Herzfeld paper named “2023 Hot PCCP article”

images from Herzfeld paperIn a new paper (DOI: 10.1039/d2cp05648h), selected as a “2023 Hot PCCP article”, the Herzfeld group has shown that the “Lewis dot” representation of electrons can predict states that have otherwise been predicted only by the most advanced implementations of quantum mechanics.

Basically, the structures and reactions of molecules are controlled by the interactions of electrons with each other and with atomic nuclei. However, the process is complicated by the fact that wave properties are important for particles as light as electrons. The gold standard is to explicitly model these properties using wave mechanics. But it is convenient to have an implicit description that is more accessible and intuitive. These are the “Lewis dots” that are generally used to represent bonds and reaction mechanisms in chemistry courses and journal articles. Lewis dots are semi-classical particles: classical in the sense of being associated with a location in space, but non-classical in that they don’t stick to the oppositely charged nuclei and can have two different spin states.

In recent years, the Herzfeld group has sought to quantify this picture. A subtlety is that the interactions between electrons is spin dependent due to the antisymmetry of electron wave functions. This explains why electrons of unlike spin often form pairs. However, the charges of electrons should always repel one another and Linnett suggested already in 1961 that two electrons should only co-localize if they are both sufficiently attracted to the same inter-nuclear region. In their new paper, the Herzfeld group shows that, a careful representation of the effects of wave function anti-symmetry, leads to Linnett-like structures when there are not enough internuclear basins to induce all the electrons to form simple pairs. A striking example is given by benzene. The traditional semi-classical representation of benzene, as a resonance between two structures with alternating single and double bonds, is obviated by a structure with three electrons in each carbon-carbon bond (shown here with the six carbon kernels in teal, six hydrogen kernels in white, and 15 valence electrons of each spin in pink and magenta).

Publication: Emergence of Linnett’s “double quartets” from a model of “Lewis dots.” Judith Herzfeld. Physical Chemistry Chemical Physics, Issue 7, 2023.

Albion Lawrence receives 3-year funding from NASA’s Physical Oceanography program

Albion Lawrence

The ocean is a highly complex, multiscale system, with many types of motions occurring simultaneously. Ocean turbulence between 1km and hundreds of kilometers (the *submesoscale* and *mesoscale*) contains about 90% of the kinetic energy of the ocean, and is crucial for understanding the vertical and horizontal transport of heat, salt, carbon, and microorgamisms; and for understanding the coupling between the ocean and atmosphere. At these scales, internal waves driven by tides and wind also propagate through the ocean and play an important role in mixing such quantities. Characterizing and disentangling these different classes dynamics, and understanding how they interact, is a central problem in physical oceanography. This has become particularly salient with the December 2022 launch of the Surface Water and OceanTopography (SWOT) satellite, which will observe the ocean from space with unprecedented resolution.

Typical studies focus on the kinetic energy as a function of physical scale, (the “power spectrum”), to characterize ocean turbulence. However, this is a fairly blunt instrument and requires more precision than is available. Thus, Joern Callies, Assistant Professor for Environmental Science and Engineering at Caltech and Albion Lawrence, Professor of Physics, intend to use high-order statistical tests, inspired by tools used by observational cosmologists, quantum field theorists, and statistical physicists, to study mesoscale and submesoscale ocean dynamics using satellite observations, direct measurements made in the ocean, and numerical modeling. Their proposal, “Higher-order statistics of geostrophic turbulence and internal waves”, for which Professor Lawrence is the PI and Professor Callies is the Co-PI, was just selected for funding by the Physical Oceanography program at NASA. It was one of nine proposals selected out of 40 in 2022.

Professor Lawrence has been a theoretical high energy physicist for over thirty years, and has only recently begun working in climate-related physics problems. He just co-wrote two papers (arxiv.org, arxiv.org) on black holes and quantum gravity. To further help his move into this new field, he was also awarded a Simons Foundation Pivot Fellowship to spend the 2023-24 academic year embedded in Professor Callies’ group at Caltech. Brandeis’ collegial and interdisciplinary environment had a lot to do with the success and fun Professor Lawrence has had to date. This direction of his research was spurred by his involvement in a large multi-department NSF IGERT grant in “Geometry and Dynamics” that ran from 2011-2018; and got a very important boost from a Provost’s Innovation on “Nonequilbrium Statistical Mechanics of the Ocean and Atmosphere” that Lawrence received in 2019.

Brain rhythms coordinate neural networks to mediate memory-guided decision making

Significance of findings: The authors report coordination mechanisms between oscillations recorded in the CA1 subfield of the hippocampus, prefrontal cortex, and olfactory bulb and cell ensemble activity in CA1 and prefrontal cortex during odor-cued decision-making. The important findings support the hypothesis that the β rhythm plays a role in coordinating CA1-prefrontal cortex ensembles during decision-making. Sensory-guided decision-making is of broad significance to many readers who are studying executive functions and decision-making behaviors, and the observations reported in this manuscript provide convincing evidence of mechanisms that may support these functions and behaviors.

“Rhythmic coordination and ensemble dynamics in the hippocampal-prefrontal network during odor-place associative memory and decision making”. Claire A Symanski, John H Bladon, Emi T Kullberg, Paul Miller, Shantanu P Jadhav. eLife 2022, 11:e79545. DOI: 10.7554/eLife.79545

Simons Foundation: Jané Kondev discusses the Mathematics of Biology

As part of their 4 Minutes With series, the Simons Foundation recently presented a video of Jané Kondev, William R. Kenan, Jr. Professor of Physics, discussing the Mathematics of Biology. Kondev is a 2020 Simons Investigator in Theoretical Physics in Life Sciences.

Image: Simons Foundation

Kondev is a theoretical physicist who works primarily on problems in molecular and cell biology (Kondev Group).

 

 

Han receives DoD award to purchase X-ray diffraction instrument

Congratulations to Grace Han, Assistant Professor of Chemistry and Landsman Career Development Chair in the Sciences. She has been awarded funds from the Department of Defense to purchase a bench-top X-ray diffraction instrument. This award is part of the DoD’s Defense University Research Instrumentation Program (DURIP) that will provide $59 million in FY 2023 to purchase research equipment at 77 institutions across 30 states.

Changes in the properties of organic materials undergoing transition between solid and liquid phases are employed in a variety of applications, including thermal energy storage, cooling, and actuation. The ability to regulate such phase transitions by light opens up new opportunities to achieve functions with a high spatial precision, triggered by the rapid, remotely applied, and non-invasive stimulus. This capability enables novel applications including photo-controlled heat storage, adhesion, actuation, and catalyst recovery, which the Han group investigates.

The DURIP award from the Air Force Office of Scientific Research (AFOSR) and the Department of Defense (DoD) will enable the Han team to build a new research capability on campus. A non-ambient, benchtop X-ray diffractometer, equipped with light sources and a heating/cooling stage, will allow the group to study how molecules change their geometry and intermolecular interaction in response to irradiation and temperature change. This will yield a deep understanding of photoswitch designs that undergo facile structural changes in solid phase, assisting the discovery and development of light-responsive functional materials.

Designing synthetic DNA nanoparticles that assemble into tubules

How does nature assemble nanoscale structures? Unlike the typical top-down methods for manufacturing, biological systems manufacture functional nanomaterials from the bottom up using a process called self-assembly. In self-assembly, individual ‘building blocks’ are encoded with instructions about how to interact with one another. As a result, ordered structures spontaneously form from a soup of building blocks through thermal fluctuations alone. Famous examples of self-assembling structures in nature include viral capsids, which protect the genetic material and orchestrate viral infections, and microtubules, which form part of the highway systems used for intracellular transportation. However, until recently, manufacturing similarly complex nanostructures from synthetic materials was out of reach because there were no methods for synthesizing building blocks with the kinds of complex geometries and interactions common to biological molecules.

Assembled Tubules Under TEM

In collaboration with the Dietz Lab at the Technical University of Munich and the Grason Group at the University of Massachusetts Amherst, a team of scientists from the Rogers Lab, Hagan Group,  and Fraden Lab in the Department of Physics at Brandeis developed a class of nanoscale particles that can overcome this hurdle. They designed and synthesized triangular building blocks using a technique known as DNA origami, in which the single-stranded DNA genome from a bacteriophage is ‘folded’ into a user-prescribed 3D shape using a cocktail of short DNA oligonucleotides. The triangular particles that they designed bind to other triangles through specific edge-edge interactions with bond angles that can be independently tuned to make a surface with programmable curvature.

Daichi Hayakawa, a Ph.D. student in the Rogers Lab, tuned the triangle design so that the particles would spontaneously assemble into a tubule with a programmed width and chirality. Interestingly, the assembled tubules were highly polymorphic. In other words, the width and chirality varied from tubule to tubule. Working together with the Hagan Group in Physics, the team rationalized this observation by considering the ‘softness’ of the edge interaction, which allows thermal fluctuations to steer assembly away from the target geometry. To constrain this polymorphism, the research team came up with an alternative method. By using more than one distinct triangle type to assemble a single tubule geometry, they found that they could eliminate some of these off-target structures, thereby making tubule assembly more specific.

In summary, this work highlights two avenues for increasing the fidelity of self-closing structures self-assembled from simple building blocks: control of the curvature through precise geometrical design and addressable complexity through increasing the number of unique species in the assembly mixture. Not only will this result be useful for constructing self-closing nanostructures through self-assembly, but it may also help us understand the role of symmetry and complexity in other self-closing structures found in nature.

Publication:

Geometrically programmed self-limited assembly of tubules using DNA origami colloids. Daichi Hayakawa, Thomas E. Videbaek, Douglas M. Hall and W. Benjamin Rogers.  Proc Natl Acad Sci USA. 2022 Oct 25;119(43):e2207902119.

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