Discover Chemical Engineering

I describe some of my activities, academic and personal, since coming to the United States in 1946 at the age of 16. It has been a long journey with many ups and downs. I selectively and briefly describe my experiences in a rabbinical school with an attached (parochial) high school, at Brooklyn College, in graduate school at Syracuse University, during a postdoc with Lars Onsager at Yale University, and in my academic positions at Stevens Institute of Technology, Yeshiva University and Rutgers University. I write at greater length about some experiences traveling to the Soviet Union (now Russia) during the period of 1978–1990, where I went to meet with refusenik and dissident scientists. There, I met Andrei Sakharov, whose fight for human rights has been an inspiration to me. I conclude with a talk I recently gave (via film) at the March 2024, meeting of the American Physical Society.

AbstractColloidal dispersions exhibit rich equilibrium and nonequilibrium thermodynamic properties, self-assemble into diverse structures at different length scales, and display transport behavior under bulk conditions. In confinement or under geometrical restrictions, new phenomena emerge that have no counterpart when the colloids are embedded in an open, noncurved space. In this review, we focus on the effects of confinement and geometry on the self-assembly and transport of colloids and fluidized granular systems, which serve as model systems. Our goal is to summarize experiments, theoretical approximations and molecular simulations that provide physical insight on the role played by the geometry at the mesoscopic scale. We highlight particular challenges, and show preliminary results based on the covariant Smoluchowski equation, that present promising avenues to study colloidal dynamics in a non-Euclidean geometry.

Fractons emerge from many-body systems, featuring subdimensional particles with restricted mobility. These particles have attracted interest for their roles across disciplines, including topological quantum codes, quantum field theory, emergent gravity, and quantum information. They display unique nonequilibrium behaviors such as nonergodicity and glassy dynamics. This review offers a structured overview of fracton phenomena, especially those of gapless fracton liquids, which enable collective modes similar to gauge fluctuations in Maxwell's electromagnetic framework, yet their phenomena are distinguished by a unique conservation law that restricts the mobility of individual charges and monopoles. We delve into the theoretical basis of three-dimensional (3D) fracton liquids, exploring emergent symmetric tensor gauge theories and their properties. We also discuss the material realization of fracton liquids in Yb-based pyrochlore lattices and other synthetic quantum matter platforms.

Solids are rigid, which means that when left undisturbed, their structures are nearly static. It follows that these structures depend on history—but it is surprising that they hold readable memories of past events. Here, we review the research that has recently flourished around mechanical memory formation, beginning with amorphous solids’ various memories of deformation and mesoscopic models based on particle rearrangements. We describe how these concepts apply to a much wider range of solids and glassy matter, and how they are a bridge to memory and physical computing in mechanical metamaterials. An understanding of memory in all these solids can potentially be the basis for designing or training functionality into materials. Just as important is memory's value for understanding matter whenever it is complex, frustrated, and out of equilibrium.

Spin-polarized antiferromagnets have recently gained significant interest because they combine the advantages of both ferromagnets (spin polarization) and antiferromagnets (absence of net magnetization) for spintronics applications. In particular, spin-polarized antiferromagnetic metals can be useful as active spintronics materials because of their high electrical and thermal conductivities and their ability to host strong interactions between charge transport and magnetic spin textures. We review spin and charge transport phenomena in spin-polarized antiferromagnetic metals in which the interplay of metallic conductivity and spin-split bands offers novel practical applications and new fundamental insights into antiferromagnetism. We focus on three types of antiferromagnets: canted antiferromagnets, noncollinear antiferromagnets, and collinear altermagnets. We also discuss how the investigation of spin-polarized antiferromagnetic metals can open doors to future research directions.

Trapped ions offer long coherence times and high fidelity, programmable quantum operations, making them a promising platform for quantum simulation of condensed matter systems, quantum dynamics, and problems related to high-energy physics. We review selected developments in trapped-ion qubits and architectures and discuss quantum simulation applications that utilize these emerging capabilities. This review emphasizes developments in digital (gate-based) quantum simulations that exploit trapped-ion hardware capabilities, such as flexible qubit connectivity, selective mid-circuit measurement, and classical feedback, to simulate models with long-range interactions, explore nonunitary dynamics, compress simulations of states with limited entanglement, and reduce the circuit depths required to prepare or simulate long-range entangled states.

The shape of a soft solid is largely determined by the balance between elastic and surface energies with capillarity becoming important at length scales smaller than the elastocapillary length, which approaches the millimeter scale for the softest hydrogels, leading to many new and surprising phenomena. This review is focused on describing recent experimental and theoretical progress on the deformations of soft solids due to capillarity in two-phase systems for both statics and dynamics. Relative to rigid solids, surface tension can lead to the rounding of sharp corners, wrinkling and creasing, and general morphological shape-change of the static equilibrium configuration, beyond a critical elastocapillary number. With regard to dynamics, both surface tension and viscoelasticity affect wave number selection in a number of dynamic pattern formation phenomena in soft solids, such as elastocapillary-gravity waves, Rayleigh–Taylor instability, Plateau–Rayleigh instability, Faraday waves, and drop oscillations, all of which have direct analogs with classical hydrodynamic instabilities helping to interpret the relevant physics.

With the growing number of microscale devices from computer memory to microelectromechanical systems, such as lab-on-a-chip biosensors and the increased ability to experimentally measure at the micro- and nanoscale, modeling systems with stochastic processes is a growing need across science. In particular, stochastic partial differential equations (SPDEs) naturally arise from continuum models—for example, a pillar magnet's magnetization or an elastic membrane's mechanical deflection. In this review, I seek to acquaint the reader with SPDEs from the point of view of numerically simulating their finite-difference approximations, without the rigorous mathematical details of assigning probability measures to the random field solutions. I will stress that these simulations with spatially uncorrelated noise may not converge as the grid size goes to zero in the way that one expects from deterministic convergence of numerical schemes in two or more spatial dimensions. I then present some models with spatially correlated noise that maintain sampling of the physically relevant equilibrium distribution. Numerical simulations are presented to demonstrate the dynamics; the code is publicly available on GitHub.

Even when ideal solids are insulating, their states with crystallographic defects may have superfluid properties. It became clear recently that edge dislocations in 4He featuring a combination of microscopic quantum roughness and superfluidity of their cores may represent a new paradigmatic class of quasi-one-dimensional superfluids. The new state of matter, termed transverse quantum fluid (TQF), is found in a variety of physical setups. The key ingredient defining the class of TQF systems is infinite compressibility, which is responsible for all other unusual properties such as the quadratic spectrum of normal modes (or even the absence of sharp quasiparticles), irrelevance of the Landau criterion, off-diagonal long-range order at T = 0, and the exponential dependence of the phase slip probability on the inverse flow velocity. From a conceptual point of view, the TQF state is a striking demonstration of the conditional character of many dogmas associated with superfluidity, including the necessity of elementary excitations, in general, and the ones obeying the Landau criterion in particular.

Organisms maintain the status quo, holding key physiological variables constant to within an acceptable tolerance, and yet adapt with precision and plasticity to dynamic changes in externalities. What organizational principles ensure such exquisite yet robust control of systems-level “state variables” in complex systems with an extraordinary number of moving parts and fluctuating variables? Here, we focus on these issues in the specific context of intra- and intergenerational life histories of individual bacterial cells, whose biographies are precisely charted via high-precision dynamic experiments using the SChemostat technology. We highlight intra- and intergenerational scaling laws and other “emergent simplicities” revealed by these high-precision data. In turn, these facilitate a principled route to dimensional reduction of the problem and serve as essential building blocks for phenomenological and mechanistic theory. Parameter-free data-theory matches for multiple organisms validate theory frameworks and explicate the systems physics of stochastic homeostasis and adaptation.

The flattening of single-particle band structures plays an important role in the quest for novel quantum states of matter owing to the crucial role of interactions. Recent advances in theory and experiment made it possible to construct and tune systems with nearly flat bands, ranging from graphene multilayers and moiré materials to kagome metals and ruthenates. Although theoretical models predict exactly flat bands under certain ideal conditions, evidence was provided that these systems host high-order Van Hove points, i.e., points of high local band flatness and power-law divergence in energy of the density of states. In this review, we examine recent developments in engineering and realizing such weakly dispersive bands. We focus on high-order Van Hove singularities and explore their connection to exactly flat bands. We provide classification schemes and discuss interaction effects. We also review experimental evidence for high-order Van Hove singularities and point out future research directions.

Active matter theories naturally describe the mechanics of living systems. As biological matter is overwhelmingly chiral, an understanding of the implications of chirality for the mechanics and statistical mechanics of active materials is a priority. This article examines active, chiral materials from a liquid-crystal physicist's point of view, extracting general features of broken-symmetry-ordered phases of such systems without reference to microscopic details. Crucially, this demonstrates that activity allows chirality to affect the hydrodynamics of broken-symmetry phases in contrast to passive liquid crystals, in which chirality induces the formation of a range of spatially periodic structures whose large-scale mechanics have no signatures of broken parity symmetry. In active systems, chirality leads to the formation of phases that break time translation symmetry, which is impossible in equilibrium, and the existence of new kinds of elastic force densities in translation symmetry-broken states.

Abstract We discuss the emerging advances and opportunities at the intersection of machine learning (ML) and climate physics, highlighting the use of ML techniques, including supervised, unsupervised, and equation discovery, to accelerate climate knowledge discoveries and simulations. We delineate two distinct yet complementary aspects: (a) ML for climate physics and (b) ML for climate simulations. Although physics-free ML-based models, such as ML-based weather forecasting, have demonstrated success when data are abundant and stationary, the physics knowledge and interpretability of ML models become crucial in the small-data/nonstationary regime to ensure generalizability. Given the absence of observations, the long-term future climate falls into the small-data regime. Therefore, ML for climate physics holds a critical role in addressing the challenges of ML for climate simulations. We emphasize the need for collaboration among climate physics, ML theory, and numerical analysis to achieve reliable ML-based models for climate applications.

Antibiotics are a cornerstone of modern medicine, and antibiotic resistance is a growing threat to public health. The evolution of resistance is a multiscale process shaped by many of the same phenomena that have fascinated condensed matter physicists for decades: fluctuations, disorder, scaling, and the emergence of structure from local heterogeneous interactions. In this review, we offer a brief introduction to antibiotic resistance through the lens of these shared cross-disciplinary themes. We highlight conceptual connections shared across disciplines and aim to inspire continued investigation of this complex and important biomedical problem.

Over the past approximately 10 years, it has become routine to use piezoelectric actuators to apply large anisotropic stresses to correlated electron materials. Elastic strains exceeding 1% can often be achieved, which is sufficient to qualitatively alter the magnetic and/or electronic structures of a wide range of correlated electron materials. Experiments fall into two broad groups. In one, explicit use is made of the capacity of anisotropic stress to reduce the point group symmetry of the lattice, for example, from tetragonal to orthorhombic. In the other, anisotropic stress is used as a more general, powerful tuning method that, within the elastic limit of the material under test, does not introduce disorder. In this review, we provide a brief recent history of strain tuning, describe current methodology, provide selected examples of the types of experiment that have been done, and discuss the thermodynamics of uniaxial stress.