Life, death and active matter

“The force that drives the flower drives my green age”

At the dawn of modern chemistry, in the 18th century, the prevailing view was that there was something special about living tissue compared to inert matter.  In conventional accounts of the development of chemistry, this view – known as “vitalism” – is widely believed to have been definitively killed by Wöhler’s synthesis of urea from inorganic starting materials in 1828, opening the way to a purely mechanical concept of biology, full of pumps and levers.

And yet, there is something special about a swimming bacteria, a crawling amoeba, a growing plant, a muscle, a heart, a brain.  We know now that what’s special about these forms of living matter isn’t some occult life-force; it’s a continuous input of free energy.  These systems are driven systems, sustained far from equilibrium by this constant free energy input.  In soft matter physics, we call this kind of matter active matter.  This encompasses not just biological tissues, but increasingly, synthetic analogues.

Active matter is characterised by the free energy input being, in some sense, internal, rather than external.  The fluid in a stirred tank or a heated pan is not at equilibrium, and this continuous free energy input can create considerable structure – for example convection cells, shear banding, or indeed, on a large scale, the wind patterns in a tropical storm.  Yet we don’t refer to these systems as active matter.  In a muscle, or the active gel of an amoeba’s cytoplasm, the free energy is being converted internally.  Active matter is characterised by a hierarchical structure, and the free energy is deployed at the scale of the sub-units of the structure.

It’s important to stress that what we’re talking about here is free energy – that fraction of total energy that can be converted into useful work, given the requirement of the second law of thermodynamics that the total entropy of the universe can never decrease.  Active systems typically operate at constant temperature, so the total energy that enters must be balanced by the energy that leaves.  The inputs – in the form of light and chemicals in a high free energy state – have a lower entropy than the heat and waste products that leave the system.  

Active matter exports entropy, and this allows it to generate order.  This is what makes all the marvellous complexity and order of life consistent with the second law of thermodynamics.

We can see how this works at the level of the whole earth.  The earth is constantly receiving energy from the sun, in the form of the high energy photons characteristic of a white-hot object with a temperature of about 6000 K.  But, given that the earth is not getting (much [1]) hotter, it must be re-radiating the same amount of energy into outer space. Since the earth is much cooler than the sun, this radiation is in the form of many low energy photons, in the infra-red, which carry away much more entropy than is brought by the fewer, higher energy photons arriving in the sun.  The earth exports entropy, and this allows it to generate order.

As in the macrocosm, so in the microcosm.  Photosynthesising bacteria – cyanobacteria – and the chloroplasts in plants harvest high energy photons from the sun, using their free energy to split water molecules. The resulting hydrogen ions are pumped across membranes, and the free energy thus stored is used to synthesise the universal biological free energy vector ATP.  Almost [2] all other organisms, directly or indirectly, exploit the free energy that cyanobacteria and plants have captured from the sun.

What do biological systems do with this constant input of free energy?  It allows them to export entropy, and thus create a little oasis of order amidst the increasing disorder of the universe as a whole.  We can roughly divide their entropy-defying activities into three categories:

  1. Construction, Assembly and Growth.  The molecular components of life – proteins, lipids, nucleic acids and polysaccharides – generally have a higher free energy than their building blocks.  So making the molecules of life needs to take place through the coupling of “uphill” reactions, that need an input of free energy, with the “downhill”, free energy releasing, reaction of ATP hydrolysis.  Then these molecular components need to be assembled to produce the functional structures of cell biology.  This usually involves the shepherding of the molecules to the right places, so that the self-assembly mechanisms of local free energy minimisation can produce functional structures.
  2. Motility.  Only in the smallest and simplest cells is diffusion sufficient to move molecules to where they are needed, so mechanisms for active transport are a precondition for the evolution of size and complexity. At the level of whole cells, many bacteria can swim towards food sources and away from toxic chemicals. In multicellular organisms like ourselves cell motility is involved in the creation and repair of tissues, while molecular scale motors permit the muscular contractions that underlie wriggling, walking, running and swimming in animals of all sorts.
  3. Information processing.  The human brain accounts for a disproportionate amount of the energy we use; there’s a deep relationship between information processing and entropy, which means that computation necessarily uses free energy.  But an organism doesn’t need a nervous system to do information processing; the basic unit of biological computing is the molecule.  Many bacteria are able to sense their environment and respond accordingly, and these kinds of capabilities underly the much greater complexity of cell-signalling in multi-cellular organisms.

Active matter, then, incorporates molecular scale components that use free energy – usually in the form of chemical fuels like ATP – to accomplish these goals.  What are the physical principles that underlie how they work?

Biological active matter is soft matter, in the sense that it operates in an environment dominated by Brownian motion, and interaction energies comparable to thermal energy.  Molecules are moving around by diffusion, weak interactions bring components together, and thermal energy breaks them apart.  

There’s an important difference between active matter and soft matter at equilibrium, though.  At equilibrium, every possible interaction can happen in reverse, with the same probability.  This “principle of detailed balance” is broken in active matter.  In biological systems, the origin of broken detailed balance arises because the concentration of the free energy vector ATP is clamped at a high, and out of equilibrium, value.  It’s the resulting directionality of time which underlies the apparently purposeful nature of what active matter enables.  It permits the construction of complex functional structures, and, by in effect rectifying Brownian motion, allows directional motion.

These are molecular machines – devices that convert chemical free energy into useful work – but they are machines that don’t depend on mechanism as we understand it macroscopically.  It’s not Newton’s laws, (or, indeed, the Schrödinger equation), that governs the behaviour of these “soft machines”.  Inertia is essentially negligible, there’s constant agitation from Brownian motion, and weak forces leading to components constantly sticking and unsticking to each other.

In biology, we see these principles at work in the molecular motors that make our muscles work, and in the active gels that allow amoeba to propel themselves by oozing along surfaces.  We’re now starting to see synthetic examples, too, in the form of self-propelled colloid particles and synthetic molecular motors made using supramolecular chemistry. 

Understanding the principles of active matter gives us a new insight into what makes living matter different.  There is a difference between the matter of life and death, but we don’t need any occult vital forces to explain it.  Living matter is active matter – it uses a constant supply of free energy, it constantly exports entropy, and it creates its own order.  Without a constant flux of free energy, the second law of thermodynamics drives everything to equilibrium, and equilibrium is death.

[1] The fact that the atmosphere is less transparent in to outgoing low energy photons than to incoming high energy photons means that at steady state the earth is warmer than it would be if it were a pure “black body” – this is the greenhouse effect.  As currently the concentration of greenhouse gases in the atmosphere is currently increasing, largely as a result of human action, the steady state temperature of the earth is increasing.

[2] A few ecosystems – notably those around deep-sea hydrothermal vents – rely on chemical sources of energy rather than the sun.

UK science must deliver on its promise of economic growth

This piece was first published on the WonkHE blog on 18 May 2026. It’s an attempt to condense the arguments I’ve been making in my three longer blogpostsUK Science in a post-liberal world, UK science policy in transition, and Winds of change for UK science policy.

For more than a decade, there’s been a remarkable cross-party political consensus in the UK in support of funding scientific research.  Despite the wider pressures on public finances, public spending on science has been increasing in real terms, and further increases are planned.  But that consensus is now breaking down – and, in my view, the wider UK research community has not yet woken up to the threat.  We can’t take continuing government and public support for science for granted, and the science funding system needs to adapt and demonstrate that it is delivering for the nation, to make sure that support continues.

The recent English local elections made clear that the old political duopoly is breaking up – and what’s driving many supporters of both Greens and Reform is a sense that the old system is broken.  “Burn it all down” is an emerging political theme. There are obvious new threats that the country needs to respond to, notably increasing geopolitical insecurity.  The Conservative Party’s plan to cut UK Research and Innovation’s funding by 20%, moving the money into direct defence R&D, is a signal that, whoever forms the next government, times are changing.

But perhaps the biggest issue the research community must face is this: the justification for increases in the government’s research budget has been that more R&D will lead to economic growth – but that growth has not materialised.  GDP per person is about 29% lower than it would have been if the pre-2008 trend had continued, and this stagnation manifests itself directly in people’s wages and living standards, which on average have barely increased over the last twenty years, and in governments’ difficulties in funding public services.

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How Sheffield became Steel City

For the first time for several decades, there are grounds for optimism about the future of Sheffield’s steel industry (very much reduced in scale though it now is). Sheffield Forgemasters (now UK state owned) is building a major new facility, and Special Melted Products (with an infusion of Taiwanese capital) is also expanding. This isn’t about the standard grades of steel for use in construction – the expansion is to meet demand for specialised forgings from speciality steels and other alloys, driven by applications in defense, aerospace, civil nuclear and energy, and influenced by a new focus on UK national resilience and industrial capacity. This gives me a pretext to republish this piece I wrote nearly ten years ago about the history of the steel industry in Sheffield – and the valuable lessons this history can teach us about innovation.

As someone interested in the history of innovation, I take great pleasure in seeing the many tangible reminders of the industrial revolution that are to be found where I live and work, in North Derbyshire and Sheffield. I get the impression that academics are sometimes a little snooty about local history, seeing it as the domain of amateurs and enthusiasts. If so, this would be a pity, because a deeper understanding of the histories of particular places could be helpful in providing some tests of, and illustrations for, the grand theories that are the currency of academics. I’ve recently read the late David Hey’s excellent “History of Sheffield”, and this prompted these reflections on what we can learn about the history of innovation from the example of this city, which became so famous for its steel industries. What can we learn from the rise (and fall) of steel in Sheffield?

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Andy Burnham, Manchesterism, and Reindustrialisation

As the Mayor of Greater Manchester, Andy Burnham, attempts to re-enter national politics, he’s talked a lot about “Manchesterism” as an approach that underlies the relative economic success of Greater Manchester in recent years, and has argued for the re-industrialization of those parts of the country that lost much of their industry in the 1980’s and 90’s.  What is behind these arguments?  I can’t claim any direct knowledge of Burnham’s plans, but I do have some insight into the development of the Greater Manchester Combined Authority’s economic strategy, which may offer some clues.  

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The slow road to digital matter

Ray Kurzweil’s book “The Singularity is Near” is twenty years old, and its thesis has become conventional wisdom in Silicon Valley.  The Singularity is an event horizon – a date at which technological growth becomes so rapid that to look beyond it becomes quite unknowable to pre-Singularity humans, a point at which machine intelligence surpasses human intelligence and goes into a recursive cycle of self-improvement.  Kurzweil’s target date for the Singularity was 2045, and in the opinion of many in Silicon Valley we’re well on schedule.

The evidence for the accuracy for Kurzweil’s prediction is, of course, recent rapid progress in AI.  But that’s not the only technological development that Kurzweil’s prediction depends on. The connection between machine super-intelligence and control over the physical world needs to be established through nanotechnology.

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Winds of change for UK science policy

The Conservative Party plans to cut funding for UK Research and Innovation (UKRI) by 20%, amounting to £6 billion over three years, reallocating the funding to military drone procurement, according to a report in Research Professional. Julia Lopez, Shadow DSIT Minister, says “we need to focus our remarkable British scientific and technological capabilities more explicitly on defence”.

We’re seeing a two-decade old cross-party consensus around science funding now breaking down.  It’s notable that UKRI was a creation of the 2015 Conservative Government, with a funding increase balanced with the explicit goal of bringing the UK’s R&D programme more directly under government control. The R&D spending plans of the current government are essentially those it inherited from the 2020 Conservative Government.  But, as its leader Kemi Badenoch has taken to saying, the Conservative Party is under new management now.

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The place of UK business in the global R&D scoreboard

My last post looked at the growth in UK government support for R&D over the last decade. But if we are interested in restoring economic growth (as we should be, given the ongoing economic stagnation that the UK has been suffering), it’s R&D carried out by businesses that is more immediately relevant in terms of its direct effect on productivity growth, through the development of new, high value goods and services, and through making existing processes more efficient.  This post takes a look at R&D done by UK-owned businesses, taking a snapshot in the year 2024.

First, I’ll pose two similar-looking questions.  First, how much R&D do UK-owned businesses do?  Second, how much R&D is done by businesses in the UK?

The best answer we have to the first question – how much R&D do UK-owned businesses do? – is £32.1 billion.  This comes from the EU R&D scoreboard, which uses publicly available data to list and rank the world’s top 2000 R&D performing companies.  According to the scoreboard, the world total of business spending on R&D from these 2000 companies in 2024 was £1.2 trillion, so the share of this total done by UK companies is about 2.7%.

For the second question – how much R&D is done by businesses in the UK? – we turn to the ONS’s survey of Business Enterprise R&D, the BERD survey.  For 2024, this gives a total business R&D spend of £55.6 billion.

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The UK’s big bet on science and technology

Between 2015 and 2023, UK government direct spending on research and development increased by 22% in real terms, and the current government plans a further 12% increase by 2029.  If one includes the subsidy for private sector R&D represented by the R&D tax credit (and one should) the total real terms increase in government support for R&D is even larger.  From the low point of austerity, in 2011, to 2023, the real terms increase was 65%, a remarkable – and, perhaps, little appreciated – figure in the context of difficult fiscal circumstances faced by those governments.  Underlying this increase is a broad consensus about the importance of R&D for economic growth, and the need for the state to invest in R&D, to correct the market failure that means that the private sector will invest less in R&D than is societally optimal.

Given this economic motivation for investing in R&D, it’s inevitable that people will ask whether the increase in government spending on R&D has resulted in a measurable increase in economic growth.  So far, the answer seems to be that it hasn’t, with the UK’s economic stagnation continuing well into its second decade.  This is an important context for the changes in science policy I discussed in my earlier post – UK science policy in transition.  The question that’s going to be asked is, when is the UK’s big bet on science and technology going to pay off?

UK government spending on R&D since 1986, expressed in real (inflation corrected) terms.  Sources: spending out-turns: UK government statistics, reduced to constant 2023 £s using GDP deflator.  Plans: 2025 Comprehensive Spending Review, corrected for anticipated inflation using OBR inflation predictions.

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AI and the problems of protein folding

The problem of predicting protein structure from sequence has been definitively solved by the AI programme AlphaFold, winning a well-deserved Nobel prize for its developers. But structure prediction is just one of at least four different problems of protein folding.  Here I introduce four different problems of protein folding: protein structure prediction, the nature of the protein folding transition, the role of proteins that don’t fold at all, and the importance of protein misfolding, particularly for diseases like Alzheimer’s disease. 

The most important contributions yet made by machine learning and artificial intelligence to science so far are unquestionably DeepMind’s AlphaFold programmes for protein structure prediction, for which Demis Hassabis & John Jumper won the Nobel prize in chemistry in 2021 (shared with David Baker, for closely related work).  Proteins are linear macromolecules; each type of protein has a unique one dimensional sequence of amino acids. For many proteins, this 1d sequence encodes a unique three dimensional structure, and it’s this 3d structure which underpins the function of the protein in the operations of the living cell.  AlphaFold takes the 1d sequence of a protein and predicts the 3d structure.  This is the problem of protein structure prediction, outstanding for half a century, now definitively solved by AI.  

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UK science policy in transition

The way the UK government funds science is currently in the midst of a major transition, with the creation of a much more direct link between the priorities of the government of the day and the kind of research that it funds.  A few months ago I wrote about the likely prospect of a breakdown of a long period of consensus in UK science policy – UK Science in a post-liberal world.  I’m not sure whether the current changes are best thought of as the first manifestation of this breakdown of consensus, or as an attempt to make those changes in the system that are necessary to preserve it.  Here I make a first attempt to set these changes in context.  

Some history

UK governments have recognised the need for the State to fund scientific research since the late 19th century, and some of the principles underpinning that were articulated early in the 20th century. One innovation of that period was the Research Council – conceived as a body standing slightly apart from government, largely managed by expert scientists.  The first of these was the Medical Research Council, established in 1920 as a body incorporated by a Royal Charter.  Subsequently, other research councils, covering other fields of science – and social science and the humanities – were established on the same principles, and various reorganisations have taken place, but the basic model remained in place until 2017.

It is important, however, to understand that for most of this period the research supported by Research Councils amounted to only a small fraction of total government R&D.  Most of this took place with the direct support of government departments, such as those responsible for agriculture, for defence and military procurement, and for atomic energy, often in government research laboratories.  Going into the 1980’s, when the UK was one of the most R&D intensive countries in the world, less than 15% of government funded R&D was supported by the research councils.

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