent Re6+ atoms. In the second S site, S is bonded in a 3-coordinate geometry to three equivalent Re6+ atoms. O2- is bonded in a single-bond geometry to one Re6+ atom.

36 MATERIALS SCIENCE↗

Materials Data on AlSiTc2 by Materials Project

Tc2SiAl is Zincblende, Sphalerite structured and crystallizes in the orthorhombic Immm space group. The structure is zero-dimensional and consists of two aluminum molecules and two Tc2Si clusters. In each Tc2Si cluster, Tc+0.50+ is bonded in a single-bond geometry to one Si4- atom. The Tc–Si bond length is 2.28 Å. Si4- is bonded in a linear geometry to two equivalent Tc+0.50+ atoms.

36 MATERIALS SCIENCE↗